eunate abilleira cillero · 2016. 7. 5. · tipb 1,3,5-triisopropilbenceno tn total nitrogen tva...

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Eunate Abilleira Cillero

INFLUENCIA DE LOS SISTEMAS DE PRODUCCIÓN OVINAEN LA CALIDAD Y LAS PROPIEDADES

TECNOLÓGICAS DE LA LECHE Y EL QUESO

Vitoria-Gasteiz, 2010

TESIS DOCTORALESN.º 68

InfluencIa de los sIstemasde produccIón ovIna

en la calIdad y las propIedadestecnológIcas de la leche y el queso

Eunate Abilleira Cillero

Universidad del País vasco

Edición: 1.ªmayo2010

Tirada: 50ejemplares

© AdministracióndelaComunidadAutónomadelPaísVascoDepartamentodeMedioAmbiente,PlanificaciónTerritorial,AgriculturayPesca

Internet: www.euskadi.net

Edita: EuskoJaurlaritzarenArgitalpenZerbitzuNagusiaServicioCentraldePublicacionesdelGobiernoVasco Donostia-SanSebastián,1-01010Vitoria-Gasteiz

Impresión: EuskoPrintingService,S.L. www.eps-grupo.com

ISBN: 978-84-457-3070-6

D.L.: VI199-2010

UnregistrobibliográficodeestaobrapuedeconsultarseenelcatálogodelaBibliotecaGeneraldelGobiernoVasco:<http://www.euskadi.net/ejgvbiblioteka>.

Aitari eta Egoitzi

Este trabajo de Tesis Doctoral ha sido dirigido porLuis Javier Rodríguez Barron y Mailo Virto Lekuona, Realizado en el Área de Tecnología de Alimentos del Departamento de Farmaciay Ciencias de los Alimentos de la Facultada de Farmaciade la Universidad del País Vasco.

Nire esker ona azaldu nahi nieke tesi hau gauzatzen lagundu eta bultzatu

nauten pertsona eta erakunde guztiei. Bereziki:

Luisja eta Mailo nere tesi zuzendariei, lau urte hauetako gidaritza lanagatik eta

emandako laguntza, konfidantza eta gomendioengatik. Batez ere Luisjari,

momentu zailetan ere tesi honi eta neroni eskainitako arduragatik.

I would like to thank Dr. Hedwig Schlichtherle-Cerny for her guidance during my

short stay in Agroscope Liebefeld-Poiseaux Research Station. It was a very

enriching experience, both personally and professionally, and I’m really grateful.

Gazten Kalitatea eta Segurtasuna ikerketa taldeko lankideei eta Elikagaien

Teknologia, Biokimika eta Biologia Molekularra eta Elikadura eta Bromatologia

saileko beste lankide guztiei, beraien laguntzagatik eta elkarrekin bizitako

momentu onengatik. Analisirako Zerbitzu Zentralaren Arabako Unitateari ere

emandako laguntza eskertu nahiko nioke.

Baita ere, esne eta gazta laginak eskaini dizkiguten artzai eta gaztagileei, hala

nola Artzai-gazta elkarteari, Idiazabal Jatorrizko Izendapenari eta Neiker-eko

Animalien Ekoizpen saileko taldeari beraien aholkularitza lan finagatik.

Azkenik, nere familia eta adiskideei eskertu nahiko nieke urte luze hauetan

emandako babesa eta nere “ardi, esne eta gaztengatik” azaldu duten interesa.

Bereziki, Unairi garai gozo zein bolada ez horren gozoetan bidelagun

ezinhobea izateagatik.

Agradezco a la Universidad del País Vasco/Euskal Herriko Unibertsitatea la

admisión como becaria predoctoral y las facilidades prestadas para la

realización de esta tesis, y al Gobierno Vasco/Eusko Jaurlaritza la concesión de

una beca predoctoral (2005/09). Este trabajo ha sido posible gracias a la

financiación a través de los proyectos 9/UPV 00042.125-15317/2003, Cátedra

UNESCO 05102 y RTA 2006-00100-C02-02 (INIA).

Índice

9I

ABREVIATURAS Y SÍMBOLOS 11

RESUMEN 15

Capítulo 1. INTRODUCCIÓN 19

1. Manejo de los rebaños de oveja latxa en el País Vasco y

Navarra

21

2. Producción de leche y queso Idiazabal 23

3. Efectos de los diferentes manejos de la alimentación y el

pastoreo en la calidad de la leche y el queso

26

Capítulo 2. OBJETIVOS 31

Capítulo 3. MATERIALES Y MÉTODOS 35

1. Muestreo 37

1.1. Rebaños comerciales 37

1.2. Manejo de la alimentación 37

1.3. Muestras de leche y queso 40

2. Métodos 42

2.1. Análisis de la leche 42

2.1.1. Composición grosera 42

2.1.2. Coagulación y medidas reológicas de la cuajada 43

2.1.3. Terpenos 44

2.2. Análisis del queso 45

2.2.1. Ácidos grasos 45

2.2.2. Volátiles y compuestos odorantes 46

2.3. Análisis estadístico 48

2.3.1. Análisis de la varianza (ANOVA) 48

2.3.2. Análisis de componentes principales (PCA) 49

2.3.3. Análisis discriminante 50

2.3.4. Análisis de regresión 50

influencia de los sistemas de producción ovina en la calidad y las propiedades tecnológicas de la leche y el queso

10II

Capítulo 4. RESULTADOS Y DISCUSIÓN 51

1. Resultados 53

Manuscrito 1: Seasonal changes in the technological and

compositional quality of ewe’s raw milks from commercial

flocks under part-time grazing

55

Manuscrito 2: Effects of seasonal changes in the feeding

management under part-time grazing on the evolution of the

composition and coagulation properties of ewes’ raw milk

65

Manuscrito 3: An accurate quantitative method for the analysis

of terpenes in milk fat by headspace solid-phase

microextraction coupled to gas chromatography-mass

spectrometry

93

Manuscrito 4: Seasonal changes in terpene concentrations of

milk from ewes managed under part-time grazing

103

Manuscrito 5: Winter/Spring changes in fatty acid composition

of farmhouse Idiazabal cheese due to different flock

management systems

129

Manuscrito 6: Volatile composition and aroma-active

compounds of farmhouse Idiazabal cheese made in winter and

spring

139

2. Discusión general 173

Capítulo 5. CONCLUSIONES 181

Capítulo 6. BIBLIOGRAFÍA 187

abreviaturas y sÍmbolos

11III

ABREVIATURAS Y SÍMBOLOS

(Ag+)-HPLC silver ion high performance liquid chromatography

AEDA aroma extract dilution analysis

ANCOVA analysis of covariance

ANOVA analysis of variance

AP after pasture-flocks

BCFA branched-chain fatty acids

BP before pasture-flocks

CLA conjugated linoleic acid

CoF coagulum firmness

CRC curd resistance to compression

CuF curd firmness

DHA docosahexaenoic acid

DM dry matter

DPA docosapentaenoic acid

DVB/CAR/PDMS divinylbenzene/carboxen/polydimethylsiloxane

EI electronic impact

EPA eicosapentaenoic acid

FA fatty acid

FAD fibra ácido-detergente

FAME fatty acid methyl ester

FB fibra bruta

FND fibra neutro-detergente

G alfalfa granulada

GB grasa bruta

GC-FID gas chromatography-flame ionization detector

GC-MS gas chromatography-mass spectrometry

GC-O gas chromatography-olfactometry

GFR gel firming rate

GLM modelo lineal general

HPLC high performance liquid chromatography

HR concentrate fed-flocks


12IV

HS headspace

IMCU international milk clotting units

LCFA long-chain fatty acids

LOD limit of detection

LOQ limit of quantification

LR forage fed-flocks

LRI linear retention index

LT long time grazing-flocks

M pradera monofita

MCFA medium-chain fatty acids

MID methylen-interrupted diene

MS materia seca

MSD mass-spectrometry detector

MUFA monounsaturated fatty acids

NCN non-casein nitrogen

ND not detected

NI not identified

NMID non-methylen-interrupted diene

NNC nitrógeno no caseínico

NNP nitrógeno no proteico

NPN non-protein nitrogen

NS not significant

OAV odour activity value

OIR odour impact ratio

OT odour threshold

P pradera polifita

P probability

PAO polyalphaolefin

PB proteína bruta

PC principal component

PCA principal component analysis

PDO protective denomination of origin

PUFA polyunsaturated fatty acids

abreviaturas y sÍmbolos

13V

R alfalfa en rama

R2 coefficient of determination

RA rumenic acid

RCT rennet coagulation time

RET relative transmission

RRFTIPB relative response factor of terpenes with respect to tipb

RSD relative standard deviation

SCC somatic cell counts

SCFA short-chain fatty acids

SD standard deviation

SEr standard error of regression

SFA saturated fatty acids

SIM selected ion monitoring

SPME solid-phase microextraction

ST short time grazing-flocks

TIC total ion current

TIPB 1,3,5-triisopropilbenceno

TN total nitrogen

TVA trans-vaccenic acid

UFA unsaturated fatty acids

resumen

15

VII

RESUMEN

Esta tesis se encuadra dentro de la línea de investigación del grupo de Calidad

y Seguridad de Quesos de la UPV/EHU que estudia la influencia de la

alimentación y el manejo del rebaño en las características tecnológicas,

sanitarias y nutricionales de la leche de oveja y del queso producido a partir de

ésta.

Para ello, se ha contado con la participación de productores de leche y queso

adscritos a la Denominación de Origen Queso Idiazabal que proporcionaron

muestras de leche de tanque de sus rebaños a lo largo de la lactación, así

como muestras de queso elaborado a partir de esa misma leche.

Concretamente, se seleccionaron explotaciones de pequeño tamaño y con

rebaño propio, similares en cuanto al manejo reproductivo y alimenticio de las

ovejas. El manejo de estos rebaños buscaba el aprovechamiento máximo de

los recursos naturales por lo que el calendario productivo dependió

directamente del ritmo de crecimiento de la hierba. Consistió en una paridera

concentrada en invierno, seguida de un periodo de cría de aproximadamente

un mes, tras el cual los corderos fueron destetados para comenzar el ordeño

de las ovejas que se prolongó hasta mediados de julio. En cuanto a la

alimentación, durante los primeros meses de lactación (invierno) los rebaños se

alimentaron a base de concentrados y forrajes conservados, y a medida que la

mejora de las condiciones climáticas y la calidad de los pastos lo permitió

(primavera), esos aportes en pesebre fueron disminuyendo a favor de la hierba

fresca. Este tipo de manejo alimenticio se denomina pastoreo a tiempo parcial.

Al tratarse de rebaños comerciales con partos concentrados resulta imposible

desligar el efecto del estado de lactación de los animales de los factores

estacionales como pueden ser los cambios en la alimentación. Por lo tanto, el

objetivo de la tesis ha sido estudiar el efecto estacional asociado al manejo de


16VIII

la alimentación de los rebaños en la calidad y las propiedades tecnológicas de

la leche y el queso.

Primeramente, se estudió el efecto estacional asociado a la alimentación de las

ovejas sobre la calidad composicional y tecnológica de la leche (manuscritos

1 y 2). Se determinó la composición grosera de las muestras de leche y se

realizaron ensayos de coagulación de la leche y medidas reológicas de las

cuajadas obtenidas. El efecto estacional asociado a los cambios en el manejo

de la alimentación se tradujo en contenidos superiores de macrocomponentes

(proteína, grasa, extracto seco) y minerales (calcio y magnesio) en la leche de

los rebaños en pastoreo en estado avanzado de lactación, frente a la de los

rebaños en estabulación al inicio de la lactación. Los cambios en la

composición afectaron a la aptitud a la coagulación de la leche y a la textura de

la cuajada, siendo las cuajadas de los rebaños en pastoreo más firmes y más

resistentes a la compresión. Estas dos variables tecnológicas están muy

relacionadas entre sí y definen el parámetro de consistencia de la cuajada. Se

correlacionaron positivamente con el contenido de proteína, grasa, calcio y

magnesio de la leche. Por un lado, las proteínas y los minerales son

responsables de formar la estructura del gel, mientras que la grasa atrapada en

esa estructura aporta firmeza al gel. También se observó una correlación

positiva entre el pH de la leche y el tiempo de coagulación.

En segundo lugar, se estudiaron los compuestos terpénicos como marcadores

de trazabilidad de la leche procedente de animales en régimen de pastoreo por

el interés y la necesidad de disponer de herramientas para certificar con

fiabilidad la procedencia de los productos de pasto (manuscritos 3 y 4). Se

desarrolló un método analítico sencillo y fiable para cuantificar terpenos en la

grasa láctea, que después se aplicó en las muestras de leche recogidas a lo

largo de la época productiva de los rebaños en condiciones de campo, para

comprobar la adecuación de los terpenos como indicadores del tipo de dieta.

Como cabía esperar, el contenido total de terpenos fue más elevado en la

leche de las ovejas en pastoreo que en la leche de las ovejas estabuladas.

Además, los sesquiterpenos únicamente se detectaron en leches de rebaños

resumen

17IX

alimentados con hierba fresca. Sin embargo, la gran variabilidad observada en

la acumulación de monoterpenos y sesquiterpenos individuales no permitió

proponer con garantía un compuesto terpénico marcador del pastoreo a tiempo

parcial frente a manejos en intensivo sin pasto. No obstante, los terpenos

α-pineno y β-cariofileno se correlacionaron con la evolución estacional, por lo

que éste último podría considerarse buen candidato para cumplir esa función.

En cualquier caso, es necesario profundizar en cuestiones relacionadas con la

presencia de terpenos concretos en diferentes forrajes, así como los niveles

mínimos de acumulación y siempre contextualizar este tipo de estudios en cada

caso de interés.

Finalmente, se investigó el efecto de la estación asociado al manejo alimenticio

de los rebaños en la calidad nutricional y tecnológica del queso (manuscritos

5 y 6). Se analizaron los ácidos grasos, incluidos los ácidos linoleico

conjugados (CLA), y la composición volátil de las muestras de queso, así como

los compuestos con impacto aromático. Se observó que los quesos elaborados

a partir de la leche de los rebaños en pastoreo tenían un perfil de ácidos grasos

más saludable, puesto que contenían menos grasa saturada, un índice

aterogénico menor y niveles más altos de ácidos grasos deseables desde un

punto de vista nutricional (ácido ruménico, transvaccenico y docosahexaenoico,

entre otros). Por otro lado, el manejo en pastoreo redundó en niveles más altos

de ésteres y alcoholes entre los volátiles de los quesos analizados, en

detrimento de los compuestos carbonílicos. En los quesos de pasto los ésteres

y alcoholes odorantes se detectaron con mayor intensidad, lo cual podría ser

indicativo de notas olfativas más afrutadas y dulces que en los quesos

elaborados durante el periodo de estabulación invernal.

Los resultados de este trabajo proporcionan información útil y de interés tanto

para los productores como para los organismos de control y certificación, y

contribuye a una mejor comprensión de la relación entre el manejo de pastoreo

a tiempo parcial y la calidad de la leche y el queso.

Capítulo 1. INTRODUCCIÓN

capÍtulo 1. introducción

21

Capítulo 1. Introducción

3

1. Manejo de los rebaños de oveja latxa en el País Vasco y Navarra

La oveja latxa es una raza autóctona del País Vasco y Navarra cuya

explotación se remonta al paleolítico (4000 a.C.). Hay dos variedades que se

diferencian en la coloración de la cabeza y las extremidades: la latxa cara

negra y la latxa cara rubia. Se trata de una oveja de tamaño medio, muy ágil y

perfectamente adaptada a la orografía abrupta y a las condiciones

climatológicas de alta pluviosidad de la zona.

Junto con la oveja carranzana, emparentada genéticamente con la latxa,

constituyen la mayoría del ganado ovino censado de la CAPV y norte de

Navarra. En el censo del año 2006 figuran 423300 cabezas de latxa y 15000

efectivos de carranzana repartidas en 8000 rebaños de los cuales sólo 827

(54 % de las ovejas) superan las 100 cabezas. Los rebaños son pequeños,

siendo el tamaño medio de un rebaño profesionalizado de unas 260 ovejas

(Ugarte, 2007). Generalmente, la dedicación no suele ser exclusiva y los

ganaderos tienen otras actividades complementarias, fundamentalmente la

elaboración de queso y la explotación de vacuno de carne y de leche. Se trata

de explotaciones cuya actividad está orientada a mantener la economía familiar

ya que la mano de obra asalariada es prácticamente inexistente (IKT, 2007;

ITG Ganadero, 2007).

Los calendarios de producción están condicionados por el manejo de la

alimentación que, al estar basado en el aprovechamiento de recursos

naturales, depende directamente del ritmo de crecimiento de la hierba. Por ello,

los calendarios de producción varían ligeramente de una zona a otra en función

de la climatología del lugar. En general, el sistema se basa en una única

paridera por año que se concentra en otoño-invierno. Tras un periodo de cría

de aproximadamente un mes se procede al destete de los corderos y comienza

el ordeño de las ovejas. El ordeño se prolonga hasta el final de primavera o

mediados de verano (Ruiz, 2009).


22


4

Las ovejas se alimentan de pasto siempre que las condiciones lo permiten con

el fin de aprovechar al máximo los recursos naturales disponibles. En muchos

casos los pastizales cercanos a la explotación, conocidos como pastos de

fondo de valle, son insuficientes para soportar la producción del ganado a lo

largo de todo el año, por lo que es bastante frecuente la trashumancia a pastos

de montaña. Los animales suelen ser conducidos a estos pastos de montaña

tras el secado (final del verano) y permanecen allí hasta que la nueva gestación

ya está avanzada (final del otoño) (Ruiz y Oregui, 1998). La excepción la

conforman los pastores que suben sus ovejas al monte en primavera para

aprovechar esos pastos de montaña, mientras el rebaño aún produce leche, y

elaborar queso de montaña, aunque este colectivo está disminuyendo por la

dureza y la exigencia que este trabajo de montaña supone.

El final de la gestación e inicio de la lactación es la época más exigente en

cuanto a necesidades nutricionales y, al ser invierno, la hierba de los pastos

escasea. En este periodo las ovejas son alimentadas en pesebre a base de

concentrados y forrajes conservados (Ruiz y Oregui, 1998). Con la llegada de

la primavera, las condiciones climáticas y la calidad del pasto mejoran y

permiten ir reduciendo paulatinamente el aporte de concentrado y forrajes de la

dieta en favor de la hierba fresca, sin que ello comprometa la producción

(Perojo et al., 2005; Arranz et al., 2009). La fecha de salida al pasto (y la época

de partos) suele ser más temprana en los valles de la vertiente cantábrica

puesto que la primavera suele llegar un mes antes allí que a las zonas más

altas y del interior. Así, durante el periodo principal de producción lechera,

gracias al pastoreo a tiempo parcial, se optimiza el uso del pasto y se limita el

aporte de suplementos en pesebre contribuyendo a la sostenibilidad del

sistema.

Además de la ventaja económica que supone a los ganaderos el

aprovechamiento de los recursos naturales, la utilización de los pastos tiene

implicaciones ecológicas, sociales y culturales no menos importantes. La

presencia de rumiantes evita el embastecimiento de la vegetación y ayuda al

mantenimiento de la biodiversidad y del paisaje, gracias a lo cual se reduce el

riesgo de incendios forestales y se habilitan espacios que pueden ser


23


5

destinados a usos recreativos. La actividad pastoril contribuye al desarrollo

socio-económico de las zonas rurales y frena el abandono de la población,

porque hace que la producción de leche y queso bajo este esquema de manejo

sea rentable y sostenible (Ruiz, 2009).

2. Producción de leche y queso Idiazabal

Los datos productivos de la raza latxa varían ligeramente en función del ecotipo

y la zona geográfica de producción, pero de forma general la lactación real

media dura unos 160 días y cada oveja puede llegar a producir 150 litros en

ese tiempo (Ugarte, 2007). Anualmente se producen en torno a 15 millones de

litros de leche en CAPV y Navarra de los cuales aproximadamente la mitad se

transforman en queso en las propias explotaciones y la otra mitad se vende a

industrias queseras de mayor tamaño (Ruiz, 2009).

Al tratarse de un manejo que comprende un parto por año, la producción de

leche y queso es estacional y abarca desde invierno hasta verano. Debido al

manejo generalizado de partos concentrados, las curvas de lactación de las

ovejas y sus picos productivos coinciden y la producción de queso se concentra

principalmente en primavera. Por lo tanto, a medida que avanza la época de

producción la composición de la leche de tanque del rebaño también va

evolucionando por efecto de la lactación y hay un aumento notable de grasa

(incremento del 25 %) y proteína (incremento del 13 %) que se traduce en un

incremento del extracto seco (incremento del 11 %) (Barron et al., 2001). A

pesar de que el rendimiento lechero de las ovejas sufra un acusado descenso a

partir del tercer mes de lactación (Ruiz et al., 2000), el aumento del extracto

seco provoca que el rendimiento quesero aumente (incremento del 11 %)

(Barron et al., 2001).

Cuando se trata de rebaños comerciales, el hecho de que el estado fisiológico

de todos los animales del rebaño evolucione a la par, hace imposible desligar el

efecto del estado de lactación de los animales de los factores estacionales o

externos, como pueden ser los cambios en la alimentación, haciendo más


24


6

complicado su estudio en condiciones de campo. Estas variaciones

estacionales motivadas por el momento de la lactación en que se encuentran

las ovejas, se perciben más claramente en las explotaciones pequeñas que

transforman la leche de su propio rebaño que en las queserías industriales que

elaboran queso a partir de leche mezclada procedente de diferentes rebaños

(Pérez-Elortondo, 1998).

En cualquier caso, tanto las queserías pequeñas como las industriales elaboran

el queso Idiazabal a partir de leche cruda de oveja latxa y/o carranzana

siguiendo lo establecido por el Reglamento de la Denominación de Origen

Queso Idiazabal que se aprobó en 1987 (MAPA, 1993) y como se muestra

esquemáticamente en la Figura 1. El queso Idiazabal es un queso de pasta

prensada, no cocida, puesto que no se superan los 37 ºC en ningún momento

de la elaboración, y está considerado “semi-duro” o “duro” en función del

tiempo de maduración, que en todo caso debe ser superior a 2 meses (de

Renobales et al., 2008). Un rasgo típico de la elaboración del queso Idiazabal

es el empleo de cuajo de cordero en pasta que le confiere al queso su sabor

“picante” característico (Virto et al., 2003), aunque también se permite el uso de

cuajo animal comercial o una mezcla de ambos. Tal y como señala el

Reglamento de la Denominación de Origen Queso Idiazabal, el queso debe

tener un sabor intenso, equilibrado y característico a leche madurada de oveja,

que a su vez debe ser limpio y consistente con un ligero toque a cuajo natural.

Se debe percibir un olor intenso, limpio y penetrante a leche de oveja,

ligeramente picante y con intensidad variable de aroma ácido y dulce (Pérez-

Elortondo, 1998).

Las primeras referencias científicas al queso Idiazabal aparecen en la década

de los 70 y 80 en trabajos que estudian la composición de diferentes quesos

elaborados en la Península Ibérica (Marcos et al., 1983). Sin embargo, hasta la

creación del grupo de investigación de Calidad y Seguridad de Quesos de la

Universidad del País Vasco/Euskal Herriko Unibertsitatea en 1989 no se inició

una caracterización científica y sistemática del mismo. Desde entonces éste, y

otro grupo creado posteriormente en la Universidad Pública de Navarra, han

llevado a cabo una investigación básica y estratégica orientada a caracterizar


25


7

los procesos bioquímicos, microbiológicos y tecnológicos implicados en la

fabricación del queso Idiazabal que influyen directamente en su calidad

sensorial, tecnológica, nutritiva e higiénico-sanitaria (de Renobales et al.,

2008).

1. Leche cruda de oveja pH 6.5-6.8 + cultivo iniciador homofermentativo

2. Adición de cuajo:• Cordero en pasta• Animal comercial• Mezcla de ambos

Coagulación a 28-32 ºC en 20-45 min

3. Corte y desuerado diámetro del grano 5-10 mm

5. Moldeado:• Diámetro 10-12 cm• Altura 8-12 cm

4. Recalentado < 38 ºC, 25 min

6. Prensado 6-10 h

7. Inmersión en salmuera:• 14-16 h a 9-12 ºC• Densidad 16-19 ºBé

8. Maduración:• Mínimo 2 meses• 8-12 ºC y Hr 85 %

1. Leche cruda de oveja pH 6.5-6.8 + cultivo iniciador homofermentativo

2. Adición de cuajo:• Cordero en pasta• Animal comercial• Mezcla de ambos

Coagulación a 28-32 ºC en 20-45 min

3. Corte y desuerado diámetro del grano 5-10 mm

5. Moldeado:• Diámetro 10-12 cm• Altura 8-12 cm

4. Recalentado < 38 ºC, 25 min

6. Prensado 6-10 h

7. Inmersión en salmuera:• 14-16 h a 9-12 ºC• Densidad 16-19 ºBé

8. Maduración:• Mínimo 2 meses• 8-12 ºC y Hr 85 %

Figura 1. Esquema de las etapas de elaboración del queso Idiazabal

Entre los numerosos trabajos desarrollados se encuentran el establecimiento

de la definición sensorial del queso Idiazabal (Pérez-Elortondo, 1998; Bárcenas

et al., 1999), el estudio en profundidad del cuajo de cordero en pasta artesanal

(Bustamante et al., 2000; Virto et al., 2003; Gil et al., 2007) y otros aspectos


26


8

tecnológicos tales como los procesos de salado y ahumado (Pérez-Elortondo et

al., 1993; Nájera et al., 1994; Pérez-Elortondo et al., 2002), la adición de

lipasas (Hernández et al., 2009), la pasteurización de la leche (Ordoñez et al.,

1999; Chavarri et al., 2000) y el desarrollo de volátiles (Barron et al., 2005a)

entre otros. A pesar de contar con trabajos sobre el efecto de la estacionalidad

en la calidad de la leche de partida y el queso (Mendia et al., 2000; Perea et al.,

2000; Barron et al., 2001), el grupo de investigación ha comenzado a abordar

en profundidad el efecto del manejo de los animales desde hace relativamente

poco tiempo gracias a la colaboración del departamento de Producción Animal

del Instituto Vasco de Investigación y Desarrollo Agrario (Neiker).

El interés por la relación entre la alimentación y la calidad de la leche y el

queso no sólo atañe a los ganaderos que buscan optimizar la producción y el

aprovechamiento de recursos, sino también a los consumidores que muestran

una preocupación creciente por adquirir productos más saludables y

elaborados bajo unas prácticas que respetan el medio ambiente y el bienestar

animal (Bernués et al., 2003; de Renobales et al., 2008). En este sentido, el

trabajo desarrollado en esta tesis pretende ser una contribución que ayude a

comprender mejor esa relación centrando su interés en el manejo de pastoreo

a tiempo parcial.

3. Efectos de los diferentes manejos de la alimentación y el pastoreo

en la calidad de la leche y el queso

La calidad del queso está directamente relacionada con la composición y la

calidad de la leche con la que se elabora. Esta calidad puede entenderse y

evaluarse con criterios muy diferentes considerando aspectos higiénico-

sanitarios, nutricionales, tecnológicos o incluso sensoriales. La calidad de la

leche, en todas sus vertientes o interpretaciones, está ligada a sus propiedades

físico-químicas y a su contenido en macrocomponentes (grasa, proteína y

lactosa) y microcomponentes (minerales, vitaminas, ácidos grasos minoritarios,

colesterol o terpenos). Todo esto depende de diversos factores productivos,

relacionados entre sí, que tienen que ver con los animales, el entorno y las


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9

prácticas agro-ganaderas de cada explotación. A pesar de la complejidad de

las relaciones entre factores, el manejo de la alimentación es uno de los más

importantes puesto que las variaciones estacionales y la evolución fisiológica

de los animales se ven reflejados en los cambios de la naturaleza y la cantidad

de los alimentos que ingiere el rebaño (Morand-Fehr et al., 2007).

Existen diferentes revisiones bibliográficas muy interesantes que tratan

ampliamente el efecto de la nutrición de los rumiantes y su manejo sobre la

producción y composición de la leche (Walker et al., 2004; Pulina et al., 2006;

Morand-Fehr et al., 2007). En general, la composición y el contenido de

proteína apenas sufren variaciones por el manejo y la alimentación, mientras

que la grasa es muy sensible a cambios en la dieta (Pulina et al., 2006). En

sistemas intensivos de ración total mezclada se ha llegado a un control muy

minucioso de producción y composición de la leche, pero la comprensión de

cómo afecta la nutrición en sistemas basados en pastoreo es, hoy en día,

mucho más limitada (Walker et al., 2004). Estudios llevados a cabo con

rebaños de ovejas (Martínez, 2008) y cabras (Min et al., 2005) han demostrado

que es posible alcanzar una buena producción lechera afectando mínimamente

a la composición en sistemas basados en pastoreo y limitando el aporte de

concentrados, lo cual pone de manifiesto la importancia de la calidad de los

pastos empleados, así como la necesidad de aprovechar y gestionar bien los

recursos naturales.

La composición de la leche juega un papel crucial en la aptitud para la

coagulación de la misma (Guinee et al., 1997), y teniendo en cuenta que en

ovino casi la totalidad de la producción lechera se destina a la fabricación de

queso, esta aptitud se ha convertido en uno de los principales parámetros

tecnológicos de estudio. En la elaboración de la mayoría de los quesos,

incluido el Idiazabal, se emplea cuajo como agente coagulante de la leche

estando su actividad enzimática fuertemente influenciada por el pH, la

temperatura y la concentración de proteína y calcio de la leche (Lucey et al.,

2003; Nájera et al., 2003). La mayoría de los estudios de coagulación de la

leche han sido realizados en vacas, observándose resultados contradictorios

en cuanto al efecto de la alimentación en pasto sobre los parámetros de


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10

coagulación (Bovolenta et al., 2002; Joudu et al., 2008). Sin embargo, se ha

observado que el aumento de sólidos (proteína y grasa en la leche) causado

por efecto combinado de la lactación y la alimentación se relaciona con una

mayor firmeza de la cuajada (Guinee et al., 1997; Auldist et al., 2002). En otro

estudio en el que se comparaban animales en pastoreo frente a animales

estabulados como control, se observó mayor firmeza de la cuajada en la leche

de los animales en pastoreo, con independencia de la época de lactación

(Berry et al., 2001).

Otra etapa muy importante en el proceso de elaboración del queso es la

maduración. En esta última etapa, que es la más larga de todo el proceso, tiene

lugar el desarrollo de los compuestos responsables del sabor y el aroma que

caracterizan a cada tipo de queso. El aroma de un queso es el resultado de un

fino equilibrio entre cientos de compuestos volátiles que se generan en las

reacciones de glucolisis, proteolisis y lipolisis a lo largo de la maduración

(McSweeney y Sousa, 2000). Sin embargo, no todos los compuestos volátiles

contribuyen de la misma manera al aroma global, y sólo unos pocos tienen un

poder odorante apreciable por el olfato humano (Curioni y Bosset, 2002).

Algunos autores han señalado que compuestos volátiles que aparecen en el

queso pueden haber sido transferidos directamente de los alimentos a la

sangre y de ahí a la leche, a través del aire inhalado por los animales, los

gases que se generan en el rumen o por absorción directa en el tracto digestivo

(Shipe et al., 1962; Carpino et al., 2004b). Es por ello que la influencia de la

alimentación en pastoreo sobre las características organolépticas de la leche y

sus derivados suscita un gran interés entre los investigadores y los

elaboradores de queso.

Los efectos positivos del pasto de primavera en las propiedades sensoriales de

la leche fueron descritos por primera vez en 1757 (Bradley, 1757). Posteriores

estudios también evidenciaron esos beneficios en productos lácteos (Wigan,

1951), pero ha sido en las últimas décadas cuando se ha profundizado en el

estudio de los compuestos responsables de esa calidad sensorial diferenciada

de la leche y queso de pasto. En este sentido, varios autores han encontrado

diferencias cualitativas y cuantitativas importantes en los compuestos volátiles,


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y de aquellos con impacto aromático, entre quesos elaborados con leche de

animales estabulados y los obtenidos con leche de animales en pastoreo

(Carpino et al, 2004b; Coulon et al., 2004). Como consecuencia de la ingesta

de pasto, los quesos presentaron un mayor número de compuestos odorantes,

así como notas florales y herbáceas más pronunciadas (Carpino et al., 2004a).

La alimentación en régimen de pastoreo modifica también el perfil nutricional de

la leche y el queso. Es importante comprender bien esta relación para poder

ofrecer al consumidor productos que, además del placer sensorial, le aporten

beneficios nutricionales (Walther et al., 2008). La grasa láctea no ha gozado de

muy buena opinión en los últimos años porque su ingesta se ha relacionado

con el riesgo de padecer enfermedades coronarias por su alto grado de

saturación (ácidos láurico, mirístico y palmítico) y presencia de isómeros trans-

insaturados (Berner, 1993). Sin embargo, como se ha citado al inicio de este

apartado, la grasa de la leche es el nutriente más sensible a los cambios en la

alimentación lo cual permite manipular no sólo el contenido total de grasa sino

también la composición de la misma (Palmquist et al., 1993; Chilliard et al.,

2000; Pulina et al., 2006).

La hierba fresca es una excelente fuente de ácidos grasos poliinsaturados

(Cabiddu et al., 2005) que al ser ingerida por los rumiantes provoca que el

contenido de ácidos grasos saturados de la leche disminuya a favor de los

insaturados, mejorando notablemente su perfil nutricional (Schroeder et al.,

2003). Además, la alimentación de pasto promueve la acumulación de otros

ácidos grasos minoritarios denominados en conjunto ácido linoleico conjugados

(CLA), cuyos beneficios potenciales para la salud han sido descritos en los

últimos años (Parodi et al., 2006). Algunos autores atribuyen a estos ácidos

CLAs efectos anticarcinogénicos, preventivos frente a enfermedades

caridiovasculares, de reducción de la grasa corporal, inmunológicos,

antiinflamatorios y relacionados con la salud ósea (Yeonhwa y Pariza, 2009).

Por todo ello, ha surgido un gran interés por parte de los organismos de control

por disponer de herramientas para certificar con fiabilidad (trazabilidad) que un

producto proviene de animales alimentados con pasto, puesto que esto


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12

permitiría diferenciar estos productos y dotarlos de un mayor valor añadido. La

existencia de una etiqueta de calidad distintiva de los productos de pasto

beneficiaría tanto a productores como a consumidores, asegurando la calidad

de estos productos y contribuyendo a la sostenibilidad de los sistemas de

producción en pastoreo.

En las últimas décadas, varios autores han tratado de buscar compuestos de

origen vegetal, presentes en la hierba de los pastos, que tras ser ingeridos por

los rumiantes fueran trasferidos a la leche y al queso, de manera que pudieran

ser utilizados como indicadores del tipo de dieta de los animales (Fernández et

al., 2003; Prache et al., 2005; Engel et al., 2007). Una de las familias de

compuestos más estudiadas con este fin ha sido la de los terpenoides,

compuestos derivados del metabolismo secundario de las plantas, formados

por dos o más unidades de isopreno (Bouvier et al, 2005). Varios autores han

observado que los terpenos se transfieren rápidamente del forraje a la leche

(Viallon et al., 2000) pero también que pueden sufrir cambios y modificaciones

en el rumen, lo cual podría disminuir su potencial como compuestos

indicadores (Schlichtherle-Cerny et al., 2004). Otro aspecto que dificulta su uso

como marcadores es que existen grandes diferencias en cuanto al contenido

de terpenoides en diferentes especies botánicas (Mariaca et al., 1997; Cornu et

al., 2001; Fedele et al., 2007). Por lo general, las monocotiledóneas son pobres

en terpenos, especialmente sesquiterpenos, mientras que las dicotiledóneas

son ricas en estos compuestos (Mariaca et al., 1997; Viallon et al., 2000). El

tipo de terpeno y cantidad acumulada en una planta está condicionado a su vez

por otros factores intrínsecos dependientes del estado de maduración de la

planta, y otros de origen ambiental (Rajeswara Rao et al., 1995; Sangwan et

al., 2001). Esta gran variabilidad, unida a la falta de una metodología que

permita de forma sencilla y fiable cuantificar estos compuestos en los productos

lácteos hace aún cuestionable la utilidad de los terpenos como marcadores de

alimentación de animales en pastoreo.

Capítulo 2. OBJETIVOS

capÍtulo 2. objetivos

33

Capítulo 2. Objetivos

15

Esta tesis se ha realizado dentro del grupo de investigación multidisciplinar de

Calidad y Seguridad de Quesos que engloba las áreas de conocimiento de

Tecnología de Alimentos, Nutrición y Bromatología y Bioquímica y Biología

Molecular de la Universidad del País Vasco/Euskal Herriko Unibertsitatea

(grupo Calidad y Seguridad de Quesos, 2009). Desde su creación en 1989,

este grupo ha trabajado en la caracterización de los procesos bioquímicos,

microbiológicos, y tecnológicos implicados en la fabricación del queso Idiazabal

que influyen directamente en su calidad sensorial y nutritiva, así como en su

seguridad higiénico-sanitaria, con el fin de poder facilitar al sector productivo la

información necesaria para obtener un producto de alta calidad y seguridad en

todas las condiciones de producción.

El objetivo general de este trabajo se sitúa dentro de la mejora de la producción

y calidad del queso Idiazabal. Concretamente, el presente trabajo forma parte

de una línea de investigación que estudia la influencia de la alimentación y el

manejo del rebaño en las características tecnológicas, sanitarias y nutricionales

funcionales de la leche de oveja y del queso producido a partir de ésta.

Los objetivos específicos planteados son:

Objetivo 1: Estudio del efecto estacional asociado al manejo de la alimentación

de los rebaños en la calidad composicional y tecnológica de la leche.

Objetivo 2: Estudio de los compuestos terpénicos como herramienta de

trazabilidad de leche procedente de animales en régimen de pastoreo.

2.1. Desarrollo de un método cuantitativo para la determinación sencilla y

fiable de compuestos terpénicos en grasa láctea.

2.2. Estudio de la presencia de compuestos terpénicos en la leche de

rebaños comerciales durante la época de lactación y en régimen de

pastoreo a tiempo parcial.


de los rebaños en la calidad nutricional funcional y tecnológica del queso.

Capítulo 3. MATERIALES Y MÉTODOS

capÍtulo 3. materiales y métodos

37

Capítulo 3. Materiales y Métodos

19

1. Muestreo

1.1. Rebaños comerciales

Se seleccionaron 11 explotaciones adscritas a la Denominación de Origen

Queso Idiazabal similares en cuanto a características de la explotación y

manejo reproductivo y alimenticio. Las explotaciones se encontraban en

localidades de altitud media (300-600 m) y alta (700-900 m), próximas a Vitoria-

Gasteiz y pertenecientes a Araba (San Vicente de Arana, Egino, Munain,

Gereñu, Gordoa, Larrea, Laleze y Abecia), Bizkaia (Abadiño) y Gipuzkoa

(Arantzazu y Legazpia). El tamaño medio de los rebaños rondaba las 200

cabezas, llegando a tener los dos más grandes cerca de 500 cabezas. Además

de la actividad ganadera, 10 de las explotaciones transformaban la leche cruda

obtenida de sus rebaños en queso. Eran explotaciones pequeñas de tipo

familiar y con un marcado carácter artesanal. Todos los rebaños concentraban

sus partos al comienzo del invierno, extendiéndose la producción de leche y

queso desde finales de enero, tras el destete de los corderos con

aproximadamente 1 mes de vida, hasta mediados de julio. Los diferentes

estudios se llevaron a cabo utilizando muestras procedentes de estos rebaños

en dos campañas de producción consecutivas.

1.2. Manejo de la alimentación

Se diseñó una encuesta para recabar información referente al manejo de la

alimentación de los rebaños. Se realizó una encuesta exhaustiva inicial a cada

pastor el primer día del muestreo y los cambios posteriores de alimentación se

anotaron en cada nueva visita. En las encuestas se anotó el tipo de alimentos

suministrados, así como la cantidad y composición de los mismos, el tiempo de

pastoreo, las zonas y tipos de pastos utilizados, y algunos aspectos productivos

del rebaño (Tabla 1).


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20

Tabla 1. Modelo de encuesta de alimentación del rebaño.

Explotación

Fecha de visita Fecha de control lechero

Inicio del ordeño

Número de ovejas en ordeño Litros totales de leche

Concentrado y subproductos Cantidad (kg/oveja y día)

Pienso a base de cereales

Pulpa remolacha

Otros:

Forrajes conservados Cantidad (kg/oveja y día)

Alfalfa

Heno de hierba

Silo de hierba

Silo de maíz

Otros:

Utilización de pastizales Horas al día

Sembrado (especificar especies)

Natural

Monte (altitud del pastizal)

La Tabla 2 muestra los tipos de alimentos empleados en las explotaciones y la

Tabla 3 recoge la composición media de los alimentos suministrados a los

rebaños, con excepción del pasto. De forma general, el manejo de la

alimentación fue similar en todas las queserías, basándose en concentrados y

forrajes conservados en invierno y haciendo un uso paulatinamente mayor de

los pastos a medida que avanzó la campaña y la calidad de la hierba permitió

el aprovechamiento de los mismos, tal y como recoge la Figura 2. La ingesta

de hierba fresca de cada rebaño se estimó teniendo en cuenta el tiempo de

permanencia en el pasto, a partir de los datos publicados por Perojo et al.


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(2005) por interpolación. Los programas de alimentación de cada explotación

apenas variaron de una campaña a la siguiente.

Tabla 2. Tipos de alimentos empleados para la alimentación de los animales y

porcentaje de explotaciones que los usaron en las dos campañas productivas.

Concentrado Forraje conservado Pastizal

Pulpa Alfalfa Heno Silo Silo Sembrado Pienso

remolacha G R hierba hierba maízNatural

M P Monte

100% 45% 36% 64% 73% 18% 18% 36% 45% 18% 36%

G: granulado; R: en rama; M: praderas monofitas; P: praderas polifitas. Especies botánicas predominantes en praderas monofitas: ryegrass inglés (Lollium perenne) y en praderas polifitas: ryegrass y trébol blanco (Trifolium repens). Los pastos naturales tenían una mayor diversidad de especies vegetales aunque no se determinó su composición. Los pastos de monte se utilizaron a partir de junio y se diferenciaron de los naturales por su localización a mayor altitud (≥ 1000 m).

Tabla 3. Composición media (g/100 g MS) de los alimentos suministrados a los

rebaños en las dos campañas productivas.

Pienso Pulpa

remolachaAlfalfa

Heno

hierba

Silo

hierba Silo maíz

MS 88.0 ± 2 88.4 ± 1.0 88.0 ± 1.9 80.5 ± 5.5 36.3 ± 4.4 35.4 ± 1.4

GB 3.2 ± 0.9 - - - - -

PB 19.7 ± 2.3 10.1 ± 0.0 18.2 ± 1.9 10.1 ± 2.8 15.8 ± 2.3 8.0 ± 0.2

FB 7.6 ± 2.1 17.8 ± 0.0 32.7 ± 9.4 32.9 ± 3.0 33.3 ± 1.3 19.3 ± 2.8

FAD - 22.9 ± 0.0 36.5 ± 8.9 35.0 ± 2.5 35.4 ± 1.1 24.1 ± 3.7

FND - 42.8 ± 0.0 52.9 ± 13.3 56.0 ± 4.7 62.1 ± 7.7 48.5 ± 11.1

Cenizas 6.9 ± 1.4 7.7 ± 0.0 11.3 ± 2.2 8.7 ± 1.2 9.5 ± 1.0 4.2 ± 1.2

MS: materia seca; GB: grasa bruta; PB: proteína bruta; FB: fibra bruta; FAD: fibra ácido detergente; FND: fibra neutro detergente.


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22

0

20

40

60

80

100

Febrero Marzo Abril Mayo Junio Julio

% r

ació

n

0,0

0,2

0,4

0,6

0,8

1,0

L le

che/

ovej

a y

orde

ño

Concentrado Forraje Pasto Rend

Figura 2. Manejo de la alimentación de los rebaños a lo largo de la época

productiva. Contribución media relativa (p/p) de cada tipo de alimento a la

ración y rendimiento lechero de los rebaños.

1.3. Muestras de leche y queso

Primera campaña: Se tomaron muestras de leche cruda de tanque (1.5 L) de

cada rebaño en duplicado antes de que los rebaños salieran a pastar en

invierno (principios de marzo) y tras un tiempo en régimen de pastoreo a tiempo

parcial en primavera (mayo). Durante el mes de mayo se registraron los

siguientes datos meteorológicos: temperatura diurna media de 14.4 ºC,

humedad relativa de 74.8 % y precipitación diaria media de 2.91 L/m2

(Euskalmet, 2009). En esta primera experiencia participaron nueve rebaños

sumando un total de 36 muestras en las que se analizó la composición de la

leche y su aptitud para la coagulación mediante medidas reológicas.


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Segunda campaña: Se realizó un muestreo a lo largo de la lactación de los

rebaños recogiendo muestras de leche cruda (1.5 L) de cada explotación una

vez al mes desde febrero a julio. Los meses de la época de pastoreo se

catalogaron como muy cálidos y muy secos a excepción de marzo y la segunda

quincena de junio los cuales fueron muy húmedos. En los meses de pastoreo

se registró una temperatura media de 16.4 ºC y una precipitación diaria media

de 2.21 L/m2 (Euskalmet, 2009). En esta segunda campaña participaron once

rebaños y el número total de muestras ascendió a 66. El objetivo fue hacer un

seguimiento de la evolución de la composición y la aptitud para la coagulación

a lo largo de toda la época productiva. Así mismo, se observó la evolución del

contenido en compuestos terpénicos de la leche para evaluar la adecuación de

estos compuestos como marcadores del tipo de alimentación. Para ello, se

desarrolló un método analítico que permitiera cuantificar de forma sencilla y

fiable estos compuestos en la grasa láctea de las muestras.

Paralelamente, se recogieron quesos elaborados en dos momentos puntuales

de la lactación en los cuales los rebaños tenían un manejo de la alimentación

muy diferente: estabulación intensiva en invierno y pastoreo a tiempo parcial en

primavera. Los quesos de invierno se elaboraron con la misma leche que se

muestreó en febrero-marzo y los de primavera con la que se muestreó en

mayo-junio. Cada quesero separó cuatro quesos procedentes de una misma

cuba de elaboración en invierno y en primavera. Se dejaron madurar en las

cámaras de las queserías, y una mitad de ellos se muestreó con 120 días y la

otra mitad con 180 días de maduración. Fueron 10 los pastores que elaboraron

queso a partir de la leche de sus rebaños por lo que se muestrearon 20 cubas

(10 queserías x 2 épocas de muestreo) que dieron lugar a 80 quesos

(2 tiempos de maduración x 2 quesos por cuba). Se analizó la composición

volátil de todas las muestras y los compuestos con impacto aromático en

ambas épocas del año. También se estudió el perfil de ácidos grasos de los

quesos de 120 días de maduración.


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2. Métodos

2.1. Análisis de la leche

2.1.1. Composición grosera

Las determinaciones de materia seca, proteína, grasa y recuentos

microbiológicos y de células somáticas fueron llevadas a cabo en el laboratorio

acreditado (acreditación nº 174/LE 381 de ENAC) para la realización de

ensayos físico-químicos y microbiológicos de leche del Instituto Lactológico de

Lekunberri (Lekunberri, Navarra).

Los componentes nitrogenados de la leche se fraccionaron según el método de

Rowland (1938), obteniéndose las siguientes fracciones: nitrógeno no proteico

(NNP) y nitrógeno no caseínico (NNC). El NNP corresponde a la fracción

soluble obtenida tras la precipitación de todas las proteínas de la leche con

ácido tricloroacético y el NNC a la fracción soluble obtenida tras la precipitación

de las proteínas caseínicas a pH 4.6. El nitrógeno total de estas fracciones y el

de la leche se determinó por el método Kjeldahl y se aplicó el factor de 6.38

para convertir el nitrógeno en proteína. El resto de fracciones se calcularon por

diferencia. El contenido final se expresó en g/100 mL.

El contenido total de calcio (g/L) de la leche se determinó siguiendo la

metodología descrita por De la Fuente et al. (1997) en un espectrómetro de

absorción atómica de llama (Perkin Elmer A Analyst 200, Mathews, NC, USA)

con lámpara de cátodo hueco. Previamente, se realizó una mineralización de la

muestra por vía húmeda en medio nítrico en sistema cerrado bajo presión

controlada y empleando la energía de las microondas (MSP 1000, CEM,

Matthews, NC, USA).


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El pH de la leche se midió a 20 ºC con un pH-metro de laboratorio (pH-Meter

GLP 21+, Crison Instruments, Barcelona) previamente calibrado con soluciones

tampón de referencia.

Todos los análisis de la composición grosera de las muestras de leche fueron

realizados por duplicado.

2.1.2. Coagulación y medidas reológicas de la cuajada

La leche cruda se atemperó a 32 ºC en un baño termostático y se coaguló

añadiendo una dosis de cuajo de 3.9 IMCU/100 mL de un cuajo bovino

comercial en polvo (NaturenTM Plus 1400 NB, CHR Hansen, Madrid, Spain). El

proceso de coagulación de la leche se monitorizó según el método descrito por

Nájera et al. (2003), utilizando un gelógrafo NT Gelograph (Gel Instrumente

AG, Thalwil, Switzerland). Este equipo registra el porcentaje de radiación

infrarroja transmitida a lo largo del proceso de coagulación, de manera que, a

medida que los coágulos de leche se van formando y se va estructurando el

gel, la radiación absorbida por los nuevos enlaces es mayor y el porcentaje de

transmisión relativa (%RET) va descendiendo. El porcentaje de transmisión

relativa mantiene una relación inversa con la firmeza del gel. En el momento en

que se forma el primer coágulo aparece un punto de inflexión en el registro

gráfico y ese punto se identifica como el tiempo o punto de toma (min). A partir

de ahí, se estableció el punto de corte (min) de la cuajada como dos veces el

tiempo de toma. La velocidad de endurecimiento del gel se calculó dividiendo la

diferencia del porcentaje de transmisión entre el punto de corte y el de toma y

la diferencia de tiempo entre ambos puntos (%RET/min).

Simultáneamente, se realizó un ensayo de compresión-extrusión en el punto de

corte para obtener un índice de la consistencia de la cuajada. Se utilizó un

equipo Texture Analyser TA-XT2i (Stable Micro Systems, Surrey, UK), con una

célula de carga de 5 kg y empleando una sonda cilíndrica de aluminio de

25 mm de diámetro. El ensayo consistió en una compresión de la cuajada

contenida en un envase de 28 mm de diámetro hasta un 50 % de su altura


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inicial. La velocidad de pre-ensayo fue 1.0 mm/s, la velocidad del ensayo

0.2 mm/s y la sensibilidad superficial 0.005 Newton. Se utilizó como índice de

consistencia la fuerza media en la fase de compresión-extrusión.

Los análisis de coagulación de las muestras de leche y las medidas reológicas

de las cuajadas fueron realizadas en duplicado.

2.1.3. Terpenos

Los terpenos fueron cuantificados en la grasa láctea de las muestras de leche

mediante micro-extracción en fase sólida y cromatografía de gases acoplada a

espectrometría de masas (SPME-GC-MS) utilizando 1,3,5-triisopropilbenceno

(TIPB, Sigma-Aldrich, Madrid, Spain) como patrón interno. El procedimiento

experimental para el desarrollo y validación del método analítico se recoge en

el manuscrito 3.

La preparación de la muestra consistió en una primera centrifugación de la

leche para separar la nata (2000 g, 4 ºC, 30 min) y una segunda etapa de

centrifugación para extraer la grasa de esa nata (17000 g, 20 ºC, 1.5 h). El

TIPB se añadió sobre esa fase oleosa y se prepararon alícuotas de 1 ± 0.005 g

en viales ámbar de 4 mL sellados con septum de silicona. Tras 10 min de pre-

equilibrio en un baño termostático de agua a 40 ºC, se expuso al espacio de

cabeza del vial una fibra DVB/CAR/PDMS (1 cm, 50/30 µm de malla, Supelco)

durante 30 min a la misma temperatura, utilizando un soporte manual para fibra

SPME (Supelco, Bellfonte, PA, USA). Los analitos atrapados en la fibra se

desorbieron a 240 ºC en el inyector (modo splitless durante 5 min) de un

cromatógrafo de gases GC 8000 series acoplado a un detector de masas MD

800 (Fisons Instruments, Milan, Italia). Se utilizó una columna capilar

Supelcowax (60 m × 0.25 mm d.i. × 0.25 µm espesor de fase, Supelco,

Bellefonte, PA, USA). Se utilizó helio como gas portador con un flujo de

1 mL/min. La temperatura del horno inicial fue de 40 ºC mantenida durante

10 min, seguido de un incremento a 5 ºC/min hasta alcanzar 110º C y una

segunda rampa a 10 ºC/min hasta 240 ºC. El detector de masas operó en modo


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27

SIM monitorizando los iones m/z 93 y 136 para los monoterpenos y m/z 93,

136, 161, 189 y 204 para los sesquiterpenos. La identificación de los

compuestos se llevó a cabo por comparación de los espectros de masas (en

modo barrido completo) y los índices de retención lineal (Van den Dool y Kratz,

1963) con los de sustancias puras, y las librerías de espectros de masas

National Institute of Standards and Technology (NIST, USA).

Los resultados se expresaron en µg/Kg grasa láctea. Los análisis de terpenos

de las muestras de leche fueron realizados por duplicado.

2.2. Análisis del queso

2.2.1. Ácidos grasos

Se tomó una porción (~180 g) de queso y tras eliminar 1.5 cm de corteza se

trituró para la extracción de la fracción lipídica. La grasa se extrajo partiendo de

10 g de queso triturado con n-pentano y utilizando un equipo Soxhlet. La grasa

extraída se disolvió en n-hexano y los ésteres metílicos de los ácidos grasos se

obtuvieron por trans-esterificación de los glicéridos con metanol en medio

básico de acuerdo a la norma ISO 15884 (ISO, 2002).

El análisis de ácidos grasos se realizó según Collomb y Bühler (2000). La

separación se hizo por cromatografía de gases utilizando un equipo Agilent

6890 (Santa Clara, CA, USA) con una columna capilar CP-Sil 88 (100 m ×

0.25 mm d.i. × 0.20 µm espesor de fase; Varian BV, Middleburg, The

Netherlands) y un detector de ionización de llama (FID). Se empleó hidrógeno

como gas portador con un flujo constante de 1.5 mL/min. El horno se programó

inicialmente a 60 ºC durante 5 min, incrementándose a 14 ºC/min hasta 165 ºC,

seguido de una isoterma a esa temperatura 1 min, un segundo incremento de

temperatura a 2 ºC/min hasta 225 ºC y una isoterma final de 17 min. La

identificación los ácidos grasos se llevó a cabo por comparación con los

tiempos de retención de sustancias puras y con datos cromatográficos


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publicados por otros autores (Precht y Molkentin, 1997; Sehat et al., 1998). Los

ácidos grasos fueron cuantificados usando el ácido n-nonanóico como patrón

interno.

El mismo extracto de ésteres metílicos se utilizó para la separación y el análisis

cuantitativo de los isómeros del CLA siguiendo el método de Kraft et al. (2003)

adaptado del método original de Ricker et al. (1999). Se analizó en un

cromatógrafo de líquidos de alta resolución equipado con un detector de

fotodiodos (Agilent LC series 1100 HPLC, Santa Clara, CA, USA), operando a

λ = 234 nm, y tres columnas en serie de acero inoxidable ChromSpher Lipid

(25 cm × 4.6 mm d.i., 5 µm diámetro de partícula, Chrompack, Middleburg, The

Netherlands). La fase móvil estuvo compuesta por n-hexano con un 0.1 % de

acetonitrilo y 0.5 % de etil éter, con un flujo isocrático de 1 mL/min. La

identificación de los isómeros se realizó por comparación con los tiempos de

retención de sustancias puras y con datos cromatográficos publicados por otros

autores (Yurawecz et al., 1998; Kramer et al., 1999).

Los análisis GC y HPLC de las muestras de queso se hicieron en duplicado y

los resultados se expresaron como mg ácido graso/100 g grasa o g ácido

graso/100 g grasa.

2.2.2. Volátiles y compuestos odorantes

Los compuestos volátiles se analizaron mediante micro-extracción en fase

sólida del espacio de cabeza seguido de cromatografía de gases acoplada a

espectrometría de masas. En el caso de los compuestos con impacto

aromático, el procedimiento fue el mismo que para los volátiles y se detectaron

por olfatometría.

Se introdujeron 4 g de queso triturado en viales de 20 mL y se añadieron 8 mL

de tampón fosfato 0.1 M para fijar el pH en torno a 8 y limitar la liberación de

ácidos al espacio de cabeza. Finalmente, se homogenizó la mezcla con un

homogenizador Polytron 10/35 (Kinematica AG, Lucerne, Switzerland).


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La extracción de los volátiles del espacio de cabeza se realizó de forma

automática utilizando un muestreador automático Combi PAL Autosampler

(CTC Analytics, Zwingen, Switzerland) provisto de una fibra DVB/CAR/PDMS

(2 cm, 50/30 µm de malla; Supelco, Bellefonte, PA, USA). Tras 15 min de pre-

equilibrio a 40 ºC, se realizó una extracción de 45 min a la misma temperatura.

Los analitos se desorbieron a 260 ºC en el inyector (modo splitless durante

5 min) de un cromatógrafo de gases Agilent 5890 Series II (Agilent

Technologies, Wilmington, DE, USA) equipado con una columna capilar

HP-5ms (30 m × 0.25 mm d.i. × 0.25 µm espesor de fase; Agilent Technologies)

y con un flujo constante de helio de 2.40 mL/min. La temperatura del horno

inicial fue de 38 ºC mantenida durante 5 min seguido de un incremento a

4 ºC/min hasta alcanzar los 250 ºC. El equipo disponía de dos detectores

montados en paralelo y, llegado a este punto, el flujo proveniente de la columna

se dividía en dos partes iguales. Una parte se dirigía a un detector de masas

MSD HP 5971 (Agilent Technologies), que operó en modo barrido completo, y

la otra a un detector olfatométrico (Sniffer 9000 systems, Brechbühler,

Switzerland) en cuyo puerto un único analista anotó los descriptores y tiempos

de retención de los olores percibidos en el efluente.

La identificación de los compuestos se llevó a cabo por comparación de los

espectros de masas y los índices de retención lineal (Van den Dool y Kratz,

1963) con los de sustancias puras y las librerías de espectros de masas Wiley

138.L y 275.L (John Wiley & Sons, Hoboken, JF, USA). Para la confirmación

experimental de la identificación de los compuestos volátiles, se llevaron a cabo

análisis en el mismo equipo pero utilizando una columna capilar DB-FFAP

(30 m × 0.25 mm d.i. × 0.25 µm espesor de fase; Agilent Technologies). El

horno fue programado a 40 ºC durante 5 min, seguido de un incremento a

5 ºC/min hasta 240 ºC e isoterma final de 5 min.

Los resultados se expresaron como áreas absolutas o áreas relativas de cada

compuesto obtenidas a partir de los picos cromatográficos. En el análisis

olfatométrico se definió un indicador denominado Relación de Impacto


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30

Aromático (OIR) para estimar la contribución de cada compuesto odorante

detectado al olor global del queso:

OIR = Área absoluta del pico/ (volumen del vial × umbral olfativo)

La finalidad de este OIR fue exclusivamente comparativa puesto que la

metodología empleada no permitía cuantificar los compuestos responsables del

olor.

Todos los análisis se realizaron por duplicado.

2.3. Análisis estadístico

Los datos se analizaron utilizando el paquete estadístico SPSS versión 16.0 y

17.0 (SPSS Inc., Chicago, Illinois, USA).

2.3.1. Análisis de la varianza (ANOVA)

El Modelo Lineal General (GLM) utilizado fue diferente en función del diseño

experimental y objetivos de cada estudio.

• En el estudio comparativo de leches de rebaños estabulados al inicio de la

lactación frente a leche de rebaños en régimen de pastoreo a tiempo parcial

al final de la lactación (primera campaña), se utilizó un ANOVA de 2 vías

para determinar la presencia de diferencias significativas (P ≤ 0.05) entre las

dos épocas con manejos alimenticios diferentes. Se incluyó la “estación”

como efecto principal y en el caso de los parámetros de coagulación se

llevó a cabo un análisis de la covarianza (ANCOVA) introduciendo el pH

como covariable en el modelo. El “rebaño” se introdujo como efecto

aleatorio en el modelo. En aquellos casos en los que la interacción

“estación*rebaño” fue no significativa (P > 0.05), se consideró la “estación”

como factor fijo anidado en el factor “rebaño”. Por el contrario, cuando la

interacción “estación*rebaño” fue significativa (P ≤ 0.05), se contrastó el

estadístico-F del factor “estación” contra el del término interacción

“estación*rebaño”. El mismo modelo lineal general se utilizó para determinar la


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presencia de diferencias significativas (P ≤ 0.05) entre los rebaños

estabulados alimentados principalmente con concentrados frente a los

rebaños alimentados principalmente a base de forrajes, y también para el

caso de los rebaños en pastoreo que permanecían 16-19 h en el pasto

frente a los que pastaban únicamente 6-8 h al día.

• En el estudio en el que se hizo un seguimiento de los rebaños a lo largo de

la época de producción (segunda campaña), se aplicó un modelo mixto de

ANOVA de medidas repetidas para determinar la presencia de diferencias

significativas (P ≤ 0.05) en las variables de las muestras de leche

analizadas. El efecto “estación” fue considerado como factor intra-sujeto

(factor de medidas repetidas) mientras que el efecto “rebaño” se introdujo

como factor inter-sujeto (factor fijo) en el modelo lineal general.

• En el estudio comparativo de quesos elaborados con leches de invierno de

rebaños estabulados frente a los quesos elaborados con leches de

primavera de rebaños en régimen de pastoreo (segunda campaña), se

aplicó un ANOVA de 2 vías para determinar la presencia de diferencias

significativas (P ≤ 0.05) entre las dos épocas con manejos alimenticios

diferentes, tal y como se ha descrito en el estudio de las muestras de leche

de la primera campaña. En este caso, la interacción “estación*quesería” fue

siempre significativa (P ≤ 0.05) para todas las variables estudiadas, por lo

que se contrastó el estadístico-F del factor “estación” contra el del término

interacción “estación*quesería” en todos los casos. En el estudio de la

composición de los compuestos volátiles del queso, los datos de los quesos

de 120 días de maduración fueron introducidos en el modelo lineal general

como covariable.

2.3.2. Análisis de componentes principales (PCA)

Se aplicó el análisis de componentes principales con objeto de reducir el

número total de variables analizadas a un número mínimo de componentes, y


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buscar correlaciones entre variables analíticas de las muestras y aquellas

dependientes del manejo de los rebaños. Para la selección de componentes se

aplicó el criterio de Kaiser (valor propio del factor > 1), y se realizó una rotación

ortogonal de los factores por el método Varimax con objeto de facilitar la

interpretación de los resultados. La representación bidimensional de factores

principales se utilizó para observar la distribución espacial de las muestras, y su

grado de agrupación, en función del efecto estudiado (tipo de manejo y época

productiva).

2.3.3. Análisis discriminante

Se realizó un análisis discriminante con las variables de composición y

parámetros tecnológicos de la leche con objeto de clasificar las muestras de

leche de la segunda campaña en función del manejo de la alimentación,

codificando las muestras en tres grupos diferenciados: rebaños estabulados,

rebaños con alimentación de transición al inicio del pastoreo y rebaños

aclimatados al pasto.

2.3.4. Análisis de regresión

Se aplicó el análisis de regresión lineal simple para la estimación de los

parámetros de la pendiente, ordenada en el origen y coeficiente de

determinación (R2) correspondientes a las rectas de calibrado (área de pico

cromatográfico frente a concentración de compuesto en la matriz de

calibración) de sustancias puras, en el estudio del desarrollo del método

cuantitativo para el análisis de terpenos en leche por SPME-GC-MS.

Capítulo 4. RESULTADOS Y DISCUSIÓN

capÍtulo 4. resultados y discusión

53

Capítulo 4. Resultados y Discusión

35

1. Resultados

En respuesta a los objetivos específicos planteados se realizaron los siguientes

manuscritos:


de los rebaños en la calidad composicional y tecnológica de la leche.

Manuscrito 1. Seasonal changes in the technological and

compositional quality of ewe’s raw milks from commercial flocks under

part-time grazing. Journal of Dairy Research, 76: 301-307, 2009.

Manuscrito 2. Effects of seasonal changes in the feeding management

under part-time grazing on the evolution of the composition and

coagulation properties of ewes’ raw milk. Manuscrito enviado a la revista

Journal of Dairy Science el 9 de diciembre de 2009, Ref.: JDS-09-2983.

Objetivo 2: Estudio de los compuestos terpénicos como herramienta de

trazabilidad de leche procedente de animales en régimen de pastoreo.

2.1. Desarrollo de un método cuantitativo para la determinación sencilla y

fiable de compuestos terpénicos en grasa láctea.

Manuscrito 3. An accurate quantitative method for the analysis of

terpenes in milk fat by headspace solid-phase microextraction

coupled to gas chromatography-mass spectrometry. Food

Chemistry, 120: 1162-1169, 2010.

2.2. Estudio de la presencia de compuestos terpénicos en la leche de

rebaños comerciales durante la época de lactación y en régimen de

pastoreo a tiemo parcial.

Manuscrito 4. Seasonal changes in terpene concentrations of milk

from ewes managed under part-time grazing. Manuscrito enviado a la

revista Journal of Agricultural and Food Chemistry, el 1 de diciembre de

2009, Ref.: jf-2009-04162g.


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de los rebaños en la calidad nutricional funcional y tecnológica del queso.

Manuscrito 5. Winter/spring changes in fatty acid composition of farmhouse Idiazabal cheese due to different flock management systems. Journal of Agricultural and Food Chemisty, 57: 4746-4753, 2009.

Manuscrito 6. Volatile composition and aroma-active compounds of farmhouse Idiazabal cheese made in winter and spring. En prensa,

International Dairy Journal. Doi: 10.1016/j.idairyj. 2010.02.012.


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Manuscrito 1. Seasonal changes in the technological and compositional

quality of ewe’s raw milks from commercial flocks under part-time grazing

Journal of Dairy Research, 76: 301-307, 2009


57

Seasonal changes in the technological and compositionalquality of ewe’s raw milks from commercial flocks underpart-time grazing

Ana I Najera1, Luis JR Barron1*, Patricia Ribeiro2, Fanny Pelissier3, Eunate Abilleira1,Francisco J Perez-Elortondo3, Marta Albisu3, Jesus Salmeron3, Juan C Ruiz de Gordoa2,Mailo Virto2, Luis Oregi4, Roberto Ruiz4 and Mertxe de Renobales2*

1 Tecnologıa de Alimentos; 2 Bioquımica y Biologıa Molecular ; 3Nutricion y Bromatologıa, Facultad de Farmacia. Universidad del Paıs

Vasco/Euskal Herriko Unibertsitatea, Paseo de la Universidad 7, 01006 Vitoria-Gasteiz, Spain4 Instituto Vasco de Investigacion y Desarrollo Agrario, Neiker, Granja Modelo de Arkaute, P.O. Box 46, 01080, Vitoria-Gasteiz, Spain

Received 18 March 2008; accepted for publication 8 November 2008; first published online 12 June 2009

Rennet coagulation parameters, curd texture and gross compositional variables were studiedin ewes’ raw milk samples from nine commercial flocks using different concentrate : forageratios and grazing times. From early lactation to March flocks were fed concentrate pellets andhay whereas from April to the end of lactation flocks were allowed to graze from 6 to 19 h/dayreceiving concentrate supplementation in the morning and evening. Milk from late-lactationflocks, when allowed to graze, showed higher content of fat, dry matter, protein, casein, solubleprotein, total calcium, curd firmness and curd resistance to compression than the milk fromearly lactation flocks. Higher total calcium content and lower fat content were found when theearly lactation flocks were fed high concentrate : forage ratio than when the flocks were fed lowratio. Curd firmness were lower for milk from flocks fed high concentrate : forage ratio, andthe curd resistance to compression was greater, than for milk from flocks fed low ratio. At latelactation, when flocks grazed for a long time per day the total calcium content was higher thanwhen the flocks grazed for a short time per day. Principal component analysis showed thatprotein and fat content were highly correlated with coagulum and curd firmness, whereas totalcalcium content was highly correlated with curd resistance to compression, and milk pH withrennet coagulation time.

Keywords: Seasonal changes, ewe’s milk, milk composition, rennet coagulation, curd texture.

The production of ewe’s milk is a traditional activity ofmost Mediterranean countries. The main use for sheepmilk is for cheesemaking that is usually conducted at farmlevel or in small local dairies in most of these countries.Cheese quality depends closely on the composition andquality of milk, particularly for raw milk cheeses. Milk andcheese characteristics are mainly affected by breed, stageof lactation, health status and dietary factors. Studies onthe effect of animal feeding on milk and cheese qualityhave mainly focused on the relationship between nutrientintake from the main feeding systems and the con-centration of milk components (Coulon et al. 2004).Interesting reports have been recently published both on

the physico-chemical characteristics of sheep milk, and onthe influence of farming and feeding systems on compo-sition and quality of sheep milk and sensory properties ofcheese (Morand-Fehr et al. 2007; Park et al. 2007). It hasbeen reported that increases in the content of protein andfat during lactation, or caused by the animal diet, producechanges in the rennet coagulation properties of milk, par-ticularly increasing curd firmness (Malosini et al. 1996;Guinee et al. 1997). However, changes in rennet coagu-lation properties can be also affected by other upstreamfactors such as animal genetic characteristics, health statusand physiological stage (Macheboeuf et al. 1993; Coulonet al. 2004).

In seasonal calving systems, such in those used forsheep flocks management, the effects of stage of lactationare confounded with those of season, i.e. the effects ofvariation in photoperiod, climate and weather, and in diet

*For correspondence; e-mail : [email protected] (Luis JRBarron). [email protected] (Mertxe de Renobales)

Journal of Dairy Research (2009) 76 301–307. f Proprietors of Journal of Dairy Research 2009 301doi:10.1017/S0022029909004178 Printed in the United Kingdom


58

(Auldist et al. 1998; Walker et al. 2004). Feeding systemsbased on pasture may vary subject to the agro-climateconditions and different botanical species. Accordingly,depending on the available biomass and the nutritive va-lue of the pasture, the use of feed supplements of varioustypes has increased, particularly among local farmers re-sulting in increases in flock size ( Jaeggi et al. 2005;Steinshamm et al. 2006). However, it has been reportedthat milk production in a semi-extensive feeding regime ofpart-time grazing and concentrate is comparable that in anintensive indoor regime (Min et al. 2005), and that sup-plementary feeding was useful for increasing the pro-duction and quality of milk from ewes under part-timegrazing (D’Urso et al. 1993; Garcıa-Rodrıguez & Oregui,2004).

The objective of the present work was to report seasonalchanges including stage of lactation and diet on compos-itional quality and technological aptitude of ewe’s raw milkobtained from flocks under part-time grazing. The effectof concentrate : forage ratio was investigated in early lac-tation flocks whereas that of grazing time was studied inlate-lactation flocks.

Materials and methods

Commercial flocks and milk samples

The experiment started in March in the Basque CountryRegion of northern Spain. Nine commercial flocks of latxabreed from farmhouses belonging to the Denominationof Origin of Idiazabal Cheese were selected, all the flockshaving the same seasonal calving system. Flock size ran-ged between 200 and 400 ewes, with lambing periodsextending approximately for 45 days and lactating lasting4 to 5 months, form late winter to early summer. Duringthe first part of the experiment (from the beginning of lac-tation to March), flocks were fed concentrate pellets andhay. Different commercial formulations of concentratepellets were used in each farmhouse. Three farmhousesused a concentrate : forage ratio greater than 3 (Concen-trate Fed-flocks), whereas for the other six farmhousesthe ratio was lower than 1 (Forage Fed-flocks). Duringthe second part of the experiment (from April to the endof lactation) the flocks were allowed to graze, receivingbetween 0.6 to 1 kg concentrate pellets per day and ani-mal. In three farmhouses sheep grazed ad libitum for16–19 h/day (Long Time Grazing-flocks) whereas in theother six farmhouses sheep grazed for 6–8 h/day (ShortTime Grazing-flocks). Flocks were located at an altitudebetween 500 and 900 m. Flocks grazed both in intensivelymanaged and fertilised grasslands dominated by ryegrassand in other community grasslands with a higher diversityof grass species. Samples of bulk milk from each flock(1.5 l) were taken in duplicate in early March when earlylactation flocks were fed no pasture (Before Pasture-flocks)and at the end of May when late-lactation flocks wereallowed to graze (After Pasture-flocks). Total number of

milk samples was 36. Automatic milking machines wereused in all farmhouses. Weather conditions during Maywere rather similar for all pasture locations, with averageday temperature of 14.4 8C, relative humidity of 74.8%and precipitation of 2.9 l/m2 per day.

Milk composition analysis

The amount (g/100 ml) of nitrogen fractions such as totalnitrogen, total soluble nitrogen and non-protein nitrogenwere directly determined by Kjeldahl procedure as de-scribed by Rowland (1938). Various protein fractions wereconverted into the corresponding amounts of protein(g/100 ml) by multiplying by 6.38. The amount (g/100 ml)of total fat was measured by the Gerber method accordingto IDF international standard 105 (1981). The amount ofdry matter (g/100 g) was determined as described in IDFinternational standard 021B (1987). The pH of the milksamples was measured at 20 8C. The total calcium content(mg/l) was determined as described by De la Fuente et al.(1997) in an atomic absorption spectrometer (AAnalysit200, Shelton, CN, USA) with a cathode lamp after wetmineralization of the milk samples assisted by microwaveacid digestion in a laboratory microwave oven (MSP 1000,CEM, Matthews, NC, USA). Microwave digestion of milksamples was done in two steps. First step consisted ofclosed-vessel heating with full power under controlledpressure from 20 to 170 psig for 52 min, and the secondstep used full power under controlled pressure from20 to 150 psig for 36 min. All analyses were made induplicate.

Microbiological routine control of milks was done inthe Dairy Institute of Lekunberri (Lekunberri, Spain). Totalmicrobiological counts were lower than 50r103 cfu /ml,which indicated the high quality of the milks.

Rennet coagulation and curd texture

Commercial rennet powder (NaturenTM Plus 1400 NB, CHRHansen, Madrid, Spain) consisted of 80% (w/w) bovinechymosin and 20% (w/w) pepsin; the minimum rennetstrength was 1300 IMCU/g of coagulant. Milk sampleswere coagulated at 32 8C using 3 mg rennet per 100 ml.The coagulation process was measured as described pre-viously (Najera et al. 2003) in a model NT Gelograph (GelInstrumente AG, Thalwil, Switzerland) based on the near-infrared light absorption and scattering in the coagulatingmilk. Rennet coagulation time (min) was the time fromrennet addition to the first appearance of an increasein viscosity of the coagulated milk. Coagulum and curdfirmness were measured as the percentage of relativetransmission (% RET) of the coagulated milk at the rennetcoagulation time and at the cutting time (twice the rennetcoagulation time), respectively. A higher % RET valueequates to lower curd firmness. Gel firming rate was ob-tained by dividing the difference in firmness at cutting andrennet coagulation times by the time difference between

302 AI Najera and others


59

these two points (% RET/min). Rennet coagulation par-ameters were determined in duplicate.

Curd texture was analysed by a compression test usinga model TA.XT2i Texture Analyser (Stable Micro Systems,Surrey, UK) equipped with a local cell of 5 kg and P/25probe. Milk samples were coagulated as described above,and once the coagulation process reached the cuttingtime the curd resistance to compression (g) was measured.Curd samples were compressed at room temperature to50% of their original height using a cylindrical sampleprobe (contact area of 490.87 mm2) and a surface sensitiveforce of 0.005 kg/m s2. The force vs. time plots were re-corded using the Texture ExpertTM software with crossheadmoved at a constant speed of 12 mm/min. Four measure-ments were performed for each milk sample.

Statistical analysis

SPSS statistical package, version 16.0 (SPSS Inc., Michigan,USA), was used for the statistical analysis. Analysis ofvariance (ANOVA) was used to determine the presence ofsignificant (Pf0.05) differences in the analytical variablesbetween milks from Before Pasture-flocks and AfterPasture-flocks. Milk pH was used as covariate when co-agulation parameters were studied. Mixed linear modelwas used including ‘season’ as fixed effect nested within‘flock’ as random effect when the interaction term ‘sea-son*flock’ was not significant. F-test of the ‘season’against the interaction term ‘season*flock’ was used whenthis interaction was significant (Pf0.05). F-statistic wasalso used to determine the presence of significant differ-ences (Pf0.05) in the analytical variables either betweenmilks from Concentrate Fed-flocks and Forage Fed-flocksor between milks from Long Time Grazing-flocks andShort Time Grazing-flocks. Principal component analysis(PCA) was performed on a matrix of the compositionalvariables, coagulation parameters and curd texture ofthe milk samples using the Kaiser criterion (eigenvalue >1)to select the principal components. Factors were rotated(Varimax method) for ease of interpretation.

Results and discussion

Table 1 shows the content of gross compositional variablesof milk samples from Before Pasture-flocks (early lactationflocks) and from After Pasture-flocks (late-lactation flocks).Significant differences (Pf0.05) were found for most of thegross compositional variables. As expected, as lactationperiod progressed the content of total nitrogen, total sol-uble nitrogen, protein, casein, total fat and dry matter washigher in milk from After Pasture-flocks than in milk fromBefore Pasture-flocks. The content of total nitrogen, pro-tein and casein increased around 9% when flocks grazedon pastures, whereas the content of total soluble proteinincluding whey proteins and other minor proteins in-creased above 13%. It has been reported that seasonalT

able

1.Mea

nva

lues

andstan

darddev

iationsofgross

compositional

variab

les,

rennet

coag

ulationparam

eters,

andcu

rdtexture

ofew

e’sraw

milks

from

flock

sac

cordingto

season(dietan

dstag

eoflactation),co

nce

ntrate:forage

ratioan

dgraz

ingtimeeffects

Season

Concentrate:forage

ratio

Grazingtime

Earlylactationflocks

Late-lactationflocks

Earlylactationflocks

Late-lactationflocks

Before

Pasture-flocks

After

Pasture-flocks

ConcentrateFed-flocks

Forage

Fed-flocks

LongTim

eGrazing-flocks

ShortTim

eGrazing-flocks

Totalnitrogen(g/100ml)

0. 77±0. 05a

0. 84±0. 04b

0. 76±0. 06a

0. 78±0. 05a

0. 86±0. 05a

0. 83±0. 04a

Totalsoluble

nitrogen(g/100ml)

0. 15±0. 01a

0. 17±0. 02b

0. 15±0. 01a

0. 15±0. 01a

0. 17±0. 02a

0. 17±0. 02a

Non-protein

nitrogen(g/100ml)

0. 04±0. 00a

0. 04±0. 00a

0. 04±0. 00a

0. 04±0. 00a

0. 04±0. 00a

0. 04±0. 00a

Protein

(g/100ml)

4. 69±0. 35a

5. 14±0. 27b

4. 57±0. 40a

4. 75±0. 33a

5. 27±0. 30a

5. 08±0. 23a

Casein(g/100ml)

3. 95±0. 35a

4. 27±0. 26b

3. 85±0. 42a

4. 00±0. 31a

4. 42±0. 27a

4. 20±0. 24a

Totalfat(g/100ml)

6. 10±0. 54a

7. 07±0. 55b

5. 75±0. 43a

6. 28±0. 51b

7. 10±0. 59a

7. 05±0. 56a

Dry

matter(g/100g)

16. 29±0. 63a

17. 75±0. 76b

15. 90±0. 67a

16. 48±0. 54a

18. 01±0. 86a

17. 62±0. 71a

Totalcalcium

(mg/l)

1514. 76±241. 76a

1664. 72±189. 70b

1719. 00±197. 66a

1412. 65±196. 07b

1796. 92±117. 00a

1598. 63±187. 34b

pH

6. 68±0. 09a

6. 69±0. 07a

6. 68±0. 09a

6. 68±0. 09a

6. 72±0. 04a

6. 68±0. 08a

Ren

net

coagulationtime(m

in)

13. 53±1. 92a

12. 85±1. 97a

14. 57±1. 07a

13. 01±2. 07a

12. 88±1. 64a

12. 84±2. 19a

Coagulum

firm

ness(%

RET

)6. 14±0. 38a

5. 09±0. 41b

6. 41±0. 37a

6. 00±0. 31b

5. 07±0. 56a

5. 10±0. 33a

Curd

firm

ness(%

RET

)4. 26±0. 28a

3. 59±0. 29b

4. 44±0. 26a

4. 17±0. 25b

3. 53±0. 33a

3. 63±0. 28a

Gel

firm

ingrate

(%RET

/min)

0. 15±0. 01a

0. 13±0. 00b

0. 14±0. 03a

0. 15±0. 02a

0. 12±0. 02a

0. 12±0. 02a

Curd

resistan

ceto

compression(g)

86. 54±9. 30a

97. 11±9. 43b

95. 54±3. 46a

82. 05±7. 86b

100. 27±11. 65a

95. 53±8. 22a

a,b

Meansfollowed

byadifferentletter

weresign

ifican

tly(Pf

0. 05)differentbetweenflocksunder

each

effect

Seasonal changes on ewe’s raw milk composition 303


60

changes, mainly stage of lactation, diet and flock man-agement, affect the composition of sheep milk (Perea et al.2000; Barron et al. 2001; Pulina et al. 2006). The com-positional parameter that increased most when the late-lactation flocks grazed on pastures was total fat (around16%). It is well-known that as lactation progresses thecontent of fat and protein increase in sheep milk (Coulonet al. 1998). Some authors have reported higher casein andsoluble protein content in milk from cows fed on pastureoutdoors (Berry et al. 2001). Other authors have reportedthat fat and protein content in sheep milk decreased as thelactation period progressed because of hot weather andpoorer quality pastures ( Jaeggi et al. 2005). The content ofnon-protein nitrogen, which includes mainly urea, creatinand free amino acids (Park et al. 2007), and pH did notsignificantly (P>0.05) vary between Before Pasture-flocksand After Pasture-flocks (Table 1). Other authors foundsignificant increments ranging from 0.02 to 0.04 units inmilk pH when cows were fed on pasture (Macheboeufet al. 1993).

The content of total calcium was significantly (Pf0.05)higher in After Pasture-flocks than in Before Pasture-flocksshowing an increment over 9% when late-lactation flocksgrazed (Table 1). Khan et al. (2006) reported an increasefrom 551 to 990 mg/ml in total calcium content whencomparing milk from late-lactation ewes feeding indoorsand grazing for 2–5 h. Contradictory results have been re-ported for changes in total calcium content in sheep milkduring the lactation period (Pellegrini et al. 1994; Coulonet al. 1998). The differences observed in the seasonalfluctuations in total calcium content of ewe’s milk can beattributed to breed, diet, individual animal stage or statusof udder health (Park et al. 2007).

Significant differences (Pf0.05) in most of the coagu-lation parameters were found between milks from BeforePasture-flocks and After Pasture-flocks (Table 1). Coagu-lum firmness (% RET) decreased around 17% when late-lactation flocks grazed and curd firmness (% RET)decreased over 15%. These values (% RET) indicated thatthe curd made with milk from After Pasture-flockspresented higher firmness than that made with milk fromBefore Pasture-flocks. Also, the curd resistance tocompression increased over 12% in the milk from AfterPasture-flocks. Rennet coagulation time did not signifi-cantly (P>0.05) change when the flock feeding regimechanged and the lactation period progressed, but the gelfirming rate (% RET min–1) decreased around 13% in milksamples taken when late-lactation sheep had been grazingfor at least one month (After Pasture-flocks; Table 1). Sev-eral authors have reported that increments in the contentof protein and fat as lactation progressed, or caused bydiet, produce higher curd firmness and lower rennet co-agulation time (Guinee et al. 1997; Auldist et al. 2002). Inour work, the observed increase (around 5%) in rennetcoagulation time in milk from After Pasture-flocks was notstatistically significant (P>0.05). Some authors reportedhigher curd firmness and lower rennet coagulation time in

milks from cows with a part-time grazing regime than inmilks from cows fed concentrate and forage, regardlessthe stage of lactation (Berry et al. 2001). However, thesechanges did not appear to result entirely from the parallelincrease in milk protein content (Macheboeuf et al. 1993).Other authors have reported no significant differences incomposition and rennet coagulation properties betweenmilk samples from grazing dairy cows and milk samplesfrom cows with different feeding regimes (Bovolenta et al.2002). These divergent results imply that in addition to dietand stage of lactation, there must be other as yet un-identified factors that affect rennet coagulation time andcurd firmness. No study on changes in rennet coagulationproperties of ewe’s milk due to changes in diet, particu-larly pasture feeding, has been found in the literature.

In early lactation flocks, significant differences (Pf0.05) between milks from Concentrate Fed-flocks andfrom Forage Fed-flocks were only found for two of thecompositional variables studied: total fat and total calcium(Table 1). Total fat increased over 9% whereas total cal-cium decreased nearly 18% when flocks were fed lowconcentrate : forage ratio (Forage Fed-flocks). It has beenreported that changes in the diet of animals fed indoor dueto different nutrient intake or nature of forage influenceewe’s milk composition (Chilliard & Ferlay, 2004; Pulinaet al. 2006; Sanz Sampelayo et al. 2007). Several authorshave reported increases in the fat content of ewes’ milkwhen supply of concentrates in diet increases (Morand-Fehr et al. 2007). Other authors did not find significantdifferences (P>0.05) in the composition of milk from cowsconsuming different concentrate : forage ratios (Malossiniet al. 1996). Coagulum and curd firmness were the rennetcoagulation parameters that significantly varied betweenConcentrate Fed-flocks and Forage Fed-flocks (Table 1).Coagulum and curd firmness (% RET) decreased over6% when flocks were given feed with a low con-centrate : forage ratio. As described in Materials andMethods, the higher value of % RET, the lower firmness,and in consequence, the curds made with milks fromForage Fed-flocks were firmer than those made with milkfrom Concentrate Fed-flocks. However, the curd resistanceto compression significantly (Pf0.05) decreased by over14% in the milks from Forage Fed-flocks (Table 1). Asseveral authors have pointed out, and as it will be pointedout in the next section, increments in fat content and cal-cium content of the milk can produce increments in curdfirmness and in gel aggregation rate, respectively (Guineeet al. 1997).

In late-lactation flocks, significant differences (Pf0.05)were found only for total calcium content which was over11% higher in Long Time Grazing-flocks than in ShortTime Grazing-flocks (Table 1). It has been reported that alonger daily grazing time does not induce systematicallyan increase in level of intake, and in consequence in-crements in nutrient content of the milk (Morand-Fehr et al.2007). Therefore, in addition to the longer grazing time,other factors such as individual animal stage or status of



61

udder health could increase the calcium content in themilk from Long Time Grazing-flocks (Celik & Ozdemir,2003; Park et al. 2007). None of the rennet coagulationparameters showed significant differences (P>0.05) be-tween Long Time Grazing-flocks and Short Time Grazing-flocks (Table 1).

Principal component analysis

Principal component analysis (PCA) was applied to grosscompositional variables, rennet coagulation parametersand curd texture. Four PCs accounting for 82.6% of thetotal variance described the variation in the compositionalquality and technological aptitude of milks from flocksmanaged under part-time grazing (Table 2).

Compositional variables such as total nitrogen, protein,casein, total fat and dry matter content showed high posi-tive loadings (>0.860) with PC1 whereas rennet coagu-lation parameters such as coagulum and curd firmnessshowed high negative loadings with this factor. Gel firm-ing rate also showed negative loading (–0.586) with PC1.As above mentioned, the higher value (% RET) for coagu-lum or curd firmness, the lower firmness, and in conse-quence, both rennet coagulation parameters togetherwith gel firming rate showed negative correlation withgross compositional variables in PC1 (Table 2). Significant(Pf0.05) positive correlations have been found betweenthe content of fat, protein, casein or total solids of cow’smilk and curd firmness and curd firming rate (Auldist et al.2004). Several authors have reported that the content andtype of caseins affect the curd firmness (Auldist et al.

Table 2. Rotated factor loadings for principal components (PC)1, 2, 3 and 4 as applied to compositional variables, rennetcoagulation parameters and curd texture of ewe’s raw milksfrom Before Pasture-flocks (early lactation flocks) and AfterPasture-flocks (late-lactation flocks). Factor loadings lower than|0.350| are set to 0

Variable PC1a PC2b PC3c PC4d

Protein 0.939Curd firmness –0.937Coagulum firmness –0.934Total nitrogen 0.932Dry matter 0.921Total fat 0.869Casein 0.861Gel firming rate –0.586 –0.470 –0.499pH 0.817Rennet coagulation time 0.812Non-protein nitrogen 0.810Total soluble nitrogen 0.502 0.357 0.681Total calcium 0.858Curd resistance tocompression

0.778

a 47.3% variance; b 13.0% variance; c 11.5% variance; d 10.8% vari-

ance

2,01,00,0-1,0-2,0

PC1 (47.3%)

2,01,00,0-1,0-2,0

PC1 (47.3%)

2,01,00,0-1,0-2,0

PC2 (12.9%)

2,0

1,0

0,0

-1,0

-2,0

2,0

1,0

0,0

-1,0

-2,0

2,0

1,0

0,0

-1,0

-2,0

PC

2 (1

2.9%

)

APBP

PC

4 (1

1.5%

)

LRHR

PC

4 (1

0.8%

)

LTST

a

b

c

Fig. 1. Plots depicting milk sample distributions (factor scoremean values) in the two-dimensional coordinate systems definedby (1a) PC1 and PC2, (1b) PC1 and PC4, and (1c) PC2 and PC4.AP: After Pasture-flocks; BP: Before Pasture-flocks; HR: Con-centrate Fed-flocks; LR: Forage Fed-flocks ; LT: Long TimeGrazing-flocks; ST: Short Time Grazing-flocks.



62

2002; Lucey et al. 2003) and that increasing the levels ofmilk fat the renneting properties are enhanced (Guineeet al. 1997). Accordingly, this factor was defined as ‘gelfirming factor’.

Rennet coagulation time and pH showed high positiveloadings (>0.810) with PC2 (Table 2). Martin & Coulon(1995) found a strong correlation between bovine milkclotting time and the pH of the milk, regardless feed-ing practices during lactation; the influence of pH onrennet coagulation time is very strong because it affectschymosin activity for the hydrolysis of k-casein (Hyslop,2003). Accordingly, PC2 was defined as ‘enzymic activityfactor’.

Total calcium content and curd resistance to com-pression were highly correlated (>0.775) with PC4(Table 2). It has been reported that calcium bridges areinvolved in the aggregation of casein micelles during thenon-enzymatic phase of milk coagulation (Lucey, 2002).Accordingly, this factor was defined as ‘gel aggregationfactor’. Non-protein nitrogen and total soluble nitrogencontent were positively correlated with PC3 which pointedout that these nitrogen fractions did not significantly affectthe rennet coagulation process or curd textural properties.In rennet-induced gels, most of the serum which containsnon-protein compounds and soluble proteins is lost aswhey after the curd is cut (Lucey et al. 2003).

Figure 1 depicts milk sample distributions in two-dimensional coordinate systems defined by PC1, PC2 andPC4. Most milk samples from After Pasture-flocks (late-lactation flocks) or Before Pasture-flocks (early lactationflocks) could be distinguished by the ‘gel firming factor’(PC1) in the coordinate system defined together with PC2.Therefore, the part-time grazing together with the stage oflactation of the flocks influenced the curd firming whichstrongly depends on milk composition. Most milk samples(early lactation flocks) from Concentrate Fed-flocks andForage Fed-flocks could be distinguished by the ‘gel ag-gregation factor’ (PC4) in the coordinate system definedtogether with PC1. When flocks were managed indoorsthe content of total calcium in milk increased with theconcentrate : forage ratio, and, as a result, curd resistanceto compression also increased. Most milk samples (late-lactation flocks) from Long Time Grazing-flocks and ShortTime Grazing-flocks could be distinguished by the ‘gelaggregation factor’ (PC4) in the coordinate system definedtogether with PC2. Then, when flocks were allowed tograze, the grazing time increased the total calcium contentof the milk, but no increase in curd resistance to com-pression was observed.

In summary, in milks from early lactation flocks,the higher concentrate : forage ratio, the higher calciumcontent and the lower fat percentage. In milks from late-lactation flocks, the longer grazing time, the higher cal-cium content. When early lactation flocks fed indoorswere compared with late-lactation flocks under part-timegrazing, higher content of protein, fat and calcium werefound. These changes were responsible for variations in

rennet coagulation properties and curd texture, which willaffect ultimately rheological and sensory properties ofcheese.

Acknowledgments

The authors thank the local farmers for supplying milk samplesand technical information on their farming and feeding systems,the Regulatory Board of Denomination of Origin of Idiazabaland Artzai-Gazta association for technical support. This workwas supported by grants from the Universidad del Paıs Vasco/Euskal Herriko Unibertsitatea (Leioa, Spain) together with theDepartamento de Medio Ambiente y Ordenacion del Territoriodel Gobierno Vasco (UNESCO Cathedra/2005), and the InstitutoNacional de Investigacion y Tecnologıa Agraria y Alimentaria(Madrid, Spain) (RTA2006-00100-C02-02).

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47

Manuscrito 2. Effects of seasonal changes in the feeding management

under part-time grazing on the evolution of the composition and

coagulation properties of ewes’ raw milk

Enviado a Journal of Dairy Science el 9 de diciembre de 2009

Ref.: JDS-09-2983


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Interpretative summary: Ewes’ raw milk technological quality 1

Abilleira 2

Composition and technological properties of ewes’ raw milk produced for 3

cheesemaking were studied in commercial flocks throughout the milking season. During 4

that period the feeding of the flocks changed from an indoor diet, which consisted of 5

concentrate and forages, to an outdoor diet based mainly on grazing. More consistent 6

curds were obtained at the end of the milking season under outdoor grazing system and 7

this greater consistency was related to the higher nutrient content of the milk. This study 8

is a good example of how milk of high technological quality can be obtained 9

maximizing the use of natural resources. 10

11

EWES’ MILK COMPOSITION AND COAGULATION PROPERTIES 12

13

Effects of Seasonal Changes in the Feeding Management under Part-time Grazing 14

on the Evolution of the Composition and Coagulation Properties of Ewes’ Raw 15

Milk 16

17

E. Abilleira,* M. Virto,† A. I. Nájera,* J. Salmerón,‡ M. Albisu,‡ F. J. Pérez-18

Elortondo,‡ J. C. Ruiz de Gordoa,† M. de Renobales,† and L. J. R. Barron*,1 19

*Tecnología de Alimentos, †Bioquímica y Biología Molecular, and ‡Nutrición y 20

Bromatología, Facultad de Farmacia, Universidad del País Vasco/Euskal Herriko 21

Unibertsitatea, Paseo de la Universidad 7, 01006 Vitoria-Gasteiz, Spain 22

23

1Corresponding author: Luis Javier Rodriguez Barron; tel.: +34 945 01 30 82; fax: +34 24

945 01 30 14; e-mail address: [email protected] 25

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ABSTRACT 26

27

Ewes’ raw milk composition, rennet coagulation parameters and curd texture were 28

monitored throughout the milk production season in eleven commercial flocks reared 29

under part-time grazing system. Milking season lasted from February to July. During 30

that period, the diet of the animals shifted from indoor feeding, consisting of 31

concentrate and forage, to an outdoor grazing diet. Dry matter, fat, protein, calcium, and 32

magnesium contents increased throughout the milking season, as well as rennet 33

coagulation time, curd firmness, and curd resistance to compression. However, dry 34

matter, protein content, and curd resistance to compression stabilized when sheep 35

started to graze. Principal component analysis correlated curd resistance to compression 36

and proteins, whereas curd firmness was highly correlated with fat content and minerals. 37

Discriminant analysis distributed milk samples according to the feeding management, 38

and curd firmness, fat, and magnesium turned out to be discriminant variables. These 39

variables reflected the evolution of the composition and coagulation parameters when 40

fresh pasture prevailed over other feeds in the diet of the flocks. The present study 41

shows that seasonal changes associated with feeding management influence milk 42

technological quality and that milk of good processing quality can be obtained under 43

part-time grazing. 44

45

Key words: feeding, coagulation properties, milk composition, ewes’ raw milk 46

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INTRODUCTION 47

The main use for ewes’ milk throughout the world is for cheesemaking. Hence, the 48

capability of sheep’s milk to be transformed in high-quality cheese is a major concern 49

among cheese makers, in particular when they use raw milk (Bencini, 2002). 50

Coagulation properties have been widely used by researchers to asses the processing 51

performance of milk because it is easier than making cheese batches and measuring 52

cheese yield (Bencini, 2002). Renneting parameters of milk are affected by 53

physicochemical properties, such as pH, casein micelle structure, and mineral content 54

(Nájera et al. 2003; Park et al., 2007). The physicochemical characteristics of milk are 55

related to its composition which varies with diet, feeding, season, management, breed, 56

reproduction and sanitary characteristics, and also environmental conditions (Park et al., 57

2007; Morand-Fehr et al., 2007). 58

Because milk production represents the major cost of cheese production, it is 59

important for manufacturers to obtain milk of high technological and sanitary quality at 60

the lowest price. This is even more important for ovine milk because it is much more 61

expensive than cow’s milk (Jaeggi et al., 2005). The use of pastures to feed the sheep 62

can help in reducing milk production costs, without compromising milk production 63

(García-Rodríguez and Oregui, 2004). Taking advantage of natural resources is cheaper 64

than purchasing concentrate formulations in the market. Hence, pasture grazing 65

contributes to the sustainability of the whole system, but it is critical to know how it 66

affects milk processing quality. In most countries sheep’s milk production is seasonal 67

and flock diet changes throughout lactation to meet nutritional requirements of the 68

animals. Due to climatologic conditions it is not always possible to take advantage of 69

natural resources, and grazing period is usually limited to spring and early summer 70

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months. Hence, the effects of stage of lactation are confounded with those of season and 71

diet, and can not be dealt with separately in commercial flocks (Walker et al., 2004). 72

Seasonal differences on the composition of bulk raw milk from several latxa flocks 73

at different lactation stages have been reviewed (Barron et al., 2001) and technological 74

quality of ewes’ milk from early and late lactation flocks under part-time grazing has 75

been compared (Nájera et al., 2009). Seasonal changes, associated with feeding pattern 76

changes, in ewes’ milk composition, milk quality, and cheese yield have been also 77

reported (Jaeggi et al., 2005; Morand-Fehr et al., 2007; Park et al., 2007). However, in 78

most of these studies, samples were obtained at 2 or 3 stages of the milking season and 79

more exhaustive information about the evolution of milk processing performance of 80

individual flocks is still lacking. 81

The aim of this study was to monitor the evolution of the composition and renneting 82

properties of ewes’ raw milk throughout the milking season as affected by seasonal 83

changes in feeding under part-time grazing of commercial flocks. 84

85

MATERIALS AND METHODS 86

87

Commercial Flocks and Milk Samples 88

Eleven commercial flocks of latxa ewes were selected. All the flocks belonged to 89

the Protected Denomination of Origin Idiazabal Cheese and were reared in the Basque 90

Country in northern Spain. Flock management was similar in the eleven farms. Flocks 91

lambed in winter and suckling lambs were weaned at 30-45 days. Ewes were milked 92

twice a day using automated milking machines. Sample collection started in February 93

and ended in July. Each month 1.5 L of bulk raw milk was taken from each farmhouse 94

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and stored at 4 ºC until analysis within the next 48 h. Flock productive characteristics 95

during the milking season are summarized in Table 1. 96

97

Feeding management 98

Sheepherders were interviewed each sampling day to gather information about the 99

fodder composition and diet of the flocks. Feeding management consisted of an indoor 100

period in winter and part-time grazing system in spring and summer. In February diets 101

were based on concentrate and conserved forages and sheep stayed indoors all day. In 102

March, the grazing season began because good quality pasture was available. However, 103

a large variability in the pasture allowances and levels of supplementation was observed 104

because the transition from indoor feeding to part-time grazing was slightly different 105

from one farm to another. From April, fresh grass prevailed over other feeds in the diet 106

of all the flocks and indoor supplementation decreased progressively as lactation 107

progressed. Table 1 shows average diet composition of the flocks during the milking 108

season. Fresh pasture intake was estimated from the time spent on pasture and the 109

amount of other feeds ingested (Perojo et al., 2005). 110

111

Milk Analysis 112

Routine control analyses of milk of each flock were carried out in the Dairy Institute 113

of Lekunberri (Lekunberri, Spain) every two weeks. Total milk fat (g/100mL) was 114

determined following the IDF International Standard 105 (1981) and dry matter 115

(g/100g) was determined according to IDF International Standard 021B (1987). Somatic 116

cell (somatic cell/mL) and microbiological counts (cfu/mL) were measured following 117

the IDF International Standars 148A (1995) and 100B (1991), respectively. 118

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Mineral content (mg/L), total calcium and total magnesium, were measured by 119

atomic absorption as described by De la Fuente et al. (1997) and modified by Nájera et 120

al. (2009), using an AAnalyst 200 atomic absorption spectrometer (Shelton, CN, USA). 121

Total nitrogen, non-casein nitrogen (g/100mL) and non-protein nitrogen (g/L) were 122

determined following the procedure described by Rowland (1938). Other nitrogen 123

fractions such as casein nitrogen and true protein nitrogen were obtained by difference. 124

Casein and true protein nitrogen fractions were converted into the corresponding protein 125

amount (g/100mL) by multiplying by 6.38. 126

Rennet coagulation parameters were measured using a NT Gelograph (Gel 127

Instrumente AG, Thalwil, Switzerland) as described by Nájera et al. (2003). Milk was 128

coagulated at 32 ºC adding 3 mg/100mL of commercial rennet powder (Naturen™ Plus 129

1400 NB, CHR Hansen, Madrid, Spain) which consisted of bovine chymosin (80 % 130

w/w) and pepsin (20 % w/w) with minimum coagulating strength of 1300 IMCU/g. 131

Rennet coagulation time (min) was the time from the rennet addition to the appearance 132

of the first coagulum. Coagulum and curd firmness were expressed as the inverse of the 133

relative transmission (% RET-1) at the rennet coagulation time and at the cutting time 134

(twice rennet coagulation time), respectively. Milk pH was measured at 20 ºC before 135

each coagulation assay. 136

Textural measurement of the curds were made using a Texture Analyser TA-XT2i 137

(Stable Micro Systems, Surrey, UK) equipped with a load cell of 5 kg and a P/25 probe 138

as previously described by Nájera et al. (2009). Average force (g) during compression 139

was taken as curd resistance to compression. 140

All the analyses were carried out in duplicate. 141

142

Statistical Analysis 143

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Analysis of variance (ANOVA) was used to determine the presence of significant 144

differences (P ≤ 0.05) in the analytical variables throughout the production season. A 145

mixed model of repeated measures ANOVA was performed. “Flock” was used as fixed 146

factor whereas the “season” was the repeated measures factor. Principal component 147

analysis (PCA) was performed on analytical variables. Only variables with 148

communality values higher than 0.4 were included. The Kaiser criterion (eigenvalue > 149

1) was used to select the principal components. Factors were rotated (Varimax method) 150

for ease of interpretation. A stepwise discriminant analysis was carried out to classify 151

the samples using the same analytical variables. SPSS statistical package, version 17.0 152

(SPSS Inc., Michigan, USA), was used for the statistical analyses. 153

154

RESULTS AND DISCUSSION 155

156

Milk composition 157

As expected, the effect of “season” was significant (P ≤ 0.05) for all compositional 158

variables studied. “Flock” was also significant (P ≤ 0.05) except for the content of fat, 159

magnesium, and milk pH. The interaction term “season*flock” was significant (P ≤ 160

0.05) for all the variables except for milk pH. 161

Total fat content of the milk increased gradually (P ≤ 0.05) from the beginning to 162

the end of the milk production season (Table 2). As reported previously (Barron et al., 163

2001; Nájera et al., 2009), total fat content was higher in late lactation than in early 164

lactation milk. The greatest increase in the fat content occurred from April to May 165

(+13.44 %) after a month of outdoor grazing. Milk dry matter was significantly higher 166

(P ≤ 0.05) at the end of the season but the increase happened from March to May (+1.86 167

%) and then it stabilized (Table 2). The higher solids content of late lactation milk is, in 168

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part, due to the concentration effect caused by the milk yield depression (Sevi et al., 169

2000), which was quite pronounced from March to April (Table 1). In addition to the 170

effect of lactation stage, the shift to a part-time grazing diet might have contributed to 171

the greatest increase of fat and dry matter contents in the spring months. An experiment 172

conducted in goats demonstrated that milk from animals fed pasture plus concentrate 173

had higher contents of fat, protein and total solids than goats under a confined feeding 174

system without pasture grazing (Soryal et al., 2004). 175

The content of nitrogen in all milk fractions was higher (P ≤ 0.05) at the end of the 176

milking period, except for non-protein nitrogen which had a maximum peak in May and 177

then dropped to lower (P ≤ 0.05) levels than in winter (Table 2). Total nitrogen 178

concentration increased until May (+10.39 %) and remained constant until the end of 179

the milking season. True protein followed the same pattern with values ranging from 180

4.25 to 6.33 g/100mL. Casein content behaved in a similar way increasing progressively 181

(P ≤ 0.05) up to its maximum in May (+12.24 %). There was a slight decrease (P ≤ 182

0.05) afterwards, but the casein content at the end of the season was notably higher (P ≤ 183

0.05) than at the beginning (+9.95 %). As occurred with total fat, the greatest increase 184

for the true protein and casein fractions was observed from April to May (+5.73 % and 185

+7.32 %, respectively), after a month of pasture grazing. The concentrations of each 186

nitrogen fraction reported here are in good concordance with those given by Nájera et 187

al. (2009). 188

As for fat content, the concentration effect caused by the milk yield depression can 189

be observed for the protein content (Sevi et al., 2000), at least in the first four months of 190

the study. Regarding protein composition, little information is available on the effects of 191

nutrition on ruminant milk protein profile. The composition of the protein is almost 192

unaffected by the lactation stage in cows, and the nutrition and management of the 193

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animals has very low impact on the proportion of the different nitrogen fractions in 194

ruminants (Walker et al., 2004; Pulina et al., 2006). However, it has been reported that 195

cows grazing pasture had higher casein to whey nitrogen ratio than confined animals fed 196

exclusively indoors (Walker et al., 2004). Lieber et al. (2006) reported that casein 197

number (casein to true protein ratio) rose when cows started to graze compared to cows 198

kept in stall. They also observed an increase of the casein number with progressing 199

lactation for grazing and non-grazing herds. In the present study, both ratios (casein to 200

whey nitrogen, and casein to true protein) oscillated throughout the milking season 201

reaching the highest values (P ≤ 0.05) in May (Table 2). 202

Besides, a close correlation between dietary crude protein and milk urea has been 203

reported (Pulina et al., 2006). As the crude protein of the diet increases, nitrogen 204

conversion efficiency is worse and the excess is lost as non-protein nitrogen (Cannas et 205

al., 1998). Immature pastures are characterized by high crude protein content and a clear 206

influence of increasing grass maturity towards lower milk urea levels has been found 207

(Lieber et al., 2006). This could explain the higher non-protein nitrogen concentrations 208

in April and May and the decreasing trend in later months, because urea is the major 209

component of this nitrogen fraction (Park et al., 2007) (Table 2). 210

Total calcium content tended to increase throughout the milking season but without 211

large variations. The lowest (P ≤ 0.05) concentration was found in February and the 212

highest (P ≤ 0.05) in May and June, whereas the rest of the months it remained at an 213

intermediate level (Table 2). Calcium contents reported here were slightly higher than 214

those from a previous work (Nájera et al., 2009) but around the expected value for 215

ewes’ milk (Park et al., 2007). Few authors reported a calcium content rise during 216

grazing periods compared to confined feeding periods (Martin and Coulon, 1995; 217

Nájera et al., 2009). However, the response of the concentration of this mineral to 218

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nutritional manipulation is very limited (Knowles et al., 2006). Magnesium 219

concentration increased (P ≤ 0.05) progressively throughout the milk production period 220

(+31.15 %) (Table 2). References to the effect of lactation stage or pasture feeding on 221

the magnesium levels were not found in the literature. 222

Values of pH fluctuated throughout the season but, although statistical differences 223

were found, the oscillation was negligible, being 0.08 the highest difference among 224

months (Table 2). Macheboeuf et al. (1993) observed a 0.02 increase in milk pH as a 225

result of turning out to pasture but this fact was not confirmed in the present work. 226

227

Coagulation parameters and curd texture 228

Significant differences (P ≤ 0.05) were found for each rennet coagulation parameter 229

and curd texture measurement due to “season” and “flock” factors. The interaction term 230

“season*flock” was also significant (P ≤ 0.05) for each variable. 231

Rennet coagulation time underwent a gradual increase (P ≤ 0.05) from April to July. 232

Milk samples coagulated about 3 min earlier in the first three months of the experience 233

than in July (Table 3). Different authors have reported different coagulation time as 234

lactation stage progressed. Some of them reported shorter coagulation times (Joudu et 235

al., 2008), other researchers found non-significant differences (Nájera et al., 2009) and 236

few authors measured longer coagulation times (Pellegrini et al., 1994). These 237

contradictory results may have arisen from differences in the methodology used and 238

differences in milk pH because it is a factor of paramount importance on the rennet 239

coagulation time (Bencini et al., 2002). 240

Gel firming rate decreased (P ≤ 0.05) from month to month, being its value in July 241

about a half of that in February (Table 3). This meant that curds needed more time to 242

achieve the same firmness increment as milking season progressed. Despite the lower 243

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gel firming rate, curd firmness increased (P ≤ 0.05) gradually with season because the 244

slower rate of coagulation prevailed over the decrease of the gel firming rate as milk 245

production period advanced. Lower gel firming rate and higher curd firmness have been 246

previously reported for late lactation milks compared to early lactation milks (Pellegrini 247

et al., 1994; Nájera et al., 2009). Accordingly, curd resistance to compression increased 248

(P ≤ 0.05) progressively until April, but then it reached a plateau that lasted until the 249

end of the milk production period (Table 3). 250

251

Relationship between milk composition and coagulation properties throughout the 252

season 253

The transition from indoor feeding to pasture-based diets induced marked changes 254

in most compositional and technological parameters of the milk. Indeed, the largest 255

differences were observed between the milks of April and May, after sheep were 256

allowed to graze for one month (Table 1). This was true for fat, protein (mainly caseins 257

that accounted for 84 % of total protein), magnesium, rennet coagulation time, gel 258

firming rate, and curd firmness (Tables 2 y 3). Some links between compositional and 259

technological parameters and feeding type have been discussed above, but for the sake 260

of a better understanding of the relationships between milk composition and milk 261

coagulation parameters throughout the milking season, a principal component analysis 262

(PCA) was carried out. Four PCs were extracted which explained 73.35 % of total 263

variance (Table 4). 264

Casein and protein contents were highly correlated to PC1 (factor loadings higher 265

than 0.83) together with the dry matter content (factor loading of 0.67) and the curd 266

resistance to compression (factor loading of 0.83) (Table 4). The study conducted by 267

Malacarne et al. (2006) also showed that milk with higher casein content provided curds 268

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with higher resistance to compression. This rheological parameter gives a measure of 269

the texture of the curd and logically it is linked to the proteins, especially caseins, 270

because they are responsible for forming the structural network of the curd (Lucey et al., 271

2003). Curd firmness, as a measure of the rearrangement of the internal bonds of the 272

gel, is also correlated to the curd resistance to compression. It showed a positive factor 273

loading (0.57) with PC1. To a lesser extent, rennet coagulation time correlated 274

positively also to the PC1 (factor loading 0.53). In this sense, other authors have 275

reported longer coagulation times in milk samples with high total solids content (Clark 276

and Sherbon, 2000). 277

Curd firmness and the compositional variables fat, magnesium, and calcium 278

contents had positive loadings (≥ 0.71) with PC2, whereas gel firming rate correlated 279

negatively (-0.72) with this component. Protein content correlated also positively to this 280

component but with lower factor loading (0.40). It has been reported that milk with 281

higher fat and protein contents formed firmer curds (Clark and Sherbon, 2000). Storry et 282

al. (1983) found also a positive correlation between curd firmness and milk fat, casein, 283

magnesium and calcium content. 284

As lactation progressed and diet changed to include ever higher levels of fresh 285

pasture and lower amounts of concentrate and forage, the milk composition was richer 286

in dry matter, fat, protein, and mineral contents. PC1 and PC2 reflected this seasonality. 287

During the first part of the study, when the indoor diet was predominant, there was a 288

similar evolution of all the compositional variables. In the last months, when outdoor 289

grazing prevailed, proteins and dry matter stabilized whereas fat and magnesium 290

contents went up. Calcium content had a staggered evolution which differed from the 291

other variables but it was grouped in the PC2 because of its correlation with curd 292

firmness. Thus, PC1 was called “indoor feeding factor” which was mainly correlated to 293

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proteins and curd resistance to compression, and PC2 was named “outdoor grazing 294

factor” which mainly correlated to fat, minerals, and curd firmness. 295

Coagulum firmness and non-protein nitrogen content, which consists mainly of 296

urea, creatin, and free amino acids (Park et al., 2007), showed high factor loadings with 297

PC3 (> |0.64|). The correlation between these two variables was negative (Table 4). This 298

correlation has not been previously reported by other authors, but it does make sense 299

because few authors have reported that urea could alter the gel forming process 300

(Verdier-Metz et al., 2001; Guinot, 1992). PC3 was defined as “coagulum forming 301

factor”. 302

Rennet coagulation time and pH showed positive factor loadings with PC4 (> 0.59) 303

(Table 4). The same correlation was observed by Nájera et al. (2009). Other authors 304

reported that lower pH influenced positively renneting properties by enhancing the 305

activity of chymosin and modifying the conformation and structure of casein micelles 306

(O’Brien et al., 2006). Low pH provokes solubilisation of calcium and it impacts 307

positively in the aggregation rate of K-casein increasing the coagulation velocity 308

(Malacarne et al., 2006). PC4 was defined as “renneting time factor”. 309

A discriminant analysis was applied to observe the distribution of the samples and 310

go further in the study of the influence of the season associated to the feeding changes 311

in the composition and coagulation properties of the ewes’ milk. Milk samples were 312

grouped according to feeding regime. The indoor group comprised the milks that did 313

not have access to pasture (February), the transition group comprised the milks from the 314

beginning of the grazing period when sheep had been grazing up to one month (March 315

and April), and the outdoor group comprised the milk samples from the flocks that were 316

predominantly grazing and had little supplementation of concentrate and forage (May, 317

June and July). Figure 1 shows the distribution of milk samples according to the feeding 318

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type in the coordinate system defined by the two canonical discriminant functions. As 319

can be observed the indoor and outdoor groups were correctly separated, whereas 21.4 320

% of the transition group samples were classified as samples of the indoor group and 321

9.5 % as samples of the outdoor group. The analysis established three variables capable 322

of discriminating between the three feeding regimens: curd firmness, fat and magnesium 323

content. Function 1 explained 99.4 % of total variance and the three discriminant 324

variables contributed similarly to this canonical function. These particular variables 325

were highly correlated to “outdoor grazing factor” (PC2) of the PCA, which meant that 326

the pasture-related variables were the most relevant ones for discriminating ewes’ raw 327

milk samples throughout the season. 328

329

CONCLUSIONS 330

331

A marked influence of the season associated to the feeding management under part-332

time grazing was observed on the composition and technological quality of the ewes’ 333

raw milk. Protein, casein and dry matter content, as well as curd resistance to 334

compression, increased during the first period of the study and stabilized during the 335

outdoor grazing period. Fat and magnesium, together with curd firmness, underwent a 336

progressive increase throughout the whole milking period. These three variables were 337

capable for discriminating between milks from the indoor feeding period (February) and 338

milks from the outdoor grazing period (May-July). They reflected the evolution of the 339

composition and coagulation properties during the last months of the study when 340

pasture grazing was the predominant feed in the diet of the flocks. The good 341

technological quality of the milk when sheep are fed pasture is an incentive to 342

encourage sheepherders to design their feeding managements taking advantage of the 343

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natural resources as much as they can, giving continuity to this sustainable production 344

system. 345

346

ACKNOWLEDGEMENTS 347

This work was supported by grants from the Universidad del País Vasco/Euskal 348

Herriko Unibertsitatea (Leioa, Spain) (UNESCO Cathedra/05102) and the INIA (RTA 349

2006-00100-C02-02). E. Abilleira acknowledges a predoctoral fellowship from the 350

Basque Government. 351

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REFERENCES 352

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De la Fuente, M. A., B. Carazo, and M. Juárez. 1997. Determination of major minerals 358

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de Renobales. 2009. J. Dairy Res. 76:301-307. 388

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Pulina, G., A. Nudda, G. Battacone, and A. Cannas. 2006. Effects of nutrition on the 400

contents of fat, protein, somatic cells, aromatic compounds, and undesirable 401

substances in sheep milk. Anim. Feed Sci. Tech. 131:255-291. 402

Rowland, S. J. 1938. The determination of the nitrogen distribution in milk. J. Dairy 403

Sci. 9:42-46. 404

Sevi, A., L. Taibi, M. Albenzio, A. Muscio, and G. Annicchiarico. 2000. Effect of 405

parity on milk yield, composition, somatic cell count, renneting parameters and 406

bacteria counts of Comisana ewes. Small Rumin. Res. 37:99-107. 407

Soryal, K. A., S. S. Zeng, B. R. Min, S. P. Hart, and F. A. Beyene. 2004. Effect of 408

feeding systems on composition of goat milk and yield of Domiati cheese. Small 409

Rumin. Res. 54:121-129. 410

Storry, J. E., A. S. Grandison, D. Millard, A. J. Owen, and G. D. Ford. 1983. Chemical 411

composition and coagulating properties of renneted milks from different breeds and 412

species of ruminant. J. Dairy Res. 50:215-229. 413

Verdier-Metz, I., J. B. Coulon, and P. Pradel. 2001. Relationship between milk fat and 414

protein contents and cheese yield. Anim. Res. 50:365-371. 415

Walker, G. P., F. R. Dunshea, and P. T. Doyle. 2004. Effects of nutrition and 416

management on the production and composition of milk fat and protein: a review. 417

Aust. J. Agric. Res. 55:1009-1028. 418

419

Page 18 of 25




86

For P

eer R

evie

w

19

Ta

ble

1.

Pro

duct

ion

char

acte

rist

ics,

mil

k hy

gien

ic q

uali

ty a

nd d

iet c

ompo

siti

on (

aver

age

valu

es ±

SD

) fo

r th

e co

mm

erci

al f

lock

s (n

= 1

1) th

roug

hout

42

0

the

mil

k pr

oduc

tion

sea

son

421

Fe

brua

ry

Mar

ch

Apr

il

May

Ju

ne

July

Pro

duct

ion

char

acte

rist

ics

Mil

ked

ewes

21

7 ±

72

252

± 88

28

0 ±

92

287

± 93

23

3 ±

35

264

± 68

Day

s of

lact

atio

n, d

37

±

6 66

±

6 94

±

6 12

2 ±

8 14

8 ±

6 16

9 ±

7

Mil

k yi

eld,

L/m

ilki

ng p

er e

we

0.84

±

0.21

0.

80

± 0.

39

0.54

±

0.22

0.

49

± 0.

14

0.42

±

0.10

0.

32

± 0.

07

Hyg

ieni

c m

ilk

qual

ity

Bac

teri

al c

ount

, 103 c

fu/m

L

80

± 93

52

±

7 50

±

1 51

±

3 76

±

76

50

± 0

SC

C, 1

03 som

atic

cel

l/m

L

263

± 17

5 27

7 ±

136

314

± 17

2 42

8 ±

219

432

± 18

1 46

7 ±

142

Die

t com

posi

tion

Con

cent

rate

, kg/

d 1.

34

± 0.

26

1.40

±

0.45

1.

05

± 0.

36

0.81

±

0.20

0.

56

± 0.

24

0.56

±

0.23

Fora

ge, k

g/d

1.85

±

1.03

0.

72

± 0.

51

0.48

±

0.57

0.

30

± 0.

42

0.22

±

0.32

0.

18

± 0.

35

Gra

zed

past

ure,

kg/

d 0.

28

± 0.

93

3.39

±

1.85

4.

38

± 0.

40

4.67

±

0.57

5.

03

± 0.

70

4.92

±

0.70

42

2

Pag

e 19

of

25

Sch

ola

rOn

e su

pp

ort

: (4

34)

817

2040

ext

. 167

Jou

rnal

of

Dai

ry S

cien

ce


87

For P

eer R

evie

w

20

Tab

le 2

. M

ilk

com

posi

tiona

l var

iabl

es (

aver

age

valu

es ±

SD

) of

the

com

mer

cial

flo

cks

(n =

11)

thro

ugho

ut th

e m

ilk

prod

ucti

on s

easo

n 42

3

Fe

brua

ry

Mar

ch

Apr

il

May

Ju

ne

July

Fat,

g/10

0mL

5.

35

± 0.

71f

5.65

±

0.62

e 6.

10

± 0.

68d

6.92

±

0.68

c 7.

28

± 0.

51b

7.54

±

0.48

a

DM

1 , g/1

00g

10.7

7 ±

0.33

c 10

.77

± 0.

23c

10.9

0 ±

0.17

b 10

.97

± 0.

50a

11.0

4 ±

0.22

a 11

.02

± 0.

25a

TN

2 , g/1

00m

L

0.77

±

0.07

e 0.

78

± 0.

03d

0.81

±

0.03

c 0.

85

± 0.

07b

0.85

±

0.05

ab

0.85

±

0.04

a

NP

N3 , g

/L

0.38

±

0.04

c 0.

38

± 0.

05c

0.41

±

0.06

b 0.

43

± 0.

06a

0.37

±

0.04

d 0.

34

± 0.

07e

NC

N4 , g

/100

mL

0.

15

± 0.

01c

0.16

±

0.02

c 0.

16

± 0.

02b

0.16

±

0.03

b 0.

17

± 0.

02a

0.17

±

0.01

a

Pro

tein

, g/1

00m

L

4.65

±

0.46

d 4.

76

± 0.

18c

4.89

±

0.16

b 5.

17

± 0.

46a

5.19

±

0.35

a 5.

19

± 0.

26a

Cas

ein,

g/1

00m

L

3.92

±

0.45

e 4.

01

± 0.

18d

4.10

±

0.17

c 4.

40

± 0.

39a

4.31

±

0.28

b 4.

31

± 0.

23b

Cas

ein:

whe

y N

4.

01

± 0.

45b

4.11

±

0.58

b 3.

95

± 0.

48b

4.39

±

1.01

a 3.

90

± 0.

34b

3.97

±

0.24

b

Cas

ein

num

ber5

0.84

±

0.01

b 0.

84

± 0.

02ab

0.

84

± 0.

02bc

0.

85

± 0.

03a

0.83

±

0.01

cd

0.83

±

0.01

d

Ca,

mg/

L

1692

.75

± 98

.65c

1816

.21

± 15

2.76

b 18

50.8

3 ±

149.

52b

1913

.37

± 19

6.13

a 19

71.0

8 ±

238.

94a

1871

.90

± 20

2.00

ab

Mg,

mg/

L

163.

69

± 9.

68e

175.

99

± 17

.86d

184.

39

± 9.

82c

202.

04

± 17

.14b

205.

79

± 16

.26b

214.

68

± 21

.11a

pH

6.73

±

0.12

ab

6.75

±

0.06

ab

6.69

±

0.06

cd

6.71

±

0.10

bc

6.76

±

0.07

a 6.

68

± 0.

09d

a,b,

c,d,

e,f M

eans

wit

hin

a ro

w w

ith

diff

eren

t sup

ersc

ript

s di

ffer

(P

≤ 0

.05)

. 42

4

1 DM

: dry

mat

ter.

42

5

Pag

e 20

of

25

Sch

ola

rOn

e su

pp

ort

: (4

34)

817

2040

ext

. 167

Jou

rnal

of

Dai

ry S

cien

ce


88

For P

eer R

evie

w

21

2 TN

: tot

al n

itro

gen.

42

6

3 NP

N: n

on-p

rote

in n

itro

gen.

42

7

4 NC

N: n

on-c

asei

n ni

trog

en.

428

5 Cas

ein

num

ber:

cas

ein

to tr

ue p

rote

in r

atio

. 42

9

Pag

e 21

of

25

Sch

ola

rOn

e su

pp

ort

: (4

34)

817

2040

ext

. 167

Jou

rnal

of

Dai

ry S

cien

ce


89

For P

eer R

evie

w

22

Tab

le 3

. R

enne

t coa

gula

tion

and

cur

d te

xtur

e pa

ram

eter

s (a

vera

ge v

alue

s ±

SD

) of

the

com

mer

cial

flo

cks

(n =

11)

thro

ugho

ut th

e m

ilk

prod

ucti

on s

easo

n 43

0

Fe

brua

ry

Mar

ch

Apr

il

May

Ju

ne

July

RC

T1 , m

in

11.8

0 ±

1.07

e 12

.29

± 1.

68d

11.8

8 ±

1.38

e 13

.30

± 2.

33c

13.6

5 ±

1.68

b 15

.12

± 4.

86a

CoF

2 , %R

ET

-1

0.19

±

0.03

c 0.

18

± 0.

03d

0.18

±

0.03

d 0.

19

± 0.

02bc

0.

19

± 0.

04b

0.21

±

0.03

a

CuF

3 , %R

ET

-1

0.21

±

0.02

f 0.

23

± 0.

01e

0.24

±

0.01

d 0.

27

± 0.

02c

0.28

±

0.02

b 0.

29

± 0.

02a

GFR

4 , %R

ET

/min

0.

15

± 0.

03a

0.13

±

0.02

b 0.

12

± 0.

02c

0.09

±

0.03

d 0.

08

± 0.

01e

0.07

±

0.02

f

CR

C5 , g

98

.86

± 26

.86c

107.

79

± 11

.39b

111.

73

± 8.

35a

115.

45

± 12

.29a

115.

28

± 8.

99a

113.

00

± 15

.11a

a,b,

c,d,

e,f M

eans

wit

hin

a ro

w w

ith

diff

eren

t sup

ersc

ript

s di

ffer

(P

≤ 0

.05)

. 43

1

1 RC

T: r

enne

t coa

gula

tion

tim

e.

432

2 CoF

: coa

gulu

m f

irm

ness

. 43

3

3 CuF

: cur

d fi

rmne

ss.

434

4 GFR

: gel

fir

min

g ra

te.

435

5 CR

C: c

urd

resi

stan

ce to

com

pres

sion

. 43

6

43

7

Pag

e 22

of

25

Sch

ola

rOn

e su

pp

ort

: (4

34)

817

2040

ext

. 167

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rnal

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Dai

ry S

cien

ce


90

For Peer Review

23

Table 4. Rotated factor loadings for the principal component (PC) analysis applied to 438

compositional and technological variables of milks from commercial flocks throughout 439

the milk production season. Factor loadings lower than 0.400 are set to 0 440

PC 11 PC 22 PC 33 PC 44

CRC5 0.834

Casein 0.829

Protein 0.817 0.403

DM6 0.670

Mg 0.813

Ca 0.784

GFR7 -0.718

Fat 0.714

CuF8 0.566 0.710

NPN9 0.835

CoF10 -0.644

pH 0.799

RCT11 0.532 0.587

Percentage of explained variance; 127.45 %; 224.88 %; 310.65 %, 410.36 %. 441

5CRC: curd resistance to compression. 442

6DM: dry matter. 443

7GFR: gel firming rate. 444

8CuF: curd firmness. 445

9NPN: non-protein nitrogen. 446

10CoF: coagulum firmness. 447

11RCT: rennet coagulation time. 448

Page 23 of 25




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Figure captions 449

Figure 1. Ewes’ milk sample distribution according to the feeding regime in the two-450

dimensional coordinate system defined by canonical discriminant functions. ( ) indoor 451

feeding, ( ) transition feeding, and ( ) outdoor feeding. 452

Page 24 of 25




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Figure 1 - Abilleira 453

INDOOR

OUTDOOR

INDOOR

OUTDOOR

454

Page 25 of 25




93


75

Manuscrito 3. An accurate quantitative method for the analysis of terpenes

in milk fat by headspace solid-phase microextraction coupled to gas

chromatography-mass spectrometry

Food Chemistry, 120: 1162-1169, 2010


95

Analytical Methods

An accurate quantitative method for the analysis of terpenesin milk fat by headspace solid-phase microextraction coupledto gas chromatography–mass spectrometry

Eunate Abilleira a, Mertxe de Renobales b,*, Ana Isabel Nájera a, Mailo Virto b, Juan Carlos Ruiz de Gordoa b,Francisco José Pérez-Elortondo c, Marta Albisu c, Luis Javier R. Barron a,*

a Tecnología de Alimentos, Facultad de Farmacia, Universidad del País Vasco/Euskal Herriko Unibertsitatea, Paseo de la Universidad 7, 01006 Vitoria-Gasteiz, SpainbBioquímica y Biología Molecular, Facultad de Farmacia, Universidad del País Vasco/Euskal Herriko Unibertsitatea, Paseo de la Universidad 7, 01006 Vitoria-Gasteiz, SpaincNutrición y Bromatología, Facultad de Farmacia, Universidad del País Vasco/Euskal Herriko Unibertsitatea, Paseo de la Universidad 7, 01006 Vitoria-Gasteiz, Spain

a r t i c l e i n f o

Article history:Received 11 December 2008Received in revised form 25 June 2009Accepted 23 November 2009

Keywords:Terpene quantificationSPMEGas chromatographyMass spectrometryMilk traceability

a b s t r a c t

HS-SPME analysis of terpenes does usually have inherent quantification problems when working withcomplex samples, especially due to the matrix effect of the substrate or the calibration solution. Threedifferent terpene carrier matrices were compared: methanol, synthetic oil and milk fat obtained by cen-trifugation frommilk cream. Considerable differences in calibration sensitivity parameters were observeddepending on the matrix used and on the type of terpene standard analysed. For milk sample quantifica-tion purposes internal standard method was preferred using milk fat as calibration matrix. Linearityrange, repeatability, recovery and limits of detection and quantification were determined. Validationparameters were different depending on the concentration and molecular structure of each terpene ana-lysed, particularly between mono- and sesquiterpenes. The method was useful to determine in an accu-rate manner the terpene content in milk samples from pasture fed animals, and it will help to establishobjective terpene levels to differentiate milks from specific production systems.

� 2009 Elsevier Ltd. All rights reserved.

1. Introduction

Headspace solid-phase microextraction (HS-SPME) has beenwidely used to extract volatile and semi-volatile compounds fromdifferent food matrices (Bertelli, Papotti, Lolli, Sabatini, & Plessi,2008; Iglesias & Medina, 2008) including terpenes from milk andmilk products (Carpino et al., 2004; Favaro, Magno, Boaretto, Bailo-ni, & Mantovani, 2005). HS-SPME is an attractive alternative toother conventional sampling techniques because it can be fast, sen-sitive, solvent-less and economical. In addition to this, the highsensitivity of this technique towards terpenes has been reported(Czerwinski, Zygmunt, & Namiesnik, 1996).

The release of volatile compounds from solid or liquid matricestogether with the adsorption of released compounds onto the fibercoating are the main concerns to accurately quantify the content ofthese compounds in the matrix. Temperature and time are relevantparameters for the formation of the headspace because they affectthe vapour pressure values of the solutes and their partition coef-ficients between the gas phase and the fiber coating (Arthur and

Pawliszyn, 1990; Zabaras & Wyllie, 2001). During the extractionprocedure by HS-SPME, the amount of a certain compound presentin the gas phase is absorbed by the fiber coating at a much fasterrate than its release from the matrix, thus, a long time is requiredto reach equilibrium. This is particularly relevant for sesquiter-penes which show low vapour pressure values in combinationwith high partition coefficient values ranging from 10 to 100 foldhigher than those for monoterpenes (Zabaras & Wyllie, 2001).

Most HS-SPME approaches for the analysis of volatiles and terp-enes in milk and milk products are qualitative or semi-quantitativebecause of the difficulty to apply calibration methods (Carpinoet al., 2004; Fernandez, Astier, Rock, Coulon, & Berdagué, 2003;Juan, Barron, Ferragut, Guamis, & Trujillo, 2007; Povolo & Contarin-i, 2003; Viallon et al., 2000). However, different methods based onexternal or internal calibration have been developed for HS-SPMEdepending on the matrix and the target compounds, i.e., equilib-rium extraction, pre-equilibrium extraction, exhaustive extraction,diffusion-controlled calibration, kinetic calibration based on li-quid-coated or solid-coated fiber (Chen, Begnaud, Chaintreau, &Pawliszyn, 2006; Pizarro, Pérez-del-Notario, & González-Sáiz,2007; Zhao, Ouyang, & Pawliszyn, 2007; Zhou, Zhang, Ouyang,Es-haghi, & Pawliszyn, 2007). Other methods are based on quanti-fication of volatile compounds in the gas phase using the fibercoating/gas phase partition coefficients (Zabaras & Wyllie, 2001).

0308-8146/$ - see front matter � 2009 Elsevier Ltd. All rights reserved.doi:10.1016/j.foodchem.2009.11.050

* Corresponding authors. Tel.: +34 945 30 10 97; fax: +34 945 01 30 14 (M. deRenobales), tel.: +34 945 01 30 82; fax: +34 945 01 30 14 (L.J.R. Barron).

E-mail addresses: [email protected] (M. de Renobales), [email protected] (L.J.R. Barron).

Food Chemistry 120 (2010) 1162–1169

Contents lists available at ScienceDirect

Food Chemistry

journal homepage: www.elsevier .com/locate / foodchem


96

In all cases, matrix interference is one of the most important prob-lems that researchers have to face when quantifying volatile com-pounds in food samples (López, Lapeña, Cacho, & Ferreira, 2007;Vlachos, Kampioti, Kornaros, & Lyberatos, 2007). In this regard, dif-ferent authors have proposed the actual food matrix free of targetcompounds as calibration matrix (Bertelli et al., 2008; López et al.,2007; Perkins, D’Arcy, Lisle & Deeth, 2005; Vichi et al., 2003), but itis not always possible to use. Pure water was used as blank matrixfor the analysis of volatiles in foods with high water content suchas fresh fruits, vegetables and fish (Beltran et al., 2006; Iglesias &Medina, 2008). Commercial pump oil has been used as calibrationsolution to analyze hydrocarbons in milk using in-fiber SPME (Zhaoet al., 2007). However, the lack of terpene-free reference materialsmakes it difficult to construct calibration curves in food analysis,particularly in milk.

Addition of standard compounds has been frequently used toovercome matrix effects in HS-SPME and therefore, to improvethe accuracy and precision of the analysis (Biolatto et al., 2007;Favaro et al., 2005; Vazquez-Landaverde, Velazquez, Torres, &Qian, 2005). However, systematic errors can occur when this cali-bration method is used in complex foods analyzed by HS-SPME.The main problems are derived from either the difficulty to deliverstandards into complex sample matrices such as solid foods, gels,foams or emulsions (Afoakwa, Paterson, Fowler, & Ryan, 2009; Pin-ho, Ferreira, & Ferreira, 2002), or the use of a calibration matrix notanalogous to that of the sample, or when standards are spiked on amatrix that is not free of the target compounds. Systematic errorscan imply competition phenomena between solutes during theirrelease into the gas phase, and non-linear responses when soluteconcentrations are very low (Perkins, D’Arcy, Lisle, & Deeth 2005).

Terpenes are a group of lipophilic aliphatic compounds, origi-nated from the secondary metabolism of plants, whose structureis derived from 2 or 3 isoprenoid units for mono- and sesquiter-penes, respectively (Bouvier, Rahier, & Camara, 2005). Terpenesare abundant in certain plant families, especially dicotyledonswhile they are scarce in monocotyledons (Mariaca et al., 1997).In addition, other environmental factors affect the qualitative andquantitative terpene composition of plants. Terpenes can be rap-idly transferred from herbs or forages into milk fat (Viallon et al.,2000). Milks obtained from animals fed natural pasture containedapproximately ten times more terpenes than milks obtained fromanimals fed the corresponding hay (Cornu et al., 2005). It has alsobeen reported that cheeses made with milk from cows fed nativepasture were much richer in terpenes than cheeses made with milkfrom cows fed only total mixed ration (Carpino et al., 2004). Thus,terpenes have been proposed as pasture and fresh forage feedingbiomarkers by several authors (Bugaud, Buchin, Hauwuy, & Cou-lon, 2001; Cornu et al., 2005). Some of these terpenes have beenproposed as chemical fingerprints to discriminate between milksfrom either different geographical locations of pastures, or highand lowlands cow milks (Engel et al., 2007; Fernandez et al.,2003). However, accurate quantitative methods must be optimizedin order to use terpenes as molecular markers of feeding type ofthe ruminants, and justify the added value of milk and cheese pro-duced in extensive systems based on grazing either in low (valley)or high lands (mountain). These quantitative methods will enableestablishing objective levels to differentiate milks from specificproduction systems such as pasture grazing or mountain dairyproducts, which should be of great interest for Protective Denom-ination of Origin (PDO) Regulatory Councils.

The objective of this work was to develop an accurate quantita-tive method of analysis by HS-SPME–GC–MS to determine the ter-pene content in milk. Different internal calibration matrices werecompared and validation parameters such as linearity, precision,accuracy and limits of detection and quantification were calculatedfor mono- and sesquiterpenes.

2. Materials and methods

2.1. Milk samples

Ewe’s rawmilk samples (bulk milk) from two commercial flockswere analyzed in duplicate. Commercial flocks were located in theBasque Country Region (Northern Spain) and they belonged to PDOof Idiazabal cheese. Samples were taken from flocks that sinceearly spring are were allowed to graze. One flock grazed on culti-vated grasslands (i.e. ryegrass) at �500 m altitude (valley milk),and the other one on other higher altitude grasslands (�1000 m)which were not cultivated and which had higher diversity of grassspecies (mountain milk). Milk samples were stored at �80 �C untilanalysis.

2.2. Chemicals and gases

All solvents were of analytical grade (Panreac, Barcelona, Spain).Standards of terpenes (see Table 2) were purchased from Fluka andSigma–Aldrich (Madrid, Spain). Standards were of high purity(P90%), except for a-terpinene (P85%), terpinolene (P85%) andvalencene (P70%). High purity (P95%) 1,3,5-triisopropylbenzene(TIPB) was purchased from Fluka. High purity (P99%) n-paraffinmixtures of alkanes from C7 to C24 were purchased from Supelco(Bellefonte, USA). Polyalphaolefin (PAO) synthetic oil (type 5061)was purchased from Repsol (Madrid, Spain). PAO consisted of amixture of hydrocarbons (American Petroleum Institute, WA,USA). Helium was of 99.999% purity (Praxair, Madrid, Spain).

2.3. Sample preparation

A two-step centrifugation was done to extract the milk fat con-taining terpenes from whole milk using a method adapted fromViallon et al. (2000). First, milk cream was separated at 2000gand 4 �C for 30 min in a RC-5B Plus centrifuge (Sorvall, CT, USA).Then 35 g of this cream were placed in 50 mL polypropylene tubesand centrifuged at 17000g and 20 �C for 1.5 h in a 3K30 centrifuge(Sigma, Osterode, Germany). The supernatant oily phase wasrecovered using a Pasteur pipette. Five gram oil phase was spikedwith 2 lL of a 0.5 g/L n-pentane solution of TIPB by using a 700 ser-ies 10 lL volume syringe (Hamilton, Reno, USA) with accuracywithin ±1% of nominal volume. TIPB was spiked as internal stan-dard to reach 200 lg/kg of final concentration. 1 g oil phase ali-quots were used for terpene extraction.

2.4. SPME sampling

1 ± 0.005 g of milk oil phase was placed in 4 mL amber vialssealed with PTFE/silicone septa (Supelco). Terpenes were extractedfrom the vial headspace at 40 �C for 30 min using a 1 cm StableFlexfiber coating 30/50 lm Diviniylbenzene/Carboxen/Polydimethyl-siloxane (Supelco). Headspace pre-equilibration time was 10 minat 40 �C. The sampling was carried out in a Unitronic 320 OR ther-mostatic water bath (Selecta, Barcelona, Spain) using a SPME fiberholder for manual use (Supelco).

2.5. Gas chromatography analysis

Headspace terpene compounds were analyzed using a GC 8000series gas chromatograph coupled to an MD 800 mass spectrome-ter detector (Fisons Instruments, Milan, Italy). Data were recordedand analyzed with the Xcalibur version 1.1 Software (Thermo Finn-igan, Manchester, UK). Analyses were carried out on a Supelcowax(Supelco) capillary column (60 m � 0.25 mm � 0.25 lm film thick-ness). Fiber was desorbed in the injector port at 240 �C. Fiber was

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conditioned at 270 �C for 1 h before the first extraction. The splitvalve was opened 5 min after injection. Helium was used as thecarrier gas with a flow rate of 1 ml/min. Oven temperature was ini-tially held at 40 �C for 10 min, then increased to 110 �C at 5 �C/minfollowed by 10 �C/min to 240 �C (Juan et al., 2007). The transfer linefrom the chromatograph to the mass spectrometer was held at250 �C.

2.6. Detection and identification of terpenes

Mono- and sesquiterpenes were detected by Electronic Impact(EI) mass spectrometry at 70 eV operating in full scan mode (2scan/s) from m/z 19 to 250. Source temperature was 200 �C. Com-pounds were identified by comparing their mass spectra withthose of authentic standards and the National Institute of Stan-dards and Technology (NIST, USA) mass spectral library. Linearretention indexes (LRI) of each compound were also comparedwith those of authentic standards. Five replications were done tocalculate LRI for mono- and sesquiterpene standards and samplepeaks relative to a C7–C24 alkane series.

To increase the specificity and sensitivity of the detection, sam-ple analysis was carried out under SIMmode detection. Ionsm/z 93and 136 were monitored for monoterpenes and ions m/z 93, 136,161, 189 and 204 were recorded for sesquiterpenes (Viallon etal., 2000).

2.7. Quantification and validation procedure

Sample quantification and calibration procedure was carriedout under SIM mode. Three different calibration matrices wereused to compare peak area response/concentration values, and re-sponse factors relative to that of the internal standard (TIPB):methanol, PAO synthetic oil, and milk fat obtained by centrifuga-tion as described above. Bulk milk from early lactation ewes fedconcentrate pellets and hay indoors was selected to extract themilk fat used as blank matrix (Fig. 1). Two mixed solutions in n-pentane of terpene standards were prepared depending on thepurity grade of each terpene standard to avoid peak interferences.The concentration of each compound in the mixed solutions wasaround 0.5 g/L. One mixed solution (solution A) contained 3-car-ene, limonene, p-cymene, a-humulene and valencene. The other

mixed solution (solution B) contained a-pinene, 2-carene, a-ter-pinene, terpinolene, b-caryophyllene, b-cedrene and b-chamigrene.A 0.5 g/L n-pentane solution of TIPB was used as internal standard.Calibration curves were assayed in duplicate by spiking the matri-ces separately with each of the solutions A and B together with thatof TIPB to reach final concentrations of the compounds fromaround 300 to 6000 lg/kg. At least, four points were used for cali-bration curves. One gram spiked calibration matrix aliquots wereused for HS-SPME extraction.

Milk fat was used as calibration matrix for method validation.This procedure included linearity response, recovery and precisionanalysis, detection and quantification limits. Two new mixed solu-tions (solutions A1 and B1) in n-pentane of terpene standards wereprepared. Solution A1 consisted of solution A together with b-citr-onellene and b-pinene dissolved in concentrations of around 0.5 g/L. Solution B1 consisted of solution B together with camphene,myrcene and a-cubenene dissolved in concentrations of around0.5 g/L. Calibration curves were assayed in duplicate by spikingmilk fat with each of the solutions A1 and B1 and the internal stan-dard solution (TIPB) to reach final concentrations of the com-pounds from around 1 to 6000 lg/kg. When calibration was notlinear in this concentration range, it was divided in narrower con-centration ranges. All the calibration lines were calculated abovethe detection limits of the terpenes. Table 2 shows the concentra-tion ranges assayed for each compound. At least, four points wereused for calibration curves. One gram spiked milk fat aliquots wereused for HS-SPME extraction.

Recovery trials were carried out in duplicate by spiking milk fatwith solution B1 to reach 50–100, 300–500 and 1300–1900 lg/kgfinal concentrations of the compounds. One single concentrationof each terpene was tested inside each of the three concentrationranges. Internal standard (TIPB) was added to reach a constant finalconcentration of 400 lg/kg.

Analytical method repeatability was checked and five completeanalyses of the same real milk fat sample were done. In this case,the milk fat sample was spiked with 0.5 g/L n-pentane solutionof TIPB as internal standard to reach 130 lg/kg of finalconcentration.

All the standard solutions and internal standard (TIPB) wereadded to calibration matrices or samples using a 700 series 10 lLvolume syringe (Hamilton).

Fig. 1. Chromatograms of PAO synthetic oil and milk fat blanks analysed by HS-SPME–GC–MS. Peak numbers: 1: a-pinene; 2: toluene; 3: camphene; 4: limonene; 5: 2-(2-nitropropenyl)cyclohexanone; 6: 3-heptadecyn-1-ol; 7: 1,2,3-trimethylbenzene; 8: 4-methylpyrimidine; 9: 7-methyltetradecen-1-ol acetate; 10: 2-methyl-1-hexadecanol.Peaks 1–4 were positively identified. Peaks 5–10 were tentatively identified by comparison of their mass spectra with the NIST mass spectral library.

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Limits of detection (LOD) and quantification (LOQ) were deter-mined following the IUPAC approach (IUPAC Compendium ofChemical Terminology, 1997) by measuring the average noiseand standard deviation value (arbitrary units) when analysing 10blanks (calibration matrix). Average noise plus 3 times and 10times standard deviation were used respectively for LOD andLOQ, which were expressed in lg/kg for individual terpene stan-dards calculated from their calibration regression lines.

2.8. Statistical analysis

SPSS statistical package, version 16.0 (SPSS Inc. MI, USA) wasused for statistical analysis. Regression analysis was used to calcu-late linear regression equations for solutes in the calibration stud-ies. Analysis of variance (ANOVA) on the regression parameterswas done to establish that intercepts and slopes were significantly(p 6 0.05) different from zero. Student’s t test was applied to estab-lish significant (p 6 0.05) differences in the terpene content be-tween valley milk and mountain milk samples.

3. Results and discussion

Table 1 shows the linear calibration parameters for terpenestandards dissolved in methanol, PAO and milk fat as calibrationmatrices in the concentration range from around 300 to 6000 lg/kg. When terpenes were dissolved in methanol, determinationcoefficients (R2) lower than 0.885 were observed for monoter-penes, excepting a-pinene, whereas when calibration solutionwas PAO synthetic oil or milk fat, R2 higher than 0.980 were found.Regardless of calibration matrix, R2 higher than 0.900 were foundfor sesquiterpenes. Standard error of regression (SEr) was higherfor methanol matrix than for oily matrices, and SEr for sesquiter-penes was lower than that for monoterpenes in milk fat matrixin particular. Calibration sensitivity evaluated as slope value ofregression line was different depending on molecular structureand calibration matrix (Table 1). When standards were dissolvedin milk fat, the calibration sensitivity for monoterpenes was con-siderably higher than for sesquiterpenes which were strongly re-tained in the oily matrix. This occurred because as the solubilityof volatile and semi-volatile compounds in a hydrophobic solventincreases, the vapour–liquid partition coefficient decreases (Dru-aux, Le Thanh, Seuvre, & Voilley, 1998). Another reason to explainthis behaviour is that the vapour pressure values at the tempera-

ture used in the headspace are higher for monoterpenes than forsesquiterpenes (Fichan, Larroche, & Gros, 1999). In this respect,Helmig et al. (2003) found a downward linear relationship be-tween saturation vapour pressure and Linear Retention Index(LRI) for terpenes. As it can be seen in Table 2, LRI for sesquiter-penes were higher than those for monoterpenes.

Similar results to those observed for milk fat were obtainedwhen solutes were dissolved in PAO synthetic oil, with the excep-tion of p-cymene which showed the lowest calibration sensitivityin the latter matrix. This compound formulated as 4-isopropyltol-uene was the only monoterpene constituted by toluene aromaticstructure which strongly increased the solubility of p-cymene inthe PAO oil. Slope values for all terpene compounds dissolved inmethanol were comparable, with no differences being observedbetween mono- and sesquiterpenes. Again, p-cymene showed thelowest calibration sensitivity in this solvent indicating the effectof toluene structure on the solubility of this compound in metha-nol in comparison with the rest of terpenes.

Taking into account the points discussed above, calibration sen-sitivity for sesquiterpenes in oily matrices was lower than in meth-anol. Monoterpenes showed higher calibration sensitivity in milkfat than in methanol except for terpinolene. This increment inthe sensitivity value was particularly high for 3-carene, limoneneand p-cymene. In general, lower sensitivity values were found formonoterpenes when PAO oil was compared to methanol (Table 1).

TIPB was selected as internal standard to quantify terpenesusing HS-SPME extraction (Favaro et al., 2005), and the calibrationsensitivity for this compound was also compared when dissolvedin methanol, PAO oil and milk fat (Table 1). In spite of its highersensitivity in methanol compared to oily matrices, higher R2 andlower SEr values were recorded for TIPB in these matrices. Thestudy of the relative response factors of terpenes with respect toTIPB (RRFTIPB) was done in the three calibration matrices (Table1). As expected, RRFTIPB values were different regarding the individ-ual compound and matrix used. When terpenes were dissolved inmilk fat, monoterpenes showed lower RRFTIPB values than sesqui-terpenes among which some showed RRFTIPB values higher than 3(valencene, b-caryophyllene and b-chamigrene, Table 1). Whenterpenes were dissolved in PAO oil, monoterpenes showed RRFTIPBvalues lower than 2, except for p-cymene which showed a calibra-tion sensitivity (slope) around 9-times lower than that of TIPB (Ta-ble 1). RRFTIPB values for sesquiterpenes were higher than twoexcept for b-caryophyllene whose calibration sensitivity wasaround 2.5-times higher than that of the internal standard. When

Table 1Linear calibration parameters for terpene standards dissolved in methanol, PAO synthetic oil and milk fat as calibration matrices in the concentration range from around 300 to6000 lg/kg, using 1,3,5-triisopropylbenzene (TIPB) as internal standard. Analyses were in duplicate, and at least four calibration points were used.

Compound Methanol PAO synthetic oil Milk fat

Slope SEra R2b RRFTIPB

c Slope SEra R2b RRFTIPB

c Slope SEra R2b RRFTIPB

c

a-Pinene 353 19.47 0.964 2.84 339 18.16 0.989 0.41 507 9.47 0.983 0.402-Carene 432 47.55 0.883 2.32 420 10.49 0.990 0.33 594 10.72 0.986 0.343-Carene 592 59.77 0.883 1.69 566 13.48 0.988 0.25 3251 49.47 0.995 0.06a-Terpinene 651 71.49 0.823 1.54 88 1.45 0.993 1.59 761 16.30 0.981 0.27Limonene 415 60.73 0.753 2.42 600 13.66 0.991 0.23 1674 25.55 0.996 0.12p-Cymene 30 5.71 0.655 33.35 15 0.43 0.981 9.03 136 2.15 0.995 1.49Terpinolene 770 97.70 0.809 1.30 288 3.96 0.997 0.48 505 10.67 0.984 0.40TIPB 1003 70.53 0.951 1.00 139 3.04 0.993 1.00 204 2.69 0.994 1.00b-Caryophyllene 411 30.64 0.958 2.44 351 3.86 0.998 0.40 37 0.56 0.996 5.58b-Cedrene 955 31.49 0.960 1.05 65 2.12 0.980 2.16 73 0.98 0.996 2.79a-Humulene 922 62.64 0.957 1.09 30 1.50 0.975 4.63 98 1.76 0.993 2.09b-Chamigrene 567 28.55 0.963 1.77 31 1.52 0.953 4.48 32 0.52 0.993 6.32Valencene 715 40.10 0.946 1.40 35 1.70 0.946 3.93 53 0.94 0.986 3.82

a Standard error of the regression value �10�4.b Coefficient of determination.c Relative response factor of terpenes with respect to internal standard.



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methanol was used as calibration matrix, RRFTIPB values rangedfrom 1.05 to 2.84 for mono- and sesquiterpenes, except for p-cym-ene whose calibration sensitivity was more than 30-times lowerthan that of TIPB (Table 1).

The results showed that despite the differences observed be-tween the two oily matrices, these ones were more suitable cali-bration matrices than methanol to quantify terpene content inmilk fat samples using TIPB as internal standard. To our knowl-edge, there is no oily matrix free of terpenes commercially avail-able. For this reason specificity assays were investigated in suchoily matrices. A lot of peaks were detected in the headspace ofthe PAO oil which consisted of aliphatic and aromatic hydrocarbonmolecular structures containing ions m/z 93, 136 or 189, beingtoluene the most abundant compound (Fig. 1). The mean LOD esti-mated from the disturbance of the base line in the chromatogramsof the PAO oil was 23992 abundance units, and many interferencepeaks were above LOD. No information about composition of theheadspace of synthetic oils has been reported when these oils havebeen proposed as calibration matrix (Zhao et al., 2007). The head-space of the milk fat employed for calibration had toluene andthree monoterpene compounds in very low quantities (Fig. 1).The mean LOD estimated for milk fat was around 10-times lower(2505 abundance units) than for PAO oil. The estimated contentof a-pinene, camphene and limonene detected in milk fat blankswas 1.10, 1.59 and 2.82 lg/kg, respectively. These concentrationswere very close to their LOD and lower than their LOQ values (Ta-ble 2). Some authors have used deodorized vegetable oil as calibra-tion matrix but no data about its composition were provided (Vichiet al., 2003). Toluene was the main peak detected both in milk fatand PAO oil blanks. However, this compound was completely sep-arated from monoterpenes in either milk fat blanks or milk fatsamples. It has been reported that toluene in dairy products is re-lated to the metabolism of b-carotene (Molimard & Spinnler,1996). On the other hand, freezer storage of milk could increasethe toluene content of the samples (Bosset, Gubler, Bütikofer, &Gauch, 2000). In this regard, the bulk milk used to obtain the blankmatrix and the milk samples were frozen at �80 �C.

Taking into account the above mentioned results, milk fat wasselected as calibration matrix to validate the quantification meth-od of terpenes in milk fat samples. In this respect, changes in thecomposition of major milk fat components (triglycerides and fattyacids) due to seasonal changes (Abilleira et al., 2009; Perea et al.,2000) might be taken into account when milk fat is used as calibra-tion matrix. However, no relevant changes in the physicochemicalproperties of fat matrix at 40 �C would be expected because milkfat is completely liquid at this headspace temperature. The sea-sonal variation in fatty acid composition of milk fat affect mainlyits solid fat content and rheological properties associated withthe solid–liquid ratio at temperatures inside the melting range(Zdzislaw & Sikorski, 2002). Anyway, calibration matrix suitabilityshould be checked when milk fat is used for this purpose.

For the validation of the method, new terpene standards foundin milk were included, and the concentration range of terpenes wasextended from around 1 to 6000 lg/kg (Table 2). As terpene stan-dards were spiked into the milk fat calibration matrix, peak areasfor a-pinene, camphene and limonene were corrected by subtrac-tion. Sesquiterpenes, TIPB and monoterpenes b-citronellene, b-pinene, 3-carene, myrcene, a-terpinene, limonene and p-cymeneshowed linear responses (R2 > 0.98), being their calibration sensi-tivity very similar to that obtained when the concentration rangedfrom 300 to 6000 lg/kg (Table 1). As expected, RRFTIPB values forthese terpenes were very close to those obtained for concentra-tions greater than 300 lg/kg. However, other monoterpenes suchas a-pinene, camphene, 2-carene and terpinolene showed differentcalibration sensitivity values depending on the concentrationranges. The lower the concentration, the higher the linear slopeand the lower the RRFTIPB values (Table 2). In consequence, whena calibrated method is proposed to quantify terpenes using HS-SPME, the linearity range must be carefully delimited, particularlyfor very low quantities.

Limit of detection (LOD) and limit of quantification (LOQ) werecalculated for the terpenes using milk fat as calibration matrix (Ta-ble 2). In general, lower values for LOD and LOQ were recorded formonoterpenes than for sesquiterpenes. Monoterpenes showed LOD

Table 2Linear calibration parameters for terpene standards and 1,3,5-triisopropylbenzene (TIPB), relative response factors of terpenes with respect to internal standard (RRFTIPB), andlimits of detection (LOD) and quantification (LOQ) using milk fat as calibration matrix in the concentration range from around 1 to 6000 lg/kg. Analyses were in duplicate for eachconcentration, and at least four calibration points were used.

Compound LRIa Concentration range (lg/kg) Slope R2b RRFTIPB LOD (lg/kg) LOQ (lg/kg)

a-Pinene 1016 1–68 4291 0.999 0.05 0.58 1.2068–338 1401 0.953 0.15338–3389 507 0.983 0.41

b-Citronellene 1034 90–4873 96 0.992 2.15 26.19 53.99Camphene 1063 1–75 2997 0.999 0.07 0.84 1.72

75–375 1020 0.953 0.20375–3760 350 0.988 0.59

b-Pinene 1107 1–5568 3378 0.996 0.06 0.74 1.532-Carene 1132 1–358 1945 0.967 0.11 1.29 2.65

358–3587 594 0.986 0.353-Carene 1149 1–5216 3324 0.996 0.06 0.75 1.55Myrcene 1166 1–3328 886 0.990 0.23 2.83 5.83a-Terpinene 1178 7–2447 781 0.984 0.26 3.21 6.61Limonene 1195 1–5755 1692 0.997 0.12 1.48 3.05p-Cymene 1284 101–5398 137 0.996 1.50 18.23 37.57Terpinolene 1296 8–824 1060 0.999 0.19 2.36 4.87

824–4112 505 0.984 0.41a-Cubebene 1471 57–2831 73 0.998 2.84 34.51 71.13TIPB 1491 1–5127 206 0.996 1.00 0.21 0.43b-Caryophyllene 1626 97–4824 36 0.996 5.72 69.60 143.47b-Cedrene 1632 83–4140 72 0.997 2.85 34.61 71.33a-Humulene 1709 101–5368 98 0.993 2.11 25.64 52.86b-Chamigrene 1750 394–3976 32 0.995 6.43 78.15 161.07Valencene 1758 69–3705 53 0.989 3.90 47.42 97.74

a Linear Retention Index.b Coefficient of determination.



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and LOQ values lower than 3.5 and 7.0 lg/kg, respectively, exceptfor b-citronellene and p-cymene. LOD and LOQ values for sesqui-terpenes were higher than 25.5 and 52.5 lg/kg, respectively. Theselimits for mono- and sesquiterpenes were in agreement with theircalibration sensitivity values, that was, the higher the calibrationsensitivity (slope), the lower the LOD and LOQ (Table 2).

Replications on a real milk fat sample were used to measure theintra-assay precision (repeatability) of the HS analytical method.Values for relative standard deviation (RSD) were equal or lowerthan 20% (Table 3), which, although slightly high, it can be accept-able for a HS method (Beltran et al., 2006).

Recovery trials were carried out at three different concentra-tions for selected pure terpene standards. One single concentrationof each terpene was tested in each of the concentration ranges (Ta-ble 4). Quantities higher than LOQ values for each terpene weredetermined. Mean recovery percentages for sesquiterpenes rangedfrom 81.17% to 86.07% being the best recovery percentages (near-est to 100%) at concentrations of 1300–1900 lg/kg. However,mean recovery values for monoterpenes ranged from 60.57% to126.73% finding the best recovery value for each compound at adifferent concentration range (Table 4). It was remarkable thatrecovery for some monoterpenes, particularly for those with lowLRI values, at different concentration ranges were higher than100%, reflecting the presence of systematic errors in the recoveryof the quantitative method. It has been also reported that solutesin concentration close to LOQ can be subjected to systematic errors

yielding recovery values higher than 100% (Garrido-Frenich et al.,2006). Recovery results include the overall systematic error ofthe analytical procedure which might be due to the matrix effect,fiber adsorption capacity and competition phenomena betweencompounds during headspace equilibration, fiber desorption andthe responses of the terpene compounds at MS detector. If the con-centration range of 50–100 lg/kg is not considered, mean recoveryfactors for terpenes were from 62% to 113% which can be accept-able taking into account the analytical procedure used. To the bestof our knowledge no data on recovery percentages has been re-ported before for terpene analysis by HS-SPME.

Milk fat samples were analysed by the HS-SPME–GC–MS meth-od using TIPB (200 lg/kg spiked in milk fat sample) as internalstandard. All the compounds found in the milk fat samples werecompletely resolved in a reasonable time of analysis (37 min). Sixpeaks represented common terpenes whereas other peaks couldnot be identified. Amounts reported for these non-identified com-pounds were estimated using the RRFTIPB value of the nearest re-tained terpene in the calibration study (Tables 2 and 5).According to data reported in the literature, these not identifiedcompounds which contained ions m/z 93 and 161 were probablyconstituted by isoprene units (Buchin et al., 2002; Fernández-Gar-cía, Imhof, Schlichtherle-Cerny, Bosset, & Nuñez, 2008). Compara-tive terpene content between milk fat samples from commercialewes flocks grazing in fertilised grasslands (valley milk) and inother grasslands with a higher diversity of grass species (mountainmilk) is shown in Table 5. Terpenes were accurately quantified inboth valley and mountain milk samples showing significantly(p 6 0.05) higher content in sesquiterpenes in mountain milk sam-ples than in valley milk samples. This difference was mainly due tothe high content found for b-caryophyllene in mountain milk. Fav-aro et al. (2005) proposed monitoring the content of this sesquiter-pene as tracer compound to differentiate mountain cheeses (Table5).

4. Conclusions

The HS-SPME–GC–MS method developed in this work allowsthe accurate determination of terpene contents in milk fat. Themethod based on the use of milk fat as calibration matrix and1,3,5,triisopropylbenzene (TIPB) as internal standard was capableof quantifying very low amounts of terpenic compounds with suit-able reliability. The accurate quantification of terpene compoundsin milk will be useful for determining traceability of milk and

Table 3Intra-assay precision (n = 5) for the quantitative HS-SPME method applied to a realmilk fat sample spiked with 130 lg/kg of 1,3,5-triisopropylbenzene (TIPB) as internalstandard.

Terpene LRIa Mean content (lg/kg) RSDb

a-Pinene 1014 1495.35 16.92Camphene 1062 31.89 20.14b-Pinene 1106 47.22 16.66Limonene 1195 29.43 9.98NI1c 1371 36.28 10.42NI2d 1496 317.55 11.03NI3d 1513 453.59 9.82b-Caryophyllene 1624 1856.35 19.04a-Humulene 1708 487.27 12.16

a Linear Retention Index.b Relative standard deviation (%).c Not identified and quantified using RRFTIPB for terpinolene.d Not identified and quantified using RRFTIPB for a-cubebene.

Table 4Recovery trials for the quantitative HS-SPME method applied to a milk fat sample spiked with terpene standards at different concentrations (50–100, 300–500 and 1300–1900 lg/kg) and 400 lg/kg of 1,3,5-triisopropylbenzene (TIPB) as internal standard. Analyses were in duplicate for each concentration.

Compound 50–100 lg/kg 300–500 lg/kg 1300–1900 lg/kg

Recoverya RSDb Recoverya RSDb Recoverya RSDb Meana RSDb

a-Pinene 154.94 2.86 94.56 14.36 128.65 3.24 126.05 22.12Camphene 149.88 1.93 92.13 14.25 134.13 4.17 125.38 21.922-Carene 105.14 4.86 70.32 10.73 136.73 4.49 103.73 28.62Myrcene 123.66 6.68 86.80 5.35 74.36 0.64 94.94 24.57a-Terpinene 155.09 8.21 119.85 5.16 105.24 0.41 126.73 18.76Terpinolene 57.13 8.72 41.80 3.26 82.79 0.88 60.57 30.83a-Cubebenec 77.73 2.55 94.40 0.60 86.07 11.27b-Caryophyllened 72.71 14.21 89.64 1.74 81.17 14.15b-Cedrenee 79.14 5.04 89.01 0.59 84.08 7.31b-Chamigrenef 76.74 18.01 86.61 1.10 81.67 12.02

a Recovery percentages.b Relative standard deviation (%).c Concentration range 50–100 lg/kg was not assayed because estimated LOQ was 71.1 lg/kg.d Concentration range 50–100 lg/kg was not assayed because estimated LOQ was 143.5 lg/kg.e Concentration range 50–100 lg/kg was not assayed because estimated LOQ was 71.3 lg/kg.f Concentration range 50–100 lg/kg was not assayed because estimated LOQ was 161.1 lg/kg.



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cheese products and to differentiate milks from specific productionsystems including grazing managements or dairy products ofmountain origin. The study highlighted that non-calibrated HS-SPME methods do not provide reliable data on the terpene compo-sition. The study reported that matrix effect is one of the main con-tributors to the overall systematic error to determine terpenesamount in milk fat. In order to minimize this effect and get reliableresults, matrix-matched calibration was the preferred approach.

Acknowledgements

The authors thank local farmers for supplying milk samples.This work was supported by grant from Universidad del País Vas-co/Euskal Herriko Unibertsitatea – Cátedra UNESCO (05102). E.Abilleira acknowledges a predoctoral fellowship from the BasqueGovernment.

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Table 5Terpene content (lg/kg) in milk fat samples from commercial flocks grazing in fertilised grasslands at �500 m altitude (valley milk) and in other grasslands at �1000 m altitudewith a higher diversity of grass species (mountain milk). Samples were spiked with 200 lg/kg of 1,3,5-triisopropylbenzene (TIPB) as internal standard. Analyses were in duplicatefor each milk sample.

Compound LRIa Valley milk Mountain milk P

Mean RSDb Mean RSDb

a-Pinene 1016 12.06 8.79 13.31 1.13 nsCamphene 1063 1.86 4.30 1.80 17.22 nsb-Pinene 1107 3.41 8.21 2.17 16.13 nsLimonene 1195 6.25 7.68 5.35 13.65 nsNI1c m/z 93 1321 nd 247.62 3.65NI2c m/z 93 1448 nd 278.27 24.84NI3d m/z 93. 161 1515 219.97 6.06 ndNI4d m/z 93 1559 nd 1135.47 25.42b-Caryophyllene 1626 294.78 1.90 718.73 0.78 ***

NI5e m/z 93. 136 1670 nd 1763.85 21.76a-Humulene 1709 56.72 9.49 122.65 5.14 ***

NI6f m/z 93 1718 79.76 9.29 ndNI7g m/z 93. 136 1781 nd 1881.09 19.84NI8g m/z 93. 161 1797 nd 410.86 5.66Total identified monoterpenes 23.58 8.06 22.63 5.66 nsTotal identified sesquiterpenes 351.50 3.13 841.38 1.42 ***

Total identified terpenes 375.08 3.44 864.02 1.56 ***

NI: not identified; nd: not detected; ns: not significant (p > 0.05).a Linear Retention Index.b Relative standard deviation (%).c Quantified with RRFTIPB for a-cubebene.d Quantified with RRFTIPB for b-caryophyllene.e Quantified with RRFTIPB for b-cedrene.f Quantified with RRFTIPB for a-humulene.g Quantified with RRFTIPB for valencene.

*** p 6 0.001.



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85

Manuscrito 4. Seasonal changes in terpene concentrations of milk from

ewes managed under part-time grazing

Enviado a Journal of Agricultural and Food Chemistry el 1 de diciembre de 2009

Ref.: jf-2009-04162g


105

For Review. Confidential - ACS

ACS Paragon Plus Environment

Submitted to Journal of Agricultural and Food Chemistry


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1

Seasonal changes in terpene concentrations of milk 1

from ewes managed under part-time grazing 2

Eunate Abilleira a, Mailo Virto c, Ana Isabel Nájera a, Marta Albisu b, Francisco José Pérez-3

Elortondo b, Juan Carlos Ruiz de Gordoa c, Mertxe de Renobales c,**, Luis Javier R. Barron a,* 4

a Tecnología de Alimentos, b Nutrición y Bromatología, c Bioquímica y Biología Molecular, 5

Facultad de Farmacia. Universidad del País Vasco/Euskal Herriko Unibertsitatea, Paseo de la 6

Universidad 7, 01006 Vitoria-Gasteiz, Spain 7

8

9

Running title header: Seasonal changes in terpene content of ewe´s milk 10

* To whom correspondence should be adressed. Tel.: +34 945 01 30 82; fax: +34 945 01 30 14. E-mail address: [email protected] (L.J.R. Barron).

** Co-corresponding author. Tel.: +34 945 30 10 97, fax: +34 945 01 30 14. E-mail address: [email protected] (M. de Renobales).

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ABSTRACT 11

Terpene composition of ewes’ raw milk from eleven commercial flocks was analyzed monthly 12

from February to July. Terpenes have been proposed as potential pasture biomarkers in milk, but 13

multiple factors affect the terpene composition of pastures. Such diversity questions the suitability 14

of terpenes as dietary markers under real conditions where the feeding management changes 15

throughout the season. In this study, ewes’ diet consisted of concentrate and conserved forage in 16

winter and part-time grazing with indoor supplementation from spring. The major monoterpenes 17

were limonene and β-phellandrene and the major sesquiterpene was β-caryophyllene. Fresh pasture 18

increased the total terpene content of milks and sesquiterpenes were only detected from May to 19

July. A positive correlation was observed between β-caryophyllene and the seasonal variable 20

lactation days which reflected the evolution of the feeding. β-Caryophyllene might be a good 21

candidate, but some points need clarification before proposing it as a reliable pasture-marker. 22

23

24

25

26

27

Key-words: terpenes, ewe’s milk, part-time grazing. 28

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INTRODUCTION 29

30

In recent years, consumers are becoming more concerned about the quality of the food that they 31

purchase in the markets. This growing demand for information includes details about 32

environmental issues, animal welfare and production conditions of the ruminant derived products, 33

with particular interest in the diet (1, 2). This fact is even more important for traditional and high- 34

value-added products, which is the case of the Idiazabal Protected Denomination of Origin (PDO) 35

cheese produced from the milk of the latxa breed under study. Latxa sheep are reared in a definite 36

geographical area of the Basque Country and Navarre in northern Spain. They are fed concentrate 37

and conserved forages during pasture shortage and fresh pasture the rest of the year, with indoor 38

supplementation to meet the nutritional needs of the animals. The use of the land contributes to 39

maintaining clean forests and attracting tourism, but the most interesting thing is that the pasture is 40

a component of the “terroir” concept which is closely related to the authenticity and quality of 41

some cheeses (3). In addition, better nutritional quality of pasture milk and cheeses has been 42

recently reported (4-6). Until now, no specification about the feeding management exists for 43

Idiazabal PDO cheese and, in the last few years, pasture grazing as part of the diet is decreasing 44

due to the abandonment of rural areas and because sheepherding is a very demanding and not a 45

socially appreciated activity (7). In order to ensure the continuity of this system, and in response to 46

consumer demand, there is a need to increase the value of cheese manufactured from grazing ewes 47

and differentiate it from cheese from ewes kept indoors all year around. If new specifications 48

regarding flock management and feeding of the sheep are to be included, it is very important for 49

PDO Regulatory Councils to have an authentication tool of the animal diet to certify the higher 50

value of pasture cheeses. In this sense, terpenes have been proposed several times as potential 51

pasture biomarkers in milk, cheese, and meat products of ruminants (2, 8-10). 52

Terpenes originate from the secondary metabolism of plants and they can be rapidly transferred 53

to milk from feed (11, 12). Approximately ten times more terpenes were found in milk from 54

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animals fed pasture than in milk from animals fed the corresponding hay (13). Cheeses made with 55

milk from cows fed pasture were much richer in terpenes than cheeses made with milk from cows 56

fed only total mixed ration (14). However, environmental factors, soil characteristics, botanical 57

composition, and geographical location of the pasture, as well as phenological stage of each grass 58

species contribute to the high diversity in the terpene composition of the pasture (8). In addition to 59

this large variability throughout the grazing season, grazing management also affects the terpene 60

content in milk. A continuous increase of terpenes was observed in strip grazing strategy while 61

very little effect was observed in paddock grazing (15). But, despite the considerable amount of 62

research on the topic it remains unclear whether these compounds would be useful to trace the diet 63

of the ruminants under real conditions where diets consist of a mixture of fresh pasture and other 64

feeds. 65

On the other hand, the lack of homogeneity in the methodology used for the extraction and pre-66

concentration of these compounds makes it difficult to compare the results reported by different 67

authors (11, 14, 16). Several authors have used the headspace solid-phase microextraction (HS-68

SPME) to extract terpenes from milk and milk products (14, 16) because of the high sensitivity 69

towards these compounds showed by HS-SPME (17). Most HS-SPME methods used had a semi-70

quantitative approach which made it impossible to establish objective levels or compare real 71

quantities between different terpene compounds because they had different responses due to matrix 72

effects and competition phenomena for adsorption onto the fibre (16, 18). 73

The objective of the present work was to check the suitability of terpenes as diet type markers 74

under real conditions throughout the season when the feeding management implies changes in the 75

proportions of different types of feed in the diet, in particular fresh pasture. 76

77

MATERIALS AND METHODS 78

Chemicals. Terpene standards were purchased from Fluka and Sigma-Aldrich (Madrid, Spain). 79

High purity (≥99%) n-paraffin mixtures of alkanes from C7 to C24 were purchased from Supelco 80

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(Bellefonte, USA). High purity (≥95%) 1,3,5-triisopropylbenzene (TIPB) was purchased from 81

Fluka. n-Pentane was of analytical grade (Panreac, Barcelona, Spain). Helium was of 99.999 % 82

purity (Praxair, Madrid, Spain). 83

Samples. Eleven commercial flocks of latxa sheep participated in this study. All the flocks 84

belonged to the PDO Idiazabal cheese and were located in the Basque Country at an altitude 85

between 500 and 900 m. The flocks consisted of 100-500 heads and had the same seasonal lambing 86

system. Suckling lambs were weaned with 30 days, and milk production period for cheese-making 87

extended from winter to early summer. Ewes were milked twice a day using automatic milking 88

machines. Bulk milk samples (1.5 L) of each flock were monthly taken from each farmhouse 89

throughout this period from February to July. In each sampling day sheepherders filled a thorough 90

questionnaire about the quantity and composition of the feeds given to the sheep. In outline, all the 91

sheepherders followed the same feeding strategy that consisted of concentrate and conserved 92

forages (alfalfa and grass hay, maize and grass silage) in winter and part-time grazing with varying 93

supplementation of concentrate and forage (depending on the grazing time) from spring onwards. 94

Each farmhouse purchased different concentrate formulation and conserved forages from local 95

suppliers and some of the sheepherders prepared the forages themselves. Nutritional labels of the 96

concentrates were collected. Average composition of the concentrates on a dry matter basis was as 97

follows: crude protein 19.73 ± 2.25 %, crude fat 3.18 ± 0.88 %, crude fibre 7.59 ± 2.05 %, ashes 98

6.89 ± 1.38 %. Animals grazed on cultivated private grasslands where ryegrass (Lollium perenne) 99

and white clover (Trifolium repens) were predominant species, and in other non-cultivated 100

community-own grasslands. The pasture composition of such community-own grasslands in this 101

area has been reported by Mandaluniz et al. (19) and consisted of herbaceous species such as 102

Trifolium repens, Festuca rubra and Agrostis capillaris, but also other non-graminoid plants and 103

some shrubs. Fresh pasture intake was estimated from the time spent on pasture and the rest of 104

feeds ingested (20). Milk samples were stored at –80 ºC until analysis. 105

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Terpene analysis. Terpene analysis was carried out according to Abilleira et al. (18). Briefly, 106

terpenes were extracted by HS-SPME from the oily phase obtained by centrifugation of the milk 107

samples. Spiked oil phase aliquots were placed in 4 mL vials at 40 °C for 30 min using TIPB as 108

internal standard (200 µg/kg). SPME manual holder (Supelco) with a 1 cm DVB/CAR/PDMS fibre 109

(Supelco) was used to trap volatiles from the vial headspace. 110

Terpenes were analysed using an 8000 series gas chromatograph (GC) equipped with a 111

Supelcowax (Supelco) capillary column (60m x 0.25mm x 0.25µm film thickness) and coupled to 112

an MD 800 mass spectrometer (MS) detector (Fisons Instruments, Milan, Italy). Fibre was 113

desorbed in the injector port at 240 ºC during 5 min in splitless mode. Helium (1 mL/min) was 114

used as carrier gas. Oven temperature was initially held at 40 ºC for 10 min, then increased to 110 115

ºC at 5 ºC/min followed by 10 ºC/min to 240 ºC. MS detector operated by Electron Impact (EI) at 116

70 eV in full scan mode (2 scan/s) from m/z 19 to 250. Source temperature was 200 ºC. 117

Compounds were identified by comparing their mass spectra with those of authentic standards and 118

the National Institute of Standards and Technology (NIST, USA) mass spectral library. A series of 119

C7-C24 n-alkanes was run to calculate the linear retention indexes (LRI). LRI of each compound 120

was also compared with those of authentic standards. Terpenes from milk samples were also 121

analysed under SIM mode detection monitoring ions m/z 93 and 136 for monoterpenes and ions 122

m/z 93, 136, 161, 189 and 204 for sesquiterpenes (11). Concentrations of individual terpenes were 123

calculated in the milk samples using the internal standard quantification method as described by 124

Abilleira et al. (18). Analyses were carried out in duplicate. Terpene content was expressed as 125

µg/kg of milk fat. 126

Statistical analysis. SPSS statistical package, version 17.0 (SPSS Inc., Michigan, USA), was 127

used for statistical analysis. Analysis of variance (ANOVA) was used to determine the presence of 128

significant differences (P ≤ 0.05) in the analytical variables throughout the production season. A 129

mixed model of repeated-measures ANOVA was performed. “Flock” was used as fixed factor 130

whereas the “season” was the repeated-measures factor. The partial eta-square statistic (called the 131

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effect size measure) was used to describe the proportion of the total variability explained by the 132

factors. Principal component analysis (PCA) was performed on individual terpenes and days of 133

lactation as seasonal variable. Only variables with communality values higher than 0.4 were 134

included. The Kaiser criterion (eigenvalue > 1) was used to select the principal components. 135

Factors were rotated (Varimax method) for ease of interpretation. 136

137

RESULTS AND DISCUSSION 138

Feed management. The responses to the questionnaire about the feeds used by farmers provided 139

information on the contribution to the diet of each type of feed (Figure 1). In February the diet 140

consisted of cereal-based concentrate formulations (43 ± 17 %) and conserved forages (54 ± 14 %) 141

and only one flock was allowed to graze but not longer than 1 h/d. In March there was a great 142

variability in the percentage of fresh pasture in the diet (55 ± 29 %) because it was a transition 143

month in which some of the flocks started to graze. However, none of them stayed longer than 5 144

h/d in the pasture. From April on, all the flocks spent at least 5 hours in the pasture. Along with 145

this, the concentrate and forage amount in the diet decreased resulting in an important increase of 146

the contribution of the fresh pasture to the diet of the flocks. From April to July the fresh pasture 147

became the predominant component of the diet accounting for 82 ± 9 % of the ingested feeds 148

(Figure 1). 149

Climate could affect the type and amount of terpenes transferred from pasture to milk because 150

the production of secondary metabolites and essential oils by plants is affected by thermal and 151

moisture conditions (15, 21, 22). In this sense, it should be pointed out that weather conditions 152

were rather similar for all locations of the flocks participating in this study. Average monthly 153

temperatures from February to July were: 3.4 ºC, 9.4 ºC, 10.7 ºC, 14.1 ºC, 18.0 ºC and 20.7 ºC (23) 154

indicating a very cold winter followed by an extraordinary warm spring and summer. The monthly 155

accumulated rainfall records from February to July were: 50.8 L/m2, 146.7 L/m2, 53.9 L/m2, 32.9 156

L/m2, 57.0 L/m2 and 46.9 L/m2 (23) indicating very low rainfall records except for March. 157

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Terpenes. The effect of “season” on terpene concentration was always significant (P ≤ 0.05) as 158

well as the effect of “flock” and the interaction “season*flock”. The effect size measure for 159

“season” and “flock” factors was higher than 0.8 for all the terpene compounds. The factor “flock” 160

greatly influenced the concentration of terpenes. This factor involved uncontrolled effects such as 161

flock intrinsic characteristics, differences in flock and feeding management, grazing strategies, type 162

of pastures used (including botanical composition, phenological stage of the plants, location or soil 163

characteristics), and slight differences in daily weather conditions due to different locations of the 164

farms. Despite this variability, significant differences (P ≤ 0.05) attributable to the effect of 165

“season” were observed. 166

A total of twelve terpenes were positively identified in milk fat of latxa ewes throughout the 167

season. Nine corresponded to monoterpenes: α- and β-pinene, camphene, myrcene, α-terpinene, 168

limonene, β-phellandrene, p-cymene and terpinolene, and the other three were sesquiterpenes: α-169

cubebene, β-caryophyllene and α-humulene. All of them have been previously identified in other 170

studies where the importance of botanical composition of the pasture and maturity stage of the 171

plants in terpene profile and content was highlighted (24, 25). 172

Mean total concentrations of mono- and sesquiterpenes found in milk samples throughout the 173

season are shown in Figure 2 and those of individual terpenes in Figure 3. As it was expected, 174

total terpene content of milk samples was significantly (P ≤ 0.05) higher in spring and summer 175

months than in winter months (February and March) (Figure 2). According to the review by 176

Prache et al. (10), milk from animals grazing in pasture contains a wider range and higher amounts 177

of terpenes than milk from ruminants that are fed concentrate or conserved forage. In the present 178

study, winter months corresponded to stall-fed period and spring-summer months to pasture-based 179

diets. March was a transition month where indoor-feeds still constituted about the half of the ration 180

(Figure 1). With respect to individual terpene composition of the milk samples, all the identified 181

mono- and sesquiterpenes were found in spring and summer months whereas in the milks from 182

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winter months only some monoterpenes (limonene, β-phellandrene, α- and β-pinene and 183

camphene) and no sesquiterpenes were detected (Figure 3). 184

Monoterpenes. Monoterpenes accounted for 90 ± 28 % of total terpenes found in the milk 185

samples throughout the season. Limonene was the predominant monoterpene every month (55 ± 11 186

% of total monoterpenes) followed by β-phellandrene (27 ± 5 % of total monoterpenes), β- and α-187

pinene (18 ± 5 % and 17 ± 10 % of total monoterpenes, respectively), whereas camphene, myrcene, 188

α-terpinene, p-cymene and terpinolene together represented less than 23 ± 13 % of total 189

monoterpenes in each month. Other authors reported that limonene, β-phellandrene, β- and α-190

pinene were the main monoterpenes in milk and cheese (15, 16, 24, 25). 191

Higher concentrations of monoterpenes were found in the milks of spring and summer months 192

(ranging from 247 µg/kg in May to 1137 µg/kg in June) compared to the milks of winter months 193

(56 and 53 µg/kg in February and March, respectively) (Figure 2). The high concentration of 194

monoterpenes in the milks of spring and summer months was basically due to the accumulation of 195

the major monoterpenes limonene and β-phellandrene in amounts ranging from 58 to 762 µg/kg 196

per month and compound. Minor monoterpenes were also accumulated in the milks of spring and 197

summer months although some of them such as myrcene, α-pinene, p-cymene and terpinolene were 198

not always detected (Figure 3). The variability observed for individual monoterpenes ranged from 199

12 to 171 % which was in good concordance with data reported by Agabriel et al. (24) taking into 200

consideration the uncontrolled factors involved in the commercial farmhouses participating in this 201

study. 202

Sesquiterpenes. Sesquiterpenes were only detected in the milks from May to July and they 203

accounted for 22 ± 37 % of total terpenes in these months (Figure 2). α-Humulene was detected in 204

the milk samples from the three months accounting for 51 ± 35 % of total sesquiterpenes in each 205

month. β-caryophyllene was the main sesquiterpene accounting for 72 ± 28 % of total 206

sesquiterpenes, except in June when it was not detected. It must be remarked that β-caryophyllene 207

concentrations lower than 144 µg/kg were not quantifiable according to the method used in this 208

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work (18). α-Cubebene accounted for 32 ± 13 % of total sesquiterpenes in May. Other authors have 209

reported that β-caryophyllene was the main sesquiterpene in milk and cheese (15, 16, 24, 25). 210

The highest concentrations of sesquiterpenes were found in May and July (362 and 262 µg/kg, 211

respectively) mainly due to the accumulation of β-caryophyllene and α-humulene. The lowest 212

accumulation of sesquiterpenes in June (66 µg/kg) was only due to the concentration of α-213

humulene, whereas the minor sesquiterpene α-cubebene was only accumulated in concentrations 214

close to 80 µg/kg in the milks of May (Figures 2 and 3). The lower accumulation of 215

sesquiterpenes in June might be caused by lower terpene concentrations in plants due to 216

environmental factors that will be discussed later. 217

Relationship between terpenes in milk and feed management. The evolution of individual 218

terpenes detected in the milk samples followed an oscillating trend throughout the season. In 219

February and March, when the proportion of fresh pasture in the diet was still low or non-existent, 220

very low concentrations of terpenes were detected and they were exclusively monoterpenes 221

(Figures 2 and 3). Because terpenes are plant secondary metabolites, the main dietary source of 222

the monoterpenes found in the milks from winter months was the conserved forage (hay and 223

silage) (Figure 1). Viallon et al. (11) showed that terpene profile of milk was strongly affected by 224

the forage type ingested by the animals and that the distribution of terpenes in the forages was very 225

plant-specific. Other authors reported that the botanical species in the forage determined milk 226

terpene profile, whereas forage conservation methods affected terpene content (26). Figueiredo et 227

al. (27) reported reduced percentage of terpenes in red clover silage compared to the fresh plant 228

and a drop in the most common sesquiterpene (β-caryophyllene) in hay. It has also been reported 229

that grass species (Gramineae or monocotyledons) are poor in terpenes, especially in 230

sesquiterpenes, whereas forbs (non-Leguminosae dicotyledons) are rich in those compounds (8, 11, 231

26). According to the questionnaires filled by the sheepherders the forages given to the sheep were 232

basically alfalfa hay (Leguminosae), and grass hay (Gramineae) (data not shown), so the results of 233

winter months are consistent with those reported in the literature. 234

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On the contrary, the highest concentrations for monoterpenes were recorded from April to July 235

(Figure 2) when fresh pasture became the predominant component of the diet (Figure 1). 236

Sesquiterpenes were found in considerable quantities from May on (Figure 2). Again the higher 237

content of monoterpenes could be related to the fresh pasture intake and the presence of 238

sesquiterpenes to the higher diversity of plant species in the pastures (26). The information 239

collected about the botanical species of the pastures indicated that the predominant plants were 240

terpene-poor species because they belonged to graminoids or leguminouses. Although plants 241

selected by the sheep were not monitored, and neither were plant communities of non-cultivated 242

pastures analysed, the milk samples of the commercial flocks showed the highest diversity of 243

terpene compounds when flocks were allowed to graze (Figure 3). It was remarkable that although 244

in April the time spent on pasture of the commercial flocks was comparable to the following 245

months, sesquiterpenes were not detected in the milks from this spring month. Because plants of 246

pastures were not analysed, it was very difficult to find an explanation for it, but it could be due to 247

the maturity stage of the plants or to the metabolism of the animals that were adapting to the new 248

diet during this spring month. In this respect, Schlichtherle-Cerny et al. (28) demonstrated that 249

rumen fermentation had an impact on the terpene profile probably due to hydrogenation reactions. 250

Viallon et al (11) observed a gap between the variations of mono- and sesquiterpenes after a shift 251

in the diet from a terpene-poor to a terpene-rich hay suggesting that differences in solubility of 252

each terpene group in the animal tissues might have slowed down the incorporation of 253

sesquiterpenes to the milk fat. On the other hand, weather conditions could affect the accumulation 254

of terpenes in the plants of pastures, and ultimately affect the terpene composition of the milks 255

from grazing flocks (15, 21). 256

In order to relate seasonal changes to terpene composition of milk samples, a principal 257

component analysis (PCA) was applied to individual terpenes and days of lactation of each flock as 258

seasonal variable. Four principal components (PC) accounting for 80.93 % of the total variance 259

were extracted (Table 1). Six monoterpenes, including major compounds (myrcene, α-terpinene, 260

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limonene, β-phellandrene, p-cymene and terpinolene), showed positive loadings (≥ 0.89, except for 261

terpinolene) with PC1 (38.25 % of the total variance), whereas other two minor monoterpenes such 262

as β-pinene and camphene were positively correlated (≥ 0.94) with PC2 (17.26 % of the total 263

variance). The sesquiterpenes α-cubebene and α-humulene had high positive loadings (≥ 0.79) with 264

PC4 (11.00 % of the total variance), whereas β-caryophyllene together with the monoterpene α-265

pinene were highly correlated (≥ 0.82) with PC3 (14.44 % of the total variance). The seasonal 266

variable days of lactation showed also a positive loading (0.61) with PC3 indicating that β-267

caryophyllene and α-pinene were correlated with the evolution of the season (Table 1). As the 268

season progressed the contribution of the fresh pasture to the diet of the flock increased, and the 269

two terpene compounds which better reflected this seasonal pattern were β-caryophyllene and α-270

pinene. As mentioned above, one of the most interesting points reported in this study is that 271

sesquiterpenes were absent in the milks when sheep were not grazing. In consequence, if any 272

terpene is going to be proposed as potential pasture biomarker in the production management used 273

by farmers in this study, a sesquiterpene as β-caryophyllene would be more appropriate than a 274

monoterpene. Supporting this idea, Dumont and Adda (29) and Favaro et al. (16) found 275

sesquiterpenes only in cheeses made from summer milk when animals grazed mountain pastures. 276

Other authors found sesquiterpenes in winter during non-grazing periods, but their amount was 277

more than doubled when the animals were fed on fresh pasture (24). In this sense, some authors 278

have proposed β-caryophyllene as a generic marker of grass feeding in cheese and meat products 279

because of its ubiquity in fresh pasture plants (2, 8, 9, 16). 280

In short, a marked influence of the fresh pasture on the terpene content of milk fat from 281

commercial latxa flocks was observed. Terpene content increased significantly when animals were 282

reared under part-time grazing. Regardless of the feeding, limonene and β-phellandrene were the 283

most abundant monoterpenes and β-caryophyllene showed the highest concentrations among 284

sesquiterpenes. Bearing in mind the large amount of factors that can affect the terpene content in 285

milk, it is difficult to propose a reliable terpene to differentiate diets based on part-time grazing 286

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from those based on concentrate and conserved forages. However, our results indicated that a 287

sesquiterpene would be more suitable for that purpose. Despite not been detected in June, β-288

caryophyllene was directly related to the increasing proportion of fresh pasture in the diet. 289

Nevertheless, to use a sesquiterpene such as β-caryophyllene as a pasture-diet marker, important 290

issues need to be addressed. These issues include the occurrence of these compounds in the 291

different types of forages, the origin of the forages and the effect of the conservation method, as 292

well as the minimum threshold of accumulated concentration in milk to consider that it has been 293

obtained from animals fed in pasture. In-depth studies are necessary to clarify these points. In light 294

of the results obtained in the present work, in this type of pasture-traceability studies, relevant 295

information about the feeding and grazing management of the production system that is being 296

investigated should be considered. 297

298

ACKNOWLEDGEMENTS 299

The authors thank local farmers for supplying cheese samples and technical information on their 300

farming and feeding systems, the Regulatory Board of PDO Idiazabal cheese and Artzai-Gazta 301

sheepherders association for technical support. 302

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25. Viallon, C.; Verdier-Metz, I.; Denoyer, C.; Pradel, P.; Coulon, J. B.; Berdagué, J. L. 370

Desorbed terpenes and sesquiterpenes from forages and cheeses. J Dairy Res. 1999, 66, 319-326. 371

26. Fedele, V.; Pizzillo, M.; Claps, S.; Cifuni, G. F. Effect of types of forage on terpenes 372

content and profile in goat milk. Options Méditerranéennes A. 2007, 74, 19-24. 373

27. Figueiredo, R.; Rodrigues, A. I.; do Céu Costa, M. Volatile composition of red clover 374

(Trifolium pratense L.) forages in Portugal: the influence of ripening stage and ensilage. Food 375

Chem. 2007, 104, 1445-1453. 376

28. Schlichtherle-Cerny, H.; Imhof, M.; Fernández-García, E.; Bosset, J. O. Changes in terpene 377

composition from pasture to cheese. Mitt. Lebensm. Hyg. 2004, 95, 681-688. 378

29. Dumont, J. P.; Adda, J. Occurrence of sesquiterpenes in mountain cheese volatiles. J. 379

Agric. Food Chem. 1978, 26, 364-367. 380

381

NOTE 382

This work was supported by grants from the Universidad del País Vasco/Euskal Herriko 383

Unibertsitatea (Leioa, Spain) together with the Departamento de Medio Ambiente y Ordenación 384

del Territorio del Gobierno Vasco (UNESCO Cathedra/2005), and the Instituto Nacional de 385

Investigación y Tecnología Agraria y Alimentaria (Madrid, Spain) (RTA2006-00100-C02-02). E. 386

Abilleira acknowledges a predoctoral fellowship from the Gobierno Vasco/Eusko Jaurlaritza. 387

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FIGURE CAPTIONS 388

Figure 1. Average contribution of different feed types to the diet of the flocks throughout the milk 389

production season of 11 commercial latxa flocks. 390

391

Figure 2. Mean concentrations of mono- and sesquiterpenes in milk fat from 11 commercial flocks 392

throughout the milk production season. Different letters mean significant (P ≤ 0.05) differences 393

between months for each terpene group. Mean variation coefficient throughout the production 394

season for each terpene group was the following: monoterpenes 174 ± 89 %, sesquiterpenes 26 ± 395

22 % and total terpenes 156 ± 87 %. 396

397

Figure 3. Mean concentrations of individual terpenes in milk fat from 11 different commercial 398

flocks throughout the milk production season. Different letters mean significant (P ≤ 0.05) 399

differences between months for each individual terpene. Mean variation coefficient throughout the 400

production season for each terpene was the following: limonene 171 ± 97 %, β-phellandrene 114 ± 401

60 %, β-pinene 116 ± 66 %, myrcene 41 ± 53 %, α-terpinene 41 ± 42 %, p-cymene 12 ± 8 %, α-402

pinene 71 ± 41 %, camphene 63 ± 51 %, terpinolene 26 ± 30 %, β-caryophyllene 44 ± 18 %, α-403

humulene 22±25 %. α-Cubebene was only detected in May with a variation coefficient of 34 %. 404

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TABLES 405

Table 1. Rotated factor loadings for factors 1, 2, 3 and 4 for principal 406

component analysis applied to milk samples from 11 commercial flocks 407

throughout the season. Factor loadings lower than, or equal to, an absolute 408

value of 0.250 are set to 0. 409

Variable Principal components

1 2 3 4

Myrcene 0.982

α-Terpinene 0.978

Limonene 0.975

β-Phellandrene 0.926 0.326

p-Cymene 0.891 0.350

Terpinolene 0.519

β-Pinene 0.969

Camphene 0.261 0.941

β-Caryophyllene 0.858

α-Pinene 0.817

Days of lactation 0.608

α-Cubebene 0.870

α -Humulene 0.794

410

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Figure 1 411

0

20

40

60

80

100

February March April May June July

% F

od

der

Concentrate Conserved forage Fresh pasture

412

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Figure 2 413

0

200

400

600

800

1000

1200

1400

Feb Mar Apr May Jun Jul

µg/K

g

MonoterpenesSesquiterpenesTotal terpenes

a aa a

d

c

b

c

c

d

e

aa a

bc

d

e

monoterpenes sesquiterpenes total terpenes

0

200

400

600

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µg/K

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a aa a

d

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b

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monoterpenes sesquiterpenes total terpenes

414

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For R

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β-p

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β-phella

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Feb

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Jun

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α-h

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Jun

Jul

g/Kg

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10

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Feb

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Apr

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Jun

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g/Kga

a

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Feb

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111

Manuscrito 5. Winter/spring changes in fatty acid composition of

farmhouse Idiazabal cheese due to different flock management systems

Journal of Agricultural and Food Chemisty, 57: 4746-4753, 2009


131pubs.acs.org/JAFC Published on Web 04/27/2009 © 2009 American Chemical Society

4746 J. Agric. Food Chem. 2009, 57, 4746–4753

DOI:10.1021/jf900460u

Winter/Spring Changes in Fatty Acid Composition ofFarmhouse Idiazabal Cheese Due to Different Flock

Management Systems

EUNATE ABILLEIRA,† MARIUS COLLOMB,§ HEDWIG SCHLICHTHERLE-CERNY,§

MAILO VIRTO,# MERTXE DE RENOBALES,*,# AND LUIS JAVIER R. BARRON*,†

†Tecnolog�ia de Alimentos, Facultad de Farmacia, Universidad del Pa�is Vasco/Euskal HerrikoUnibertsitatea, Paseo de la Universidad 7, 01006 Vitoria-Gasteiz, Spain, §Agroscope Liebefeld-PoiseuxResearch Station ALP, Schwarzenburgstrasse 161, 3003 Bern, Switzerland, and #Bioqu�imica y Biolog�iaMolecular, Facultad de Farmacia, Universidad del Pa�is Vasco/Euskal Herriko Unibertsitatea, Paseo de la

Universidad 7, 01006 Vitoria-Gasteiz, Spain

Typically, two different flock managements are employed by basque sheepherders in winter and

spring. Thus, seasonal changes in the fatty acid (FA) composition of Idiazabal PDO farmhouse

cheeses were studied. Ewe0s raw milk cheeses elaborated in winter and spring were collected after

120 days of ripening from 10 Idiazabal PDO farmhouses. In winter, concentrate and conserved

forages were fed, whereas a part-time grazing system was adopted from spring onward. Spring

cheeses had less (P e 0.05) saturated FA and higher (P e 0.05) content of unsaturated FA,

including trans-FA (mainly trans-vaccenic acid) and conjugated linoleic acid (CLA), branched-chain

FA (BCFA), and n-3 FA. Principal component analysis (PCA) separated winter and spring cheeses

into two groups by the combination of two principal components (84.2% of variance). Fresh pasture

in the diet enhanced desirable FA and lowered atherogenicity index in cheeses, supporting the

benefits of using a part-time grazing system for the consumer.

KEYWORDS: Fatty acids; CLA; cheese; pasture; season; management; feed

INTRODUCTION

It is well-known that ewe’s milk production is of greateconomic importance in Mediterranean countries where mostof the milk produced is converted into cheese. A brief overallreview on the cheesesmanufactured in the Iberian peninsula frommilk of small ruminants can be consulted in the work publishedbyFreitas andMalcata (1 ). Idiazabal ProtectedDenomination ofOrigin (PDO) cheese is a semihard, raw milk cheese exclusivelymade from the milk of the latxa and carranzana breeds. It isproduced in a definite geographical area that involves the BasqueCountry region and Navarre in northern Spain. In this arearearing animals on pastures is an ancestral tradition, whichcontributes to maintaining clean forests, attracting tourism, andmost interestingly increasing consumer acceptance of sheep-derived high-quality products. Nowadays, the most frequentlyused flockmanagement system in the BasqueCountry is based onconcentrate and conserved forages during pasture shortage andon pastures for the rest of the year, with indoor supplementationwhen needed to satisfy the nutritional needs of the animals.Oregui andFalaganPrieto (2 ) reported that in theMediterraneanbasin pastures tend to decrease in the farm environment and, as aconsequence, in the feeding strategies, leading to the loss of the

authenticity and quality of some cheeses (3 ). Thus, it is of greatimportance to provide scientific evidence of the advantages andbenefits of pasture-based systems to encourage sheepherders notto abandon them.

Cheese composition is determined by milk composition (4 ),which in turn depends on other main production factors such asgenotype, reproduction and sanitary characteristics of animals,agroclimatic conditions, and socioeconomical environment andfarming methods, including feeding and milking. However, feed-ing is the most important one because other factors, such asseason or flock sanitary status, are influenced by changes in thequantity and quality of the feeds ingested (3 ).

Milk fat is the main nutrient affected by dietary changes, andits lipid composition has gained attention in recent years becauseof its nutritional implication in human health. Although milk fatis highly saturated (rich in lauric, myristic, and palmitic acids),which could be related to coronary heart disease risk (5 ), othercomponents are considered to be beneficial to human health.Among them, butyric acid, oleic acid, branched-chain fatty acids(BCFA), and polyunsaturated fatty acids (PUFA), especially n-3fatty acids (n-3 FA) and conjugated linoleic acids (CLA), areclaimed to have potential antiatherogenic, antiobesity, or anti-carcinogenic roles (6-8).

In this respect, PUFA-enriched diets (including fish oils, plantoils, and seeds) have been fed to ruminants because a highersupply of these fatty acids results in lower saturated fatty acid(SFA) concentrations in milk and cheese. Fresh pasture is a good

*Corresponding authors [(L.J.R.B.) telephone +34 945 01 30 82,fax +34 945 01 30 14, e-mail [email protected]; (M.d.R.)+34 945 30 10 97, fax +34 945 01 30 14, e-mail [email protected]].


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Article J. Agric. Food Chem., Vol. 57, No. 11, 2009 4747

alternative to marine and plant oil supplements as a source ofPUFA. It is especially rich in R-linolenic acid (C18:3 c9c12c15)(7 ), which is extensively biohydrogenated in the rumen to trans-vaccenic acid (TVA; C18:1 t11) (6 ) and further desaturated in themammary gland to yield the naturally predominant CLA calledrumenic acid (RA; C18:2 c9t11) (9 ). Hence, a healthier fatty acidprofile could be achieved by integrating pasture in the diet of theflock.

Several experiments have been conducted to improve thenutritional quality of milk fat trying to enhance the level ofbeneficial fatty acids. Although there is a great deal of informa-tion about the impact of different supplements and diets on dairycattle (6, 10-14), fewer studies have been conducted on ewes (3, 7,15), and information in natura under real farming conditions forthis species is very scarce.

The aim of this work was to evaluate the effect of season of theyear associated with changes in the management system ofcommercial flocks on fatty acid composition, including detailedCLA isomeric profile, in farmhouse PDO Idiazabal cheese.

MATERIALS AND METHODS

Chemicals. The following compounds were obtained as indicated:pure methyl esters of fatty acids, C4:0, C5:0, C6:0, C8:0, C9:0, C10:0,C12:0, C14:0, C16:0, C17:0, C18:0, C20:0 (HPLC or GC grade; Merck,Darmstadt, Germany); C15:0, C18:1 c9 and t9, C19:0, C18:2 t9t12, C18:2c9t12, C18:2 c9c12, C18:3 c6c9c12, C20:1 t11, C20:1 c5, C20:1 c9, C20:1c11, C18:3 c9c12c15, C22:0, C20:3 c8c11c14, C20:5 c5c8c11c14c17 (EPA),C22:5 c7c10c13c16c19 (DPA), C22:6 c5c7c10c13c16c19 (Sigma, Buchs,Switzerland); C18:2 c9t11, C18:2 c9c11, C18:2 t9t11, C18:2 t10c12 in acidform (Matreya Inc., Pleasant Gap, PA); C7:0, C12:1 c11, C13:0, C14:1 t9,C16:1t9, C16:1 c9, C17:1 t10, C18:1 c11, C20:2 c11c14, C20:3 c11c14c17,C20:4 c5c8c11c14 (Nu-Chek-Prep Inc., Elysian, MN); iso-C12:0, anteiso-C12:0, iso-C13:0, anteiso-C13:0, iso-C14:0, anteiso-C14:0, iso-C15:0, iso-C16:0, iso-C17:0, anteiso-C17:0 (Laordan Fine Chemicals AB, Malm

::o,

Sweden). The methyl esters of CLA c9t11 and CLA t10c12 were obtainedfrom Matreya Inc., and other CLA isomers were synthesized by isomer-ization with I2. Solvents used for chromatography were obtained fromMerck (HPLC or GC grade). All other chemicals and reagents were ofanalytical grade and were obtained from local suppliers.

Sampling. Ten farmhouses located in the Basque Country in northernSpain and belonging to the PDO Idiazabal cheese were selected. Allfarmers elaborated their cheeses with the milk from their own flocks oflatxa breed sheep. Flock size ranged from 200 to 400 ewes as these weresmall factories usually run by a single family. Due to the seasonality of themilk production, cheeses are elaborated from the end of January until themiddle of July. Winter cheeses and late spring cheeses, with differentiatedflock management systems, were collected. A thorough standardizedquestionnaire about the type, quantities, and composition of the feedssupplied to each flockwas completed by the farmers. Each farmhouse useddifferent commercially available concentrate formulations and foragespurchased from local suppliers. Some of the sheepherders prepared theconserved forages themselves in their farms. The nutritional label of eachconcentrate formulation was also collected. Information about springfeeding was partially completed by estimating the fresh pasture intakefrom the time spent on pasture and the rest of feeds ingested (16 ). Foddercomposition data and milk and cheese yields are summarized in Table 1.

In winter, because good-quality fresh pastures were not available,intensive management systems based on concentrate and conservedforages were used. From spring onward, a part-time grazing system wasused, which consisted of a variable time allowance on pastures andcorresponding supplementation in stall during milkings. Sheep grazedboth in cultivated private grasslands dominated by ryegrass (Loliumperenne) and white clover (Trifolium repens) and in other noncultivatedcommunity-owned grasslands with a higher diversity of grass species.Pastureswere located at an altitude between 500 and 900mabove sea level.From a meteorological point of view, the first half of the year was verywarm with high rainfall records, and weather conditions were rathersimilar for all locations of the flocks participating in this study. Averageday temperatures of 6.9 and 14.3 �C were recorded for winter and spring,

respectively. The monthly accumulated rainfall was 175.7 L/m2 in winterand 82.4 L/m2 in spring.

Whole cheeses (∼1.5 kg/cheese) were collected directly from theripening chambers of each farmhouse after 120 days of ripening. Wintersampling was made during February andMarch, and late spring samplingwas made from the middle of May until the end of June. In each season(winter and spring) and farmhouse, two cheeses from the same vat werecollected. A total of 20 vats were sampled, 10 fromwinter and 10 from latespring. Average gross compositional values reported for ripened Idiazabalcheeses throughout the manufacturing season were as follows: percentageof dry matter (DM), 68.21 ( 1.87%; total fat percentage in DM, 52.06 (6.21%; and total protein percentage in DM, 34.81 ( 3.98% (17 ).

Sample Preparation. Cheeses were cut in eight sections of equalweight (∼180 g). The sections were vacuum-packed and frozen at-20 �Cuntil analysis. Two sections corresponding to different cheeses from thesame vat were ground and mixed for fat extraction after removal of therind (1.5 cm) from the portions. Therefore, a total of 20 cheese sampleswere prepared for fat extraction.

Fatty Acid Analysis. Fat was extracted from 10 g of ground cheesewith n-pentane using a Soxhlet apparatus. Extracted pure fat was thendissolved in n-hexane, and glycerides were trans-esterified to the corre-sponding fatty acid methyl esters (FAME) by a solution of 2M potassiumhydroxide in methanol (18 ).

Fatty acid (FA) composition was analyzed in duplicate by high-resolution gas chromatography (Agilent 6890, Santa Clara, CA) withflame ionization detector as described by Collomb and B

::uhler (19 ). Fatty

acids were separated on a CP-Sil 88 capillary column (100 m � 0.25 mmi.d. � 0.20 μm film thickness; Varian BV, Middleburg, The Netherlands)and identified on the basis of reference substances and published identi-fications according to the method of Collomb and B

::uhler (19 ). Quanti-

fication was made using n-nonanoic acid as internal standard. Extractedfat (0.300 g) was spiked with 5.0 mL of a 0.735 g of n-nonanoic acid/100mL of n-hexane solution. Results were expressed as grams of FA per 100 gof fat. Unresolved compounds are reported in the text and tables asA+B(i.e., C18:1 t10 + C18:1 t11); they did not separate under the presentconditions and were quantified together.

CLA isomers were analyzed in duplicate by silver ion (Ag+)-HPLC onan Agilent LC series 1100 HPLC apparatus (Santa Clara, CA), equippedwith a photodiode array detector (234 nm), using three ChromSpher Lipidcolumns in series (stainless steel, 25 cm � 4.6 mm i.d., 5 μm particle size,Chrompack, Middleburg, The Netherlands), according to the method ofRickert et al. (20 ), as modified by Kraft et al. (13 ). UV-grade n-hexanewith 0.1% acetonitrile and 0.5% ethyl ether was daily prepared to use assolvent at a flow rate of 1mL/min. The procedure described byKraft et al.(13 ) was followed for the quantitative analysis; the amount of theunresolved GC peak corresponding to CLA t7c9, CLA t8c10, and CLAc9t11 was used as the reference amount for the sum of the HPLC peakareas of these three isomers. The amount of each CLA analyzed byHPLC

Table 1. Fodder Composition (Mean ( Standard Deviation) and AverageMilk and Cheese Yields in Each Season (Winter and Spring)a

winter spring

concentrate (kg/day) 1.36 ( 0.42 a 0.86 ( 0.17 b

dry matter 1.20 ( 0.37 a 0.75 ( 0.15 b

crude protein 0.23 ( 0.06 a 0.15 ( 0.02 b

crude fiber 0.10 ( 0.06 a 0.05 ( 0.02 b

crude fat 0.04 ( 0.01 a 0.02 ( 0.01 b

ashes 0.08 ( 0.04 a 0.05 ( 0.02 b

conserved forageb (kg/day) 1.72 ( 1.06 a 0.20 ( 0.15 b

time on pasturec (h/day) 0.00 ( 0.00 a 7.06 ( 0.68 b

fresh pasture intakec (kg/day) 0.00 ( 0.00 a 4.56 ( 0.16 b

milk yield (L/ewe � day) 0.92 ( 0.14 a 0.50 ( 0.16 b

cheese yield (kg/L) 0.17 ( 0.01 a 0.21 ( 0.02 b

aWinter corresponded with intensive indoor flock management system. Springcorresponded with part-time grazing system. Means followed by different lower caseletters were significantly (P e 0.05) different between spring and winter cheeses.bConserved forages consisted of alfalfa and grass hay, grass silage, and maizesilage. cMainly cultivated grasslands with predominance of ryegrass and whiteclover.


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4748 J. Agric. Food Chem., Vol. 57, No. 11, 2009 Abilleira et al.

was calculated relative to this reference value. Results were expressed asmilligrams of FA per gram of fat.

The above-described GC and (Ag+)-HPLC methods have been pre-viously used to determine the fatty acid composition of ewe0s milk fat byCollomb et al. (21 ).

Statistical Analysis. The SPSS statistical package, version 16.0 (SPSSInc., Chicago, IL), was used for the statistical analyses. Analysis ofvariance (ANOVA) was used to determine the presence of significantdifferences (P e 0.05) in the analytical variables between cheeses fromwinter-feeding flocks and spring-feeding flocks. A general linear modelwas used including “season” as fixed effect and “factory” as randomeffect.F test of the “season” against the interaction term “season � flock” wasused to determine significant differences. Principal component analysis(PCA) was performed on a matrix of the flock feeding variables andselected FA groups having communality values higher than 0.4. TheKaiser criterion (eigenvalue > 1) was used to select the principalcomponents. Factors were rotated (Varimax method) for ease ofinterpretation.

RESULTS AND DISCUSSION

Milk and Cheese Yields. Milk yield and cheese yield recordscorresponding to each season are reported in Table 1. In latespring, when the cheeses from part-time grazing systems wereelaborated, the animals were in their late-lactation phase and,accordingly, milk yield was lower (Pe 0.05) (22 ). Late-lactationmilk has higher dry matter content than the milk from earlylactation and, as a consequence, cheese yield was higher (P e0.05) in spring than in winter. In seasonal calving systems, theeffects of stage of lactation are confounded with those of season,that is, the effects of variation in photoperiod, weather, and diet.Because this study was conducted on commercial flocks underreal farming conditions, it was not possible to compare the indoorintensive management and the part-time grazing management inthe same season because they never coexist at the same time.However, Perojo et al. (16 ), observed very poor differences inmilk yieldwhen comparing animals with normal access to pastureunder the dairy latxa production system and animals withrestricted access to pasture and higher indoor supplement intake.These differences were nonexistent in terms of standard milkproduction, suggesting that replacement of pasture with indoorsupplementation might not result in higher cheese yields. Futurestudies on experimental flocks with well-controlled model sys-tems would help in understanding the effect of each single factor.

Groups of Fatty Acids. Mean concentrations of FA groups inwinter and spring cheeses are summarized in Table 2. Comparedto winter cheeses, spring cheeses had significantly (P e 0.05)lower concentrations of SFA (8.6% lower). The decrease in SFAcontent in spring cheeses was basically due to the decrease inshort-chain fatty acids (SCFA, 21.8% lower) and, to a lesserextent, inmedium-chain fatty acids (MCFA, 8.6% lower). On thecontrary, higher concentrations (P e 0.05) of long-chain fattyacids (LCFA, 24.3% higher), monounsaturated fatty acids(MUFA, 27.1% higher), and PUFA (18.8% higher), CLA(59.4% higher), and trans-FA without CLA (49.6% higher) werefound in cheeses from part-time grazing systems (spring cheeses)than in those produced during the winter months. The content ofBCFA and n-3 FA also increased (P e 0.05) in spring cheeses(12.2 and 21.4%higher, respectively), whereas the n-6 FAcontentand n-3/n-6 ratio did not differ significantly (P > 0.05) betweenwinter and spring cheeses (Table 2).

As a result of pasture-based feeding in spring, unsaturated fattyacid (UFA) content increased (Pe 0.05) to the detriment of SFAcontent in the cheeses. This led to a 1.5-fold decrease in theatherogenicity index of the cheese fat, defined as (C12:0 + (4 �C14:0) + C16:0)/UFA (23 ), resulting in a healthier fatty acidcomposition of cheeses from grazing flocks (Table 2). A similar

result was previously observed in milk fat of ewes (15 ) andlactating cows (12, 14) reared on grazing systems compared toindoor feeding based on concentrate and conserved forages.

SCFA and MCFA accounted for 88.1 and 83.6% of the totalSFA in winter and spring cheeses, respectively (Table 2). TheSCFA andMCFA groups generate from de novo synthesis in themammary gland by acetyl CoA carboxylase and fatty acidsynthase, and most of them are saturated because the Δ9-desaturase activity is very low when fatty acid chain length isshorter than 18 carbons (6 ). Palmquist et al. (10 ) suggested thatPUFA-rich diets inhibit de novo synthesis of fatty acids due to a

Table 2. Concentrations (Grams per 100 g of Fat, Mean ( StandardDeviation) of Fatty Acid (FA) Groups in Winter and Spring Cheeses

winter spring

significantly (P e 0.05) higher in winter

short-chain FAa 17.252( 0.985 13.487( 2.060

medium-chain FAb 41.735( 2.046 38.132( 3.141

saturated FAc 65.484( 2.253 59.838( 2.966

atherogenicity indexd 3.446( 0.207 2.349( 0.386

significantly (P e 0.05) higher in spring

long-chain FAe 26.465 ( 1.712 34.975( 4.261

C18:1 FAf 14.482( 0.984 19.976( 2.499

C18:2 FAg 3.078( 0.461 4.000( 0.536

unsaturated FAh 19.822 ( 0.998 26.622( 2.640

monounsaturated FAi 15.739 ( 1.020 21.593( 2.443

polyunsaturated FAj 4.083 ( 0.491 5.028( 0.575

trans-C18:1 FAk 2.185( 0.486 4.280( 1.267

conjugated linoleic acidsl 0.402( 0.124 0.989( 0.270

trans-FA without conjugated linoleic acidsm 2.829( 0.555 5.615( 1.634

branched-chain FAn 1.827 ( 0.131 2.079( 0.189

n-3 FAo 0.934( 0.130 1.188 ( 0.269

without significant (P > 0.05) differences

n-6 FAp 2.992( 0.424 2.988( 0.250

n-3 FA/n-6 FA 0.372( 0.084 0.297( 0.072

a C4:0, C5:0, C6:0, C7:0, C8:0, C10:0, C10:1. b C12:0, iso-C13:0, anteiso-C13:0, C12:1 c9 + C13:0, iso-C14:0, C14:0, iso-C15:0, C14:1 t9, anteiso-C15:0,C14:1 c9, C15:0, iso-C16:0, C16:0, iso-C17:0, C16:1 t9, anteiso-C17:0, C16:1 c9.cC4:0, C5:0, C6:0, C7:0, C8:0, C10:0, C12:0, branched-chain FA, C14:0, C15:0,C16:0, C17:0, C18:0, C19:0, C20:0, C22:0. d (C12:0 + (4 � C14:0) + C16:0)/unsaturated FA. e C17:0, iso-C18:0, C17:1 t10, anteiso-C18:0, C18:0, C18:1 FA,C19:0, C18:2 FA, C20:0, C20:1 t11, C18:3 c6c9c12, C20:1 c5, C20:1 c9, C20:1 c11,C18:3 c9c12c15, C20:2 c11c14, C22:0, C20:3 c8c11c14, C20:3 c11c14c17, C20:4c5c8c11c14, C20:5 c5c8c11c14c17 (EPA), C22:5 c7c10c13c16c19 (DPA), C22:6c5c7c10c13c16c19 (DHA). f C18:1 t4, C18:1 t5, C18:1 t6 + C18:1 t7 + C18:1 t8,C18:1 t9, C18:1 t10 + C18:1 t11, C18:1 t12, C18:1 t13 + C18:1 t14 + C18:1 c6 +C18:1 c7 + C18:1 c8, C18:1 c9, C18:1 c11, C18:1 c12, C18:1 c13, C18:1 t16 + C18:1c14. g C18:2 t,tNMID, C18:2 t9t12, C18:2 c9t13 + C18:2 t8c12, C18:2 c9t12 + C18:2c,cMID + C18:2 t8c13, C18:2 t11c15 + C18:2 t9c12, C18:2 c9c12, C18:2 c9c15,C18:2 c9t11 + C18:2 t8c10 + C18:2 t7c9, C18:2 t11c13 + C18:2 c9c11, C18:2 t9t11.hC10:1, C14:1 t9, C14:1 c9, C16:1 t9, C16:1 c9, C17:1 t10, C18:1 FA, C20:1 t11,C20:1 c5, C20:1 c9, C20:1 c11, C18:2 FA, C18:3 c6c9c12, C18:3 c9c12c15, C20:2c11c14, C20:3 c8c11c14, C20:3 c11c14c17, C20:4 c5c8c11c14, C20:5c5c8c11c14c17 (EPA), C22:5 c7c10c13c16c19 (DPA), C22:6 c5c7c10c13c16c19(DHA). i C10:1, C14:1 t9, C14:1 c9, C16:1 t9, C16:1 c9, C17:1 t10, C18:1 FA, C20:1t11, C20:1 c5, C20:1 c9, C20:1 c11. j C18:2 FA, C18:3 c6c9c12, C18:3 c9c12c15,C20:2 c11c14, C20:3 c8c11c14, C20:3 c11c14c17, C20:4 c5c8c11c14, C20:5c5c8c11c14c17 (EPA), C22:5 c7c10c13c16c19 (DPA), C22:6 c5c7c10c13c16c19(DHA). k C18:1 t4, C18:1 t5, C18:1 t6 + C18:1 t7 + C18:1 t8, C18:1 t9, C18:1 t10 +C18:1 t11, C18:1 t12, C18:1 t13 + C18:1 t14 + C18:1 c6 + C18:1 c7 + C18:1 c8.l C18:2 c9t11 + C18:2 t8c10 +C18:2 t7c9, C18:2 t11c13 +C18:2 c9c11, C18:2 t9t11.m C14:1 t9, C16:1 t9, C17:1 t10, C20:1 t11, trans-C18:1 FA, C18:2 t,tNMID, C18:2t9t12, C18:2 c9t13 + C18:2 t8c12, C18:2 c9t12 + C18:2 c,cMID + C18:2 t8c13, C18:2t11c15 + C18:2 t9c12. n iso-C13:0, anteiso-C13:0, iso-C14:0, iso-C15:0, anteiso-C15:0, iso-C16:0, iso-C17:0, anteiso-C17:0, iso-C18:0, anteiso-C18:0. o C18:2t11c15 + C18:2 t9c12, C18:2 c9c15, C18:3 c9c12c15, C20:3 c11c14c17, C20:5c5c8c11c14c17 (EPA), C22:5 c7c10c13c16c19 (DPA), C22:6 c5c7c10c13c16c19(DHA). p C18:1 t12, C18:1 c12, C18:2 t9t12, C18:2 c9t12 + C18:2 c,cMID + C18:2t8c13, C18:2 c9c12, C18:3 c6c9c12, C20:2 c11c14, C20:3 c8c11c14, C20:4c5c8c11c14. c, cis; t, trans; NMID, non-methylene-interrupted diene; MID, methy-lene interrupted diene.


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greater uptake and secretion of dietary and ruminally derivedfatty acids. These fatty acids would compete for esterificationwith SCFA synthesized in the mammary gland, leading to afeedback inhibition of the two lipogenic enzymes. High levels ofLCFA have also a direct inhibitory effect on acetyl CoA carbox-ylase as reported by Chilliard et al. (6 ).

Individual Fatty Acids.Mean contents of individual fatty acidsin winter and spring cheeses are shown in Table 3. Compared tocheeses made in winter, cheeses made in spring had significantly(P e 0.05) lower contents of butyric (C4:0), caproic (C6:0),caprylic (C8:0), capric (C10:0), lauric (C12:0), myristic (C14:0),and palmitic (C16:0) acids, which accounted for 84 and 78.6% ofthe total SFA content in winter and spring cheeses, respectively.The content of linoleic acid (C18:2 c9c12) also decreased (P e0.05) in spring cheeses (11.7% lower than in winter) (Table 3).Conversely, iso-C17:0 and most anteiso-BCFA, stearic acid(C18:0), oleic acid (C18:1 c9), most C18:1 FA including trans-vaccenic acid (TVA, C18:1 t11), and most C18:2 FA includingpredominant CLA isomers and docosahexaenoic acid (DHA,C22:6 c5c7c10c13c16c19) presented higher concentrations (P e0.05) in spring cheeses than those found in winter cheeses. Nosignificant differences (P > 0.05) were observed for the concen-trations of most iso-BCFA, most long-chain n-6 FA, R-linolenicacid (C18:3 c9c12c15), and other long-chain n-3 FA such asC20:3c11c14c17, eicosapentaenoic acid (EPA, C20:5 c5c8c11c14c17),and docosapentaenoic acid (DPA, C22:5 c7c10c13c16c19)(Table 3).

Fresh pasture is the main source of R-linolenic acid (7, 14).Many authors have reported higher concentrations of this fattyacid in milk from grazing animals than in milk from animals fedconcentrate and conserved forages in stall (11, 15). Althoughhigher values of this fatty acid would have been valuable from anutritional point of view, no significant increase was observed inthe present study for this fatty acid in spring cheeses despite thepresumably higher intake of R-linolenic acid by grazing flocks.Doreau et al. (24 ) reported extensive ruminal biohydrogenationrates for unsaturated fatty acids, almost complete for R-linolenicacid and between 60 and 95% for linoleic acid. Kucuk et al. (25 )observed a linear increase in the biohydrogenation rate of oleic,linoleic, and R-linolenic acids as forage level in the diet increased,being much more extensive for linoleic and R-linolenic (around90-96%) than for oleic acid. In 1966 Wilde and Dowson (26 )described the biohydrogenation pathway of R-linolenic acid(C18:3 c9c12c15) that comprised a first isomerization step toC18:3 c9t11c15, followed by the reduction of the double bonds atpositions 9, 15, and 11, yielding C18:2 t11c15, C18:1 t11, andC18:0, in this order. This could explain the fact that theR-linolenic acid content remained stable in bothwinter and springcheeses and the accumulation in spring cheeses of stearicacid (C18:0) and other biohydrogenation intermediates, such asC18:2 t11c15 + C18:2 t9c12 and trans-C18:1 FA, especiallyC18:1 t10 + C18:1 t11. This last peak was 2.4 times higher incheesemade frommilk of pasture-fed ewes than in cheesemade inwinter (Table 3). Indeed, in a study conducted ondairy farmswithdifferentiated winter and spring feeding managements similar tothose presented in this paper (27 ), the strong increase of TVA(C18:1 t11) and C18:2 t11c15 and the modest increase ofR-linolenic acid (C18:3 c9c12c15) in spring cheeses was attributedto the differences in ruminal biohydrogenation activity. Collombet al. (28 ) also found higher levels of C18:1 t10 + t11 and C18:2t11c15 + t9c12 in milk from organic farming, in which animalswere fed lower amounts of concentrate and higher levels of feedgrasses, than in conventional integrated farming. In addition tothis, because the R-linolenic acid content of fresh grass dependson environmental factors such as rainfall and light exposure and

the maturity stage of green plants, as well as grass variety, it isunderstandable that pasture does not always increase the percen-tage of R-linolenic acid in milk fat (4, 6, 7).

Another major microbial transformation in the rumen is thesynthesis of odd- and branched-chain fatty acids, which areimportant components of microbial lipids with potential antic-ancer activity and are not present in feeds (29 ). Amylolyticbacteria show low levels of BCFA compared to cellulolyticbacteria, which have higher content of iso- and anteiso-FA (8 ).Part-time grazing systems adopted by sheepherders in the springentailed an increase in forage/concentrate ratio and a presumablyhigher dietary crude fiber intake that generally promotes thecellulolytic bacteria in the rumen (8 ). This is in good agreementwith the results reported in this work because predominantBCFA, which were anteiso-C15:0 and iso- and anteiso-C17:0,had significantly higher concentrations in spring when fresh grasswas present in the diet (Table 3).

Only a few studies have reported the concentrations of fattyacids of 20 carbon atoms or longer inmilk fat (28, 30) and sheep’smilk cheese (4 ). Among them, n-3 FA, specifically DHA andEPA, are the most interesting ones because they can exertantithrombotic and antiarrhythmic properties (31 ), and DHAis considered to be essential for the development andmaintenanceof the brain, retina, and nerves (32 ). Humans convert very littlelinoleic acid toEPAandDHA.Therefore these fatty acids have tobe supplied through the diet. Although cheeses from pasture-fedewes had a significantly (P e 0.05) higher content of DHA thanthose fromwinter feeding, bothEPAandDHA levels in thisworkwere slightly lower than those reported by Nudda et al. (4 ).Overall, EPA and DHA constituted 0.089% and 0.095% of thetotal fatty acids in winter and spring cheeses, respectively(Table 3). However, these values are very far from those reportedfor ruminant milk fat when fish oil supplements were used in thediet (6 ).

trans- Fatty Acids without CLA. trans-FA content of springcheeses doubled as a result of pasture-based spring feeding.Quantitatively, trans-C18:1 FA was the most important group,comprising 2.56%of total fatty acids inwinter cheeses and 4.94%in spring cheeses (Table 2). The concentration of each trans-FApeak was always significantly (P e 0.05) higher in spring cheesesthan in winter cheeses (Table 3). The content of trans-FA in thecheeses and the proportions of different trans-C18:1 FA isomerswere close to the ranges published byGoudjil et al. (33 ) for ewe0smilk fat, except for elaidic acid (C18:1 t9) and C18:1 t12, whichwere higher in this work. As mentioned earlier, the greatestincrease was observed for the C18:1 t10 + C18:1 t11 peak,accounting for around half of the total trans-C18:1 FA (44.7and 54.4% inwinter and spring cheeses, respectively). Although itwas not possible to resolve the compounds of this peak, based onthe published work about the accumulation of TVA (C18:1 t11)produced during the fermentation of PUFA in the rumen, asdiscussed above, it could be suggested that it is likely to beresponsible for the great increase of this peak in spring cheeses(Table 3).

The distribution of trans-C18:1 FA isomers could be of greatnutritional concern, because avoidance of dairy products isfrequently recommended for people who wish to limit theirtrans-fat intake. Although a high intake of trans-MUFA hasbeen associated with coronary heart disease risk and myocardialinfarction, trans-FA fromdairy products and those frompartiallyhydrogenated vegetable oils seem to have different effects on thatrisk (34 ).Most hydrogenated vegetable oils are enriched in C18:1t9 and C18:1 t10, elaidic acid (trans-9 isomer) being the mostwidely studied in regard to coronary heart disease risk. On thecontrary, TVA (C18:1 t11), the main natural isomer in dairy


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Table 3. Concentration (Grams per 100 g of Fat, Mean ( Standard Deviation) of Individual Fatty Acids in Winter and Spring Cheesesa

winter spring

significantly (P e 0.05) higher in winter

butyric acid C4:0 3.100( 0.202 2.750( 0.165

caproic acid C6:0 2.694( 0.115 2.169( 0.252

caprylic acid C8:0 2.722( 0.186 2.071( 0.359

capric acid C10:0 8.340( 0.739 6.149( 1.391

lauric acid C12:0 4.703( 0.413 3.642( 0.998

myristic acid C14:0 10.009( 0.471 9.263( 0.965

palmitic acid C16:0 23.426( 1.486 20.990( 1.501

R-linoleic acid C18:2 c9c12 2.130( 0.328 1.876( 0.189

t11-eicosenoic acid C20:1 t11 0.066 ( 0.012 0.057( 0.011

c11-eicosenoic acid C20:1 c11 0.046( 0.009 0.052 ( 0.009


anteiso-pentadecanoic acid anteiso-C15:0 0.402( 0.036 0.480( 0.051

myristoleic acid C14:1 c9 0.133( 0.015 0.193( 0.051

iso-heptadecanoic acid iso-C17:0 0.324( 0.031 0.393( 0.033

palmitelaidic acid C16:1 t9 0.061( 0.017 0.163 ( 0.061

anteiso-heptadecanoic acid anteiso-C17:0 0.379( 0.034 0.427( 0.056

palmitoleic acid C16:1 c9 0.595( 0.073 0.804 ( 0.143

t10-heptadecenoic acid C17:1 t10 0.013 ( 0.001 0.016( 0.006

anteiso-octadecanoic acid anteiso-C18:0 0.016( 0.006 0.028( 0.010

stearic acid C18:0 6.885( 0.967 8.869( 2.008

t4-octadecenoic acid C18:1 t4 0.020( 0.005 0.027( 0.009

t5-octadecenoic acid C18:1 t5 0.013( 0.002 0.018( 0.007

unresolved 1 C18:1 t6-8 0.108( 0.028 0.169( 0.055

elaidic acid C18:1 t9 0.174 ( 0.018 0.238( 0.042

unresolved 2 C18:1 t10 + t11 (TVA) 0.976( 0.304 2.329( 0.969

t12-octadecenoic acid C18:1 t12 0.203( 0.048 0.314 ( 0.055

unresolved 3 C18:1 t13-14 + c6-8 0.446( 0.083 0.781( 0.238

oleic acid C18:1 c9 11.550( 1.245 14.814( 2.618

vaccenic acid C18:1 c11 0.434( 0.056 0.541( 0.078

c13-octadecenoic acid C18:1 c13 0.061( 0.009 0.086( 0.014

unresolved 4 C18:1 t16 + c14 0.248( 0.039 0.404( 0.052

t,t-NMID-octadecadienoic acid ΣC18:2 t,t-NMID 0.043( 0.009 0.101 ( 0.029

unresolved 5 C18:2 c9t13 + t8c12 0.167( 0.026 0.330( 0.100

unresolved 6 C18:2 c9t12 + c,c-MID + t8c13 0.216( 0.024 0.332( 0.049

unresolved 7 C18:2 t11c15 + t9c12 0.078( 0.017 0.300( 0.176

c9,c15-octadecadienoic acid C18:2 c9c15 0.032( 0.005 0.043( 0.008

gadoleic acid C20:1 c9 0.024( 0.003 0.033( 0.007

unresolved 8 C18:2 c9t11 + t8c10 + t7c9 0.357( 0.123 0.913( 0.257

unresolved 9 C18:2 t11c13 + c9c11 0.013( 0.003 0.034( 0.011

behenic acid C22:0 0.041( 0.007 0.083( 0.018

docosahexaenoic acid (DHA) C22:6 c5c7c10c13c16c19 0.030( 0.006 0.036 ( 0.007


valeric acid C5:0 0.034( 0.009 0.034( 0.004

enanthic acid C7:0 0.035( 0.006 0.028( 0.012

caproleic acid C10:1 0.327( 0.043 0.286( 0.069

iso-tridecanoic acid iso-C13:0 0.030( 0.031 0.026 ( 0.006

anteiso-tridecanoic acid anteiso-C13:0 0.041( 0.006 0.045( 0.014

unresolved 10 C12:1 c11 + C13:0 0.146( 0.023 0.134 ( 0.046

myristelaidic acid iso-C14:0 0.111( 0.014 0.111( 0.014

iso-pentadecanoic acid iso-C15:0 0.220( 0.033 0.257( 0.053

t9-tetradecenoic acid C14:1 t9 0.010( 0.001 0.011( 0.002

pentadecanoic acid C15:0 0.896( 0.085 0.937( 0.992

iso-hexadecanoic acid iso-C16:0 0.260( 0.019 0.261 ( 0.024

margaric acid C17:0 0.488( 0.065 0.471( 0.045

iso-octadecanoic acid iso-C18:0 0.047( 0.009 0.052( 0.010

c12-octadecenoic acid C18:1 c12 0.252( 0.048 0.255 ( 0.035

nonadecanoic acid C19:0 0.102( 0.013 0.087( 0.016

linoelaidic acid C18:2 t9t12 0.014( 0.004 0.029( 0.027

arachidic acid C20:0 0.183( 0.028 0.216( 0.041

γ-linolenic acid C18:3 c6c9c12 0.015( 0.002 0.015( 0.002

c5-eicosenoic acid C20:1 c5 0.010( 0.001 0.012 ( 0.003

R-linolenic acid C18:3 c9c12c15 0.647( 0.112 0.656( 0.141


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products and presumably in the studied cheeses as well, plays acrucial role as precursor of rumenic acid (RA, CLA c9t11), whichis the isomer generally credited with anticarcinogenic and anti-atherogenic activities (35 ). Furthermore, Kuhnt et al. (36 ) statedthat approximately one-fourth of dietary TVAwas endogenouslyconverted to RA by humans, suggesting that TVA should betaken into account when the total CLA supply in human diet isdetermined.

CLA Isomers. Average values of individual CLA isomerconcentrations for winter and spring cheeses are displayed inTable 4. As a result of taking sheep out to pastures, CLA contentin spring cheeses underwent a 2.5-fold increase. The concentra-tion of the quantitatively main CLA isomers was significantlyhigher in spring cheeses than in winter cheeses. RA (CLA c9t11)was the predominant CLA isomer, followed by CLA t7c9. This isconsistent with the relative importance of the endogenous synth-esis by theΔ9-desaturase ofRA fromTVA, and, to a lesser extent,of CLA t7c9 from C18:1 t7 as suggested by Chilliard et al. (6 ).Several authors have reported a positive association betweenfresh pasture feeding and CLA t11t13 and CLA t11c13,which could be released by biohydrogenation of R-linolenic acid(6, 27, 28).

Principal Component Analysis. PCA was applied to feedingmanagement variables (concentrate supply and fresh pasture

intake), atherogenicity index, and selected FA groups (SCFA,MCFA, LCFA, SFA, C18:1 FA, C18:2 FA, CLA, trans-FA,trans-C18:1 FA, and n-6 FA). Figure 1 depicts variable loadingsand cheese sample scores in the two-dimensional coordinatesystem defined by PC1 and PC2. These two PCs accounting for84.2% of the total variance described the variation of FAcomposition of cheeses elaborated in winter and spring undertwo clearly differentiated feedingmanagement practices (Table 1).

Feed variables showed high loadings (g|0.72|) with PC1,although the correlation value was positive for concentratesupply and negative for fresh pasture intake. SCFA, MCFA,SFA, and atherogenicity index had high positive loadings (g0.80)with PC1, whereas LCFA, C18:1 FA, and CLA showed negativeloadings (g|0.63|) with this factor (Figure 1). Therefore, concen-trate supply was positively associated with the increment ofsaturated FA content, whereas fresh pasture intake was respon-sible for the increment of unsaturated FA content in cheese. Thisfactor was defined as “feeding management factor”. C18:2 FA,CLA, trans-C18:1 FA, trans-FA, and n-6 FA showed highpositive loadings (g0.71) with PC2. Pasture intake also contrib-uted to this component with a positive loading of 0.52. As has

Table 3. Continued

winter spring

t9,t11-octadecadienoic acid C18:2 t9t11 0.034( 0.017 0.042( 0.020

eicosadienoic acid C20:2 c11c14 0.019( 0.003 0.019 ( 0.003

homo-γ-linolenic acid C20:3 c8c11c14 0.022( 0.004 0.022( 0.002

c8,c11,c14-eicosatrienoic acid C20:3 c11c14c17 0.011( 0.001 0.011( 0.001

arachidonic acid C20:4 c5c8c11c14 0.127( 0.017 0.1129( 0.013

eicosapentaenoic acid (EPA) C20:5 c5c8c11c14c17 0.046( 0.006 0.047 ( 0.007

docosapentaenoic acid (DPA) C22:5 c7c10c13c16c19 0.097( 0.026 0.103( 0.015

a c, cis; t, trans; TVA, trans-vaccenic acid; NMID, non-methylene-interrupted diene; MID, methylene-interrupted diene. Unresolved peaks: 1, petroselaidic acid +t7-octadecenoic acid + t8-octadecenoic acid; 2, t10-octadecenoic acid + trans-vaccenic acid; 3, t13-octadecenoic acid + t14-octadecenoic acid + c6-octadecenoic acid +c7-octadecenoic acid + c8-octadecenoic acid; 4, t16-octadecenoic acid + c14-octadecenoic acid; 5, c9,t13-octadecadienoic acid + t8,c12-octadecadienoic acid; 6, c9,t12-octadienoic acid + c,c-MID-octadecadienoic acid + t8,c13-octadecadienoic acid; 7, t11,c15-octadecadienoic acid + t9,c12-octadecadienoic acid; 8, rumenic acid + t8,c10-octadecadienoic acid + t7,c9-octadecadienoic acid; 9, t11,c13-octadecadienoic acid + c9,c11-octadecadienoic acid; 10, c11-dodecenoic acid + tridecanoic acid.

Table 4. Concentrations (Milligrams per Gram of Fat, Mean ( StandardDeviation) of Conjugated Linoleic Acid (CLA) Isomers in Winter and SpringCheeses

winter spring


C18:2 t7,c9 0.26( 0.08 0.43( 0.13

C18:2 t12,t14 0.09( 0.02 0.20( 0.04

C18:2 t11,t13 0.10( 0.03 0.35( 0.09

C18:2 t9,t11 0.13( 0.02 0.21( 0.05

C18:2 c,t/t,c12, 14 0.05( 0.02 0.10( 0.03

C18:2 t11,c13 0.08( 0.02 0.29( 0.10

C18:2 c9,t11 3.15( 1.13 8.44( 2.41

C18:2 t8,c10 0.15( 0.04 0.26( 0.06

CLA t,ta 0.48( 0.08 0.96( 0.18

CLA c,t/t,cb 3.48( 1.20 9.16( 2.54

CLA (total) 3.96( 1.25 10.11( 2.61


C18:2 t10,t12 0.03( 0.01 0.04( 0.01

C18:2 t8,t10 0.02( 0.01 0.04( 0.05

C18:2 t7,t9 0.06( 0.02 0.06( 0.02

C18:2 t6,t8 0.04( 0.02 0.04( 0.01

C18:2 c11,t13 0.01( 0.01 0.03( 0.04

C18:2 t10,c12 0.04( 0.01 0.04( 0.02

a t,t, all-trans-CLA. b c,t/t,c, CLA containing cis- and trans-double bonds.Figure 1. Plot depicting variable loadings and cheese sample distributionin the two-dimensional coordinate system defined by PC1 and PC2: wintercheeses (b); spring cheeses (O). CLA, conjugated linoleic acid; FA, fattyacids; LCFA, long-chain fatty acids; MCFA, medium-chain fatty acids;SCFA, short-chain fatty acids; SFA, saturated fatty acids.


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been discussed before, these groups of FA are involved inbiohydrogenation processes, which may be altered by the pre-sence of fresh grass in the diet (6, 25). Accordingly, this compo-nent was defined as “biohydrogenation factor”.

Cheese samples from winter or spring season were clearlydistinguishedby the combinationof the feedingmanagement factor(PC1) and the biohydrogenation factor (PC2) (Figure 1). Sampleslocated in the lower right-hand area of the graph (winter cheeses)presented a higher content of saturated fat, whereas sampleslocated in the upper left-hand area (spring cheeses) had a highercontent of unsaturated fat. The variability observed in the scoreswithin each season was most likely due to small differences in flockmanagement among the farmhouses collaborating in this work.

In summary, cheeses elaborated with milk from ewes fed freshpasture contained less saturated and atherogenic fat and hadhigher levels of nutritionally desirable fatty acids, such as RA,TVA, DHA, and BCFA, in comparison with cheeses elaboratedwith milk from the same ewes in intensive farming systems basedon concentrate and conserved forages. Because per capita cheeseconsumption in Europe is ∼18.5 kg per year (37 ), the contribu-tion of cheese fat to human diet is significant. The region in whichthis study took place is located within the Mediterranean coun-tries, where ewe0s cheese consumption is of great importance (1 ).Thus, data on cheese fat composition reported in this work willcontribute to provide scientific evidence on the advantages ofpasture-based systems to obtain high-quality products and toencourage sheepherders to improve and continue part-time graz-ing management.

ACKNOWLEDGMENT

We thank local farmers for supplying cheese samples andtechnical information on their farming and feeding systems andtheRegulatory Board of PDO Idiazabal cheese andArtzai-Gaztasheepherders association for technical support. We also thankMonika Spahni, PatrickMalke, and Florian Hof for their carefultechnical assistance.

LITERATURE CITED

(1) Freitas, C.; Malcata, F. X. Microbiology and biochemistry ofcheeses with app�elation d0Origine Proteg�ee and manufactured inthe Iberian peninsula. J. Dairy Sci. 1999, 83, 584–602.

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Received for Review February 9, 2009. Revised manuscript received April

7, 2009. Accepted April 10, 2009. This work was supported by grants from

the Universidad del Pa�is Vasco/Euskal Herriko Unibertsitatea (Leioa,

Spain) (UNESCO Cathedra/05102) and the Instituto Nacional de

Investigaci�on y Tecnolog�ia Agraria y Alimentaria (Madrid, Spain)

(RTA 2006-00100-C02-02). E.A. acknowledges a predoctoral

fellowship from the Gobierno Vasco/Eusko Jaurlaritza.


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121

Manuscrito 6. Volatile composition and aroma-active compounds of

farmhouse Idiazabal cheese made in winter and spring

En prensa, International Dairy Journal

DOI: 10.1016/j.idairyj.2010.02.012


141

Accepted Manuscript

Title: Volatile composition and aroma-active compounds of farmhouse Idiazabalcheese made in winter and spring

Authors: Eunate Abilleira, Hedwig Schlichtherle-Cerny, Mailo Virto, Mertxe deRenobales, Luis Javier R. Barron

PII: S0958-6946(10)00053-1

DOI: 10.1016/j.idairyj.2010.02.012

Reference: INDA 3093

To appear in: International Dairy Journal

Received Date: 7 September 2009

Revised Date: 24 February 2010

Accepted Date: 25 February 2010

Please cite this article as: Abilleira, E., Schlichtherle-Cerny, H., Virto, M., de Renobales, M., Barron, L.J.Volatile composition and aroma-active compounds of farmhouse Idiazabal cheese made in winter andspring, International Dairy Journal (2010), doi: 10.1016/j.idairyj.2010.02.012

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service toour customers we are providing this early version of the manuscript. The manuscript will undergocopyediting, typesetting, and review of the resulting proof before it is published in its final form. Pleasenote that during the production process errors may be discovered which could affect the content, and alllegal disclaimers that apply to the journal pertain.


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Volatile composition and aroma-active compounds of farmhouse 1

Idiazabal cheese made in winter and spring 2

3

4

5

6

Eunate Abilleiraa, Hedwig Schlichtherle-Cernyb, Mailo Virtoc, Mertxe de Renobalesc,, 7

Luis Javier R. Barrona*8

9

10

11

aTecnología de Alimentos, Facultad de Farmacia, Universidad del País Vasco/Euskal 12

Herriko Unibertsitatea, Paseo de la Universidad 7, 01006 Vitoria-Gasteiz, Spain 13

bAgroscope Liebefeld-Poiseux Research Station ALP, Schwarzenburgstrasse 161, 3003 14

Bern, Switzerland 15

cBioquímica y Biología Molecular, Facultad de Farmacia, Universidad del País 16

Vasco/Euskal Herriko Unibertsitatea, Paseo de la Universidad 7, 01006 Vitoria-17

Gasteiz, Spain 18

19

20

* Corresponding author. Tel.: + 34 945 013082; fax: + 34 945 013014. 21 E-mail address: [email protected] (L. J. R. Barron) 22


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______________________________________________________________________23

Abstract 24

25

Volatile composition and aroma compounds of Idiazabal PDO cheeses made in 26

winter and spring were compared. In these seasons flock management differs: 27

concentrate and conserved forages are fed in winter whereas a part-time grazing system 28

is used in spring. Commercial cheeses from ten farmhouses were analysed during 29

ripening. Acids, carbonyl compounds, esters, and alcohols were the main volatiles in 30

both seasons. The shift from winter to spring management led to a higher proportion of 31

esters and alcohols, and a lower proportion of ketones and aldehydes. More than 30 32

odour-active compounds were identified by olfactometry with butanoic acid, ethyl 33

butanoate, ethyl hexanoate and 2-heptanone being the principal ones. Coinciding with 34

fresh pasture grazing in spring, the odour impact ratios of esters and alcohols increased, 35

indicating that spring cheeses might have more intense fruity and sweet overtones in 36

comparison with winter cheeses. 37

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1. Introduction 39

40

Idiazabal cheese is a raw ewesʼ milk cheese regulated under the Idiazabal 41

Protected Denomination of Origin (PDO) (European Communities, 1996). Idiazabal 42

production is seasonal during winter and spring according to the lactation period of the 43

ewes (Perea et al., 2000). Seasonal differences are a combination of lactation, diet, and 44

environmental factors (Hickey et al., 2006). In this particular case, feeding is a factor of 45

paramount importance affecting the seasonal variability because two clearly 46

differentiated feeding strategies are employed in winter and spring. In winter, due to 47

pasture shortage, ewes are fed concentrate and conserved forages indoors. In spring, 48

flocks graze on fresh pastures and supplemental feeds are given only if they are needed 49

to satisfy the nutritional needs of the sheep (Ruiz & Oregui, 1998). In this regard, the 50

PDO Idiazabal Cheese Regulation (Ministerio de Agricultura, Pesca y Alimentación, 51

1993) only mentions that the feeding practices should follow the traditional 52

management using the best pastures available within the protected area to obtain milk 53

with the typical features to obtain the Idiazabal cheese. 54

Anecdotal evidences of the benefits of spring and summer grasslands on the 55

flavour of dairy products has existed since 1951 (Wigan, 1951). Volatile constituents 56

seem to be transferred from the blood to the milk through inhaled air, rumen gases or by 57

direct absorption from the digestive tract (Shipe et al., 1962). A good review on the 58

topic was written by Coulon et al. (2004), who observed major differences in the 59

sensory characteristics between cheeses made from cows fed indoor winter diets versus 60

pasture in spring. They attributed this effect in part to the presence of specific molecules 61

in the raw material directly derived from feeding. Carpino et al. (2004a,b) concluded 62

that consumption of native plants from fresh pasture resulted in cheeses with higher 63


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floral and green/herbaceous odour notes than cheeses from total mixed ration. They 64

reported that pasture cheeses were richer in odour-active compounds and that some of 65

the compounds had their origin in the grazed plants. However, Bendall (2001) linked 66

the flavour differences of milk from cows fed a total mixed ration or pasture to the 67

concentration differences of a set of compounds rather than the occurrence of 68

compounds uniquely associated with a particular feed. 69

The influence of different types of pastures on milk and cheese volatile 70

composition has been studied (Bugaud, Buchin, Hauwuy, & Coulon, 2001; Povolo, 71

Contarini, Mele, & Secchiari, 2007), but usually with the aim of detecting useful 72

markers to link the product to its origin. A few studies have reported seasonal variations 73

of volatile composition of ewesʼ raw milk cheeses, but information about the feeding 74

management was not provided. In consequence, seasonal variation was interpreted as 75

the sum of uncontrolled factors regarding lactation stage, flock management or climate 76

conditions (Carbonell, Núñez, & Fernández-García, 2002; Fedele, Rubino, Claps, Sepe, 77

& Morone, 2005; Fernández-García, Carbonell, Gaya, & Núñez, 2004a; Fernández-78

García, Serrano, & Núñez, 2002). 79

Volatile analysis is one of the most important methods in quality evaluation of 80

food and it has been applied to dairy products (Povolo et al., 2007; Preininger & 81

Grosch, 1994). Characterization of volatile composition and sensory profile of Idiazabal 82

PDO cheese has been previously published (Barron et al., 2005a,b). Together with the 83

above mentioned feeding factors that mainly affect the raw material quality, other 84

technological factors such as starter culture or rennet type used for Idiazabal 85

cheesemaking play a decisive role in generating volatile compounds and, in short, in 86

defining the characteristic aroma of the cheese (Barron et al., 2007; Bustamante et al., 87

2003; Virto et al., 2003). Cheese flavour results from a mixture of hundreds of 88


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compounds released during ripening (McSweeney & Sousa, 2000). Only a small 89

fraction of these compounds are mainly responsible for cheese flavour. The difficulty is 90

to identify the principal contributors to flavour and aroma. For that purpose, gas 91

chromatography-olfactometry (GC-O) provides a valuable tool for investigating the 92

odorant pattern in terms of odour descriptors and activity (Curioni & Bosset, 2002). To 93

the best of our knowledge, it is the first time that GC-O analysis has been applied to 94

Idiazabal cheese. 95

The aim of this work was to compare the Idiazabal cheese volatile profile in two 96

different farming systems associated with the season (winter-indoor versus spring part-97

time grazing) and identify changes in the aroma-active compounds of the cheeses due to 98

those two different seasonal managements. 99

100

2. Materials and methods 101

102

2.1. Cheese samples 103

104

Ten farmhouses, which manufacture Idiazabal PDO cheese with the milk from 105

their own flocks, were selected. All the flocks had the same seasonal lambing periods 106

lasting approximately 45 days and lactating periods that lasted 4 to 5 months. Each 107

flock had between 200 and 400 heads and were managed under similar feeding 108

strategies. Fodder in winter consisted of concentrate and conserved forages fed indoors, 109

whereas it was based on outdoor fresh pasture grazing, with little indoor 110

supplementation, in spring. Different formulations of commercially available 111

concentrates and forages were used in each farmhouse. Flocks grazed mainly in 112

cultivated private grasslands dominated by ryegrass (Lolium perenne) and white clover 113


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(Trifolium repens) and in other community-own grasslands with greater diversity of 114

grass species. Average fodder composition in each season is summarized in Table 1. 115

Cheeses were manufactured according to the specifications approved by the 116

Idiazabal PDO Regulatory Council (Ministerio de Agricultura, Pesca y Alimentación, 117

1993). The production method used for both winter and spring cheeses was as follows; 118

ewesʼ raw milk was heated in small vats (300-600 L) and a homo-fermentative starter 119

culture (Ezal MAO11, Rhône-Poulenc Texel, Dangé-St. Romain, France) was added at 120

the level recommended by the supplier when the milk reached 25 ºC. Adequate amount 121

of lamb rennet paste was added by each cheese-maker to coagulate the milk from 20 to 122

45 min at 28-32 ºC. All manufacturers produced their own lamb rennet paste by mixing 123

the minced stomachs of the lambs with salt according to the procedure described by 124

Bustamante et al. (2000). Data on coagulating and lipase activities of lamb rennet pastes 125

used for Idiazabal cheese have been previously reported (Bustamante et al., 2000; 126

Hernández et al., 2005; Virto et al., 2003). 127

Once the milk coagulated, the gel was milled into rice-sized grains, stirred and 128

heated to 36-37 ºC for 10 min. The whey was removed by pressing the curd grains in 129

the vat and then introduced in cheese moulds. Cheeses were pressed for 6-8 h and then 130

placed in saturated sodium chloride brine at 10-12 ºC for 16-24 h. Cheeses were then 131

ripened at 8-10 ºC and 80-85 % relative humidity for 2 months, and then at 5-6 ºC and 132

85-90 % relative humidity for another 4 months. Cheeses were cylindrically shaped, 12-133

18 cm high, and weighed approximately 1.5 kg. Previous studies did not find 134

differences in the gross composition of ripened Idiazabal cheeses made in winter and 135

spring, and reported the following average gross composition: percentage of dry matter 136

(DM) 68.21 ± 1.87; total fat percentage in DM, 52.06 ± 6.21; and total protein 137

percentage in DM, 34.81 ± 3.98 (Barron et al., 2005a). 138


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Cheeses made in winter (February and March) and late spring (end of May and 139

June) were collected from each farmhouse after 120 d and 180 d of ripening. On each 140

sampling day, two cheeses were randomly selected from the same vat. A total of 80 141

whole cheeses corresponding to 20 vats (10 farmhouses × 2 seasons × 2 ripening times 142

× 2 cheeses per vat) were collected. Cheeses were cut into sections of approximately 143

150-200 g, vacuum-packed and frozen at -20 ºC until analysis. 144

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2.2. Volatile compound analysis 146

147

Vacuum-packed cheese samples were thawed overnight at 4 ºC. Samples from 148

each of the cheeses from the same vat were grated and mixed for volatile extraction 149

after removal of the rind (1.5 cm). Four g of cheese were placed in 20 mL headspace 150

vials sealed with Teflon-lined silicone rubber septa. Eight mL of 0.1 mol L-1 phosphate-151

buffer was added to adjust the pH around 8 and ionize the free acids, to avoid their 152

release into the headspace, which might interfere with other chromatographic peaks. 153

The mixture was homogenized in the vial with a Polytron PT 10/35 equipped with a 154

PTA 7 generator (Kinematica AG, Lucerne, Switzerland) at 4000 rpm for 3 min.155

Volatile compounds were extracted from the headspace using a Combi PAL 156

Autosampler (CTC Analytics, Zwingen, Switzerland) with a 2 cm 157

Divinylbenzene/Carboxen/Polydimethylsiloxane 50/30 µm fibre (Supelco, Bellefonte, 158

PA, USA) for 45 min at 40 °C. Prior to extraction, samples were equilibrated at 40 ºC 159

for 15 min. This fibre was preferred because of its ability to extract a wide range of low- 160

to mid-molecular weight molecules (Carpino et al., 2004b). The volatiles were desorbed 161

at 260 ºC by automatically inserting the fibre into the injection port in splitless mode for 162

5 min. 163


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An Agilent 5890 Series II gas chromatograph (Agilent Technologies, 164

Wilmington, DE, USA), equipped with an HP-5MS capillary column (30 m × 0.25 mm 165

internal diameter × 0.25 µm film thickness; Agilent Technologies), was used for the 166

analysis with a MSD HP 5971A mass selective detector (Agilent Technologies). The 167

oven temperature was programmed at 38 ºC for 5 min, then increased at 4 ºC min-1 up to 168

250 ºC. Carrier gas was helium at a constant flow of 2.40 mL min-1. 169

The MSD operated in full scan mode at 1.4 scan s-1 (m/z 26-350), with 70 eV, 170

and an interface temperature of 280 ºC. Volatile compounds were identified by 171

comparing their mass spectra and linear retention indices (Van den Dool and Kratz, 172

1963) with authentic reference compounds and with the Wiley 138.L and 275.L mass 173

spectra libraries (John Wiley & Sons, Hoboken, JF, USA). LRI were calculated by 174

running a C5-C20 n-alkane series (Sigma-Aldrich, St. Louis, MI, USA) under the same 175

analytical conditions. Additionally, a new batch of samples was prepared and run in the 176

same chromatograph but equipped with a DB-FFAP capillary column (30 m × 0.25 mm 177

internal diameter × 0.25 µm film thickness; Agilent Technologies) to confirm the 178

identification of the volatile compounds obtained with the HP5-MS column. The 179

analyses were run under the same chromatographic conditions except for the oven 180

temperature program that was programmed at 40 ºC for 5 min, increased at a rate of 5 181

ºC min-1 up to 240 ºC and held for 5 min. The same n-alkane series and reference 182

compounds were also run using the DB-FFAP column to calculate the new LRI. 183

Peak absolute areas (arbitrary units) were calculated from the total ion current 184

(TIC). The detection limit (LOD) was established at twice the noise of the 185

chromatogram and below this area threshold peaks were marked as non detected (ND). 186

Analyses were conducted in duplicate and the repeatability of the method was tested by 187

analyzing the same cheese sample five times. Relative standard deviation ranged from 188


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2.66 % to 20.37 % using the same fibre unit. Although slightly high, this variability can 189

be acceptable for a HS method (Beltran et al., 2006). Results were expressed as 190

arbitrary area units and percentage of total area. The results were a semi-quantitative 191

approach because we aimed to make a relative comparison of the volatile profiles of 192

winter and spring cheeses. The limitations of HS-SPME make the calibration difficult 193

principally due to matrix effects and displacement and competition phenomena during 194

the adsorption onto the fibre (Cornu et al., 2001; Lord & Pawliszyn, 2000). 195

196

2.3. Olfactometric analysis 197

198

GC-O analysis was performed at the same conditions as above using an 199

olfactometric detector (Sniffer 9000 system, Brechbühler, Switzerland). The analysis of 200

the volatile compounds was carried out simultaneously, with MSD and olfactometric 201

detectors mounted in parallel and splitting the flow at the end of the capillary column 202

into two equal streams. 203

All GC-O analyses were carried out by the same sniffer, who described the 204

odours perceived in the effluent at the sniffing port and recorded the retention times 205

when they were perceived. Only 8 cheese samples were randomly selected to carry out 206

olfactory analyses (2 winter samples of 120 d, 2 winter samples of 180 d, 2 spring 207

samples of 120 d and 2 spring samples of 180 d). 208

To obtain a relative measure of the sensory intensity of each odour-active 209

compound detected by GC-O and estimate the contribution to the overall odour of the 210

cheese, Odour Impact Ratio (OIR) was defined. It was calculated as follows: OIR = 211

peak absolute area / (vial volume × odour threshold). These OIR values do not have a 212

quantitative character unlike the odour activity values (OAV) or similar concepts that 213


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result from the calculation of concentration to odour threshold ratios (Preininger & 214

Grosch, 1994). 215

216

2.4. Statistical analysis 217

218

Analysis of covariance (ANCOVA) was used to determine the presence of 219

significant differences (P ≤ 0.05) in the volatile composition between 180-day-old 220

cheeses from winter-feeding flocks and spring-feeding flocks. Mixed linear model was 221

used including volatile data of the 120-day-old cheeses as covariate, “season” as fixed 222

effect and “farm” as random effect. F-test of the “season” against the interaction term 223

“season*farm” was used to determine significant differences when the interaction term 224

was significant (P ≤ 0.05). The SPSS statistical package version 16.0 (SPSS Inc., 225

Chicago, IL, USA) was used for the statistical analysis. 226

227

3. Results and discussion 228

229

3.1. Volatile composition 230

231

Table 2 summarizes the average relative abundance of the main volatile 232

chemical families in winter and spring ripened Idiazabal cheeses. Individual volatile 233

compounds detected in the Idiazabal cheese samples are reported in Table 3. More than 234

80 volatile compounds were detected in the cheese samples. Esters constituted the 235

highest number of individual compounds (25) detected in the cheese samples followed 236

by alcohols (14), ketones (13), acids (10), hydrocarbons (10), aldehydes (6), and sulphur 237

compounds (2) (Table 3). These results were in agreement with previously reported data 238


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on volatile composition of Idiazabal cheese (Barron et al., 2005a; 2007). As it has been 239

reported, the predominant chemical family in the headspace of Idiazabal cheeses in both 240

seasons was that of the acids (Barron et al., 2005a). In the present work acids accounted 241

for 46.4 % and 41.9 % in winter and spring cheeses, respectively. The next groups, in 242

order of importance (area percentage), were ketones (27.2 %) and alcohols (12.5 %) in 243

winter cheeses, and alcohols (18.8 %) closely followed by esters and ketones (13.9 and 244

15.9 %, respectively) in spring cheeses. Hydrocarbons, aldehydes, sulphur compounds, 245

and other compounds were minor groups that together accounted for less than 10 % of 246

the total volatiles in both seasons (Table 2). 247

When comparing the mean percentages of the volatile compounds of winter and 248

spring cheeses, the interaction term “season*farm” was always statistically significant 249

(P ≤ 0.05) pointing out the crucial role of the sheepherder-manufacturer because slight 250

differences in the flock management, cheesemaking procedure or even location of the 251

farmhouse could have an impact in the development of the volatile composition of the 252

cheeses during ripening. In spite of the expected variability derived from the above 253

mentioned factors, seasonal differences were found in the volatile composition of winter 254

and spring cheeses. First of all, it must be pointed out that the main chemical family in 255

Idiazabal cheese samples, the free acids, did not vary (P > 0.05) from winter to spring. 256

As it will be discussed later, this result could be expected because, in the case of 257

Idiazabal cheese, the volatile acid release during ripening depends primarily on 258

technological factors (Virto et al., 2003). However, percentages of esters and alcohols 259

were significantly (P ≤ 0.05) higher in spring cheeses. Conversely, the proportion of 260

ketones and aldehydes decreased significantly (P ≤ 0.05) when flocks grazed on fresh 261

pastures in spring (Table 2). It could be that the reduction of carbonyl groups to yield 262

alcohols would have been favoured in spring cheeses. The higher alcohol availability 263


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would have promoted the generation of esters in cheeses from grazing flocks, because 264

alcohol concentration is a limiting factor in ester production (Liu, Holland, & Crow, 265

2004). 266

267

3.1.1. Esters268

Ethyl esters predominated in both seasons over the other alkyl esters accounting 269

for the 85.1 % of total esters in winter and 64.1 % in spring. Compared with winter 270

cheeses total abundance of ethyl esters increased significantly (P ≤ 0.001) in the 271

headspace of spring cheeses. The same behaviour was observed for total content of 272

methyl, propyl and branched-alkyl esters whereas that of butyl esters did not vary 273

significantly (P > 0.05) with the seasonal management shift (Table 3). With respect to 274

individual esters, ethyl, propyl and isobutyl esters of butanoic and hexanoic acids were 275

mostly responsible for the higher content of esters in the headspace of spring cheeses. It 276

was also remarkable that seven esters appeared exclusively in spring cheeses, in small 277

quantities, methyl butanoate being the most abundant among them (Table 3). Ethyl 278

hexanoate and ethyl butanoate were by far the most abundant esters in both seasons, 279

hence, it is not surprising that these compounds were perceived as intense odorants in 280

Idiazabal cheese as discussed later. 281

282

3.1.2. Alcohols283

Although the proportion of alcohols was higher (P ≤ 0.05) in spring than in 284

winter cheeses (Table 2), only the total abundance of primary alcohols significantly (P ≤285

0.05) increased (Table 3). Among the primary alcohols, only the abundance of 1-286

butanol increased (P ≤ 0.05) from indoor feeding season to part-time grazing season, 287

being 10-fold higher in spring than in winter cheeses (Table 3). Primary alcohols, such 288


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as 1-butanol may originate from the reduction of aldehydes (Marilley & Casey, 2004), 289

which is consistent with the absence of butanal in both winter and spring cheeses. Also, 290

remarkable that three alcohols, 1-nonanol, 2-nonanol and phenylethanol, were only 291

detected in spring cheeses in small quantities (Table 3). The compound 2-butanol was 292

the predominant alcohol both in winter and spring cheeses, accounting for 46.5 % and 293

47.2 % of total alcohols respectively. As it will be discussed later, this observation is 294

consistent with the fact that 2-butanone was the main ketone found in the cheeses (Table 295

3), because secondary alcohols are reduction products of methyl ketones, that are in turn 296

derived from free fatty acid catabolism (McSweeney & Sousa, 2000). 297

298

3.1.3. Carbonyl compounds 299

The decrease observed in the proportion of ketones in spring cheeses (Table 2) 300

was mainly due to the significantly (P ≤ 0.05) lower content of 2-pentanone, 2,3-301

butanedione (diacetyl) and 3-hydroxy-2-butanone (acetoin) in spring cheeses. Acetoin 302

was only detected in winter cheeses (Table 3). Major ketones were 2-butanone, 2-303

heptanone and 2-pentanone, accounting for 30.8 %, 20.4 % and 19.5 % of total ketones 304

in winter cheeses and 39 %, 25 % and 12.8 % in spring cheeses. 305

The slight, but significant (P ≤ 0.05), decrease in the percentage of aldehydes 306

from winter to spring (Table 2) was mainly due to the disappearance of 2-propenal in 307

spring cheeses which accounted for 28 % of the total aldehyde content in winter cheeses 308

(Table 3). This unsaturated aldehyde has been reported as one of the main aldehydes 309

identified in the volatile fraction of Spanish ewesʼ raw cheeses, and seasonal changes 310

have also been reported in these cheeses (Fernández-García et al. 2004a; Fernández-311

García, Gaya, Medina, & Núñez, 2004b). The principal aldehyde in both winter and 312

spring cheeses was 3-methylbutanal that represented the 62.8 % and 67.2 % of the total 313


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aldehydes in winter and spring cheeses, respectively. These values were not 314

significantly different (P > 0.05). 315

316

3.1.4. Acids 317

In the acids group, straight-chain fatty acids were the main components in both 318

winter and spring cheeses. Hexanoic acid was the most abundant (49.7 % in winter and 319

48.6 % in spring) followed by butanoic acid (23 % in winter and 24.3 % in spring). No 320

significant differences (P > 0.05) were found between the abundances of most 321

individual fatty acids in winter and in spring cheeses (Table 3). This was expected 322

because the free fatty acid content depends primarily on technological factors such as 323

the use of raw milk and the type of rennet employed for milk coagulation (Virto et al., 324

2003). Branched-chain fatty acids were minor components (less than 0.5 % of total 325

acids in both seasons) but the content of 3-methylbutanoic acid increased considerably 326

from winter to spring (Table 3). 327

328

3.1.5. Hydrocarbons and sulphur compounds 329

The percentage of alkanes, unsaturated hydrocarbons, sulphur compounds, and 330

other compounds did not change (P > 0.05) from winter to spring cheeses (Table 2). 331

Among hydrocarbons, 1,3-pentadiene was the predominant compound in both seasons 332

(93.3 % and 90 % of the total hydrocarbons in winter and spring cheeses, respectively). 333

Only the content of toluene and t-3-octene increased significantly (P ≤ 0.05) in spring 334

cheeses (Table 3). It has been reported that some hydrocarbons such as cis- and trans-335

isomers of octene could originate from oxidation of unsaturated fatty acids (Povolo et 336

al., 2007). Some authors suggested that aromatic hydrocarbons, such as toluene, may 337

come from the degradation of carotene present in fresh grass (Povolo et al., 2007; Ziino, 338


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Condurso, Romeo, Giuffrida, & Verzera, 2005). Also, terpenoids could be expected to 339

appear in higher number and abundance in spring than in winter cheeses due to fresh 340

grass grazing in spring (Bugaud et al., 2001; Carpino et al., 2004b); however, only 341

alpha-pinene was detected in very small quantities in winter cheeses. No homogeneous 342

pattern of seasonal effect was found for sulphur compounds in the cheese samples 343

studied (Table 3) as it has been reported by other authors (Fernández-García et al., 344

2004a; Izco and Torre, 2000; Virgili et al., 1994).345

346

3.2. Olfactometry 347

348

Table 4 shows the odour active compounds detected by GC-O in winter and 349

spring Idiazabal cheeses and their OIR values. Thirty aroma-active compounds were 350

identified by means of GC-O comprising esters (14), acids (6), ketones (4), alcohols (4), 351

aldehydes (1) and hydrocarbons (1), although only ten of them showed OIR values 352

greater than 1. The odour-active compounds were also classified into different odour 353

families as compiled by Barron et al. (2005a) (Table 4). Odour families which 354

comprised odour active compounds with OIR values greater than 1 were rancid, sweat, 355

fermented fruit, herb, stone or pip fruit and musty. Sensory descriptors related to the 356

animal odour family such as sour, rancid, sweaty, cheesy or sharp are typical sensory 357

attributes of aged cheeses with a high degree of lipolysis that, in the case of Idiazabal 358

cheese, is mainly due to the use of lamb rennet paste (Hernández et al., 2009). 359

Straight acids reported in Table 4 have very high odour thresholds except for 360

butanoic and hexanoic acids which were the dominant odorants contributing rancid and 361

sweaty odours to both winter and spring cheeses aroma. It is possible that their 362

contribution to the overall aroma profile (OIR values of 13 and 4-5 for butanoic and 363


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hexanoic acid, respectively) was underestimated in the present work because cheese 364

samples were suspended in a pH=8 buffer solution prior to volatile extraction which 365

could have reduced the release of these compounds into the headspace. As expected 366

from the results on Table 3, OIR values estimated for acids in winter and spring cheeses 367

were rather similar which indicated that the season did not change the contribution of 368

these compounds to Idiazabal cheese aroma. 369

Ethyl esters, particularly ethyl butanoate and ethyl hexanoate, showed the 370

highest OIR values and they were described as fruity odorants (Table 4). Ethyl esters of 371

short-chain fatty acids have been reported as aroma-active compounds in different types 372

of cheeses providing fruity and sweet notes or minimising the sharpness imparted by 373

short-chain free fatty acids (Curioni & Bosset, 2002; Liu et al., 2004). As a result of the 374

shift to pasture based feeding management in spring, OIR value of ethyl butanoate 375

doubled and that of ethyl hexanoate was 3-fold higher. Also, the odour impact of ethyl 376

valerate (OIR value 16) only contributed to the aroma profile of spring cheeses (Tables 377

3 and 4). Aroma-active alcohols detected with OIR values greater than 1 were 2-butanol 378

and 2-heptanol, and spring feeding enhanced the presence of these aroma-active 379

alcohols in the cheese volatile fraction (Table 4). Therefore, the results obtained suggest 380

that spring cheeses might have more intense fruity, sweet and green overtones in 381

comparison with winter cheeses. 382

Methyl ketones were the only ketones detected by the. Noteworthy was the OIR 383

value of 2-heptanone (48 and 37 in winter and spring cheeses, respectively), that was 384

third in importance after the two previously mentioned odour-active ethyl esters. This 385

particular compound was described as musty and soapy and might contribute to a more 386

intense mouldy flavour in the winter cheeses (Table 4). Nonanal was the only aldehyde 387

detected by means of olfactometry (floral odour) and its OIR values in winter and 388


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spring cheeses were rather similar which indicates that season did not change the 389

contribution of this compound to cheese aroma. 390

As it has been mentioned in the materials and methods section the results 391

reported here are indicative rather than quantitative but they contribute to a further 392

insight into the effect of the season associated with the feeding management. Future 393

research should be directed towards the elucidation of the key aromas of Idiazabal 394

cheese by quantitative techniques such as aroma extract dilution analysis (AEDA). On 395

the other hand, sensory analyses must be carried out to link the differences in aroma-396

active compounds found between winter and spring cheeses and the real contribution of 397

these compounds to the aroma of the cheeses. 398

399

4. Conclusions 400

401

Significant seasonal differences were associated with the two feeding patterns. 402

Fresh pasture grazing in spring enhanced the formation of esters and alcohols and 403

lowered the proportion of carbonyl compounds. Important active compounds detected 404

by olfactometry in winter and spring cheeses were butanoic acid, ethyl butanoate, ethyl 405

hexanoate and 2-heptanone. Coinciding with fresh pasture grazing in spring, the odour 406

impact ratios of esters and alcohols increased indicating that spring cheeses might have 407

more intense fruity and sweet overtones in comparison with winter cheeses. 408

409

Acknowledgements410

411

The authors thank local farmers for supplying cheese samples and technical 412

information on their farming and feeding systems, the Regulatory Board of PDO 413


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Idiazabal cheese and Artzai-Gazta sheepherders´ association for technical support. This 414

work was supported by grants from the Universidad del País Vasco/Euskal Herriko 415

Unibertsitatea (Leioa, Spain) (UNESCO Cathedra/05102) and the Instituto Nacional de 416

Investigación y Tecnología Agraria y Alimentaria (Madrid, Spain) (RTA 2006-00100-417

C02-02). E. Abilleira acknowledges a predoctoral fellowship from the Gobierno 418

Vasco/Eusko Jaurlaritza. 419

420

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554


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Table 1. 1

Average fodder composition of the flocks (mean ± standard deviation) under 2

intensive indoor management in winter and part-time grazing management in 3

spring. 4

Parameter Winter Spring

Concentrate (kg d-1) 1.36 ± 0.42a 0.86 ± 0.17b

Dry matter 1.20 ± 0.37a 0.75 ± 0.15b

Crude protein 0.23 ± 0.06a 0.15 ± 0.02b

Crude fibre 0.10 ± 0.06a 0.05 ± 0.02b

Crude Fat 0.04 ± 0.01a 0.02 ± 0.01b

Ashes 0.08 ± 0.04a 0.05 ± 0.02b

Conserved foragec (kg d-1) 1.72 ± 1.06a 0.20 ± 0.15b

Time on pastured (hours d-1) 0.00 ± 0.00a 7.06 ± 0.68b

Fresh pasture intakee (kg d-1) 0.00 ± 0.00a 4.56 ± 0.16b

a, b Means in a row followed by a different superscript letter were significantly (P5

≤ 0.05) different between spring and winter cheeses.6

c Conserved forages included alfalfa and grass hay, grass silage and maize silage. 7

d Cultivated grasslands with predominance of ryegrass and white clover. 8

e Estimated pasture intake from the time spent on pasture and the other ingested 9

feed.10


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Table 2.11

Effect associated with the flock management type on the relative abundance of the main 12

volatile chemical families (mean area percentage ± standard deviation) found in winter 13

and spring manufactured Idiazabal cheeses after180 days of ripening. 14

Volatile chemical Winter Spring F-test season/season*farm

Acids 46.40 ± 17.84 41.89 ± 20.92 NSa

Alcohols 12.53 ± 8.64 18.75 ± 12.53 *

Esters 5.27 ± 4.81 13.91 ± 6.10 ***

Ketones 27.15 ± 13.63 15.91 ± 14.11 ***

Aldehydes 2.11 ± 1.08 1.18 ± 1.16 *

Hydrocarbons 5.98 ± 4.09 7.37 ± 5.93 NS

Sulphur compounds 0.30 ± 0.79 0.51 ± 1.02 NS

Other compounds 0.26 ± 0.44 0.49 ± 0.96 NS aNS, not significant; * P ≤ 0.05; ** P ≤ 0.01; *** P ≤ 0.001 15


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Table 3.16 Effect associated with the flock management type on the abundance (arbitrary peak area units) of 17 individual volatile compounds (mean ± standard deviation) found in winter and spring 18 manufactured Idiazabal cheeses after 180 days of ripening. 19 LRIa

HP-5ms

LRI DB-

FFAP

Winter Spring F-test season/

season*farmacetic acid 719 1440c 3908 ± 1906 4515 ± 2188 NS butanoic acid 871 1606c 12992 ± 11366 13358 ± 9795 NS pentanoic acid 916 1688c ND 24 ± 52 hexanoic acid 1055 1837c 28071 ± 27357 26775 ± 19672 NS heptanoic acid 1115 1951c 126 ± 186 105 ± 150 NS octanoic acid 1215 2021c 9124 ± 7578 8196 ± 5226 NS decanoic acid 1389 2088c 2247 ± 2724 2097 ± 1269 NS 4-hexenoic acidb 1040 1917 61 ± 154 24 ± 50 *

Total straight acids 56529 ± 51271 55094 ± 38402 NS 3-methylbutanoic acid 901 1652 ND 240 ± 592 3-methylpentanoic acidb 933 12 ± 14 ND

Total branched-chain acids 12 ± 14 240 ± 592 NS ethanol 446 932 3402 ± 2183 4818 ± 1974 NS 1-propanol 572c 1043c 472 ± 927 2230 ± 2716 NS 1-butanol 675c 1166c 132 ± 367 1472 ± 1985 * 3-methyl-1-butanol 749c 1217c 995 ± 252 256 ± 562 NS 1-hexanol 884c 1349c 22 ± 31 618 ± 977 NS 1-octanol 1083 ND 18 ± 29 1-nonanolb 1118 17 ± 18 16 ± 26 NS

Total primary alcohols 5040 ± 3778 9428 ± 8269 * 2-butanol 611c 1028c 5787 ± 6837 10861 ± 14120 NS 2-pentanol 711c 1144 950 ± 1486 1159 ± 625 NS 2,3-butanediolb 840c 1553 99 ± 196 592 ± 940 NS 2-heptanol 911c 1317c 448 ± 595 809 ± 731 NS 2-nonanolb 1109c 1496c ND 62 ± 140

Total secondary alcohols 7284 ± 9114 13483 ± 16556 NS Phenylmethanolb 1057 1875c 128 ± 218 63 ± 108 NS Phenylethanolb 1132 1911 ND 16 ± 32

Total aromatic alcohols 128 ± 218 79 ± 140 NS methyl butanoate 729c 986c ND 268 ± 435 methyl hexanoate 932c 1188c 12 ± 14 159 ± 281 *** methyl octanoateb 1129c 14 ± 13 26 ± 43 NS

Total methyl esters 26 ± 27 453 ± 759 ** ethyl acetate 618c 888c 428 ± 825 1561 ± 1243 * ethyl butanonate 807c 1042c 1661 ± 2522 2880 ± 1747 NS ethyl 2-methylbutanoate 859 1058 ND 36 ± 89 ethyl 3-methylbutanoate 862 1075 ND 79 ± 189 ethyl pentanoate 905 ND 38 ± 65 ethyl hexanoate 1003c 1234c 2142 ± 3201 5842 ± 5415 *** ethyl heptanoate 1101 15 ± 20 35 ± 60 NS ethyl octanoate 1199c 1418c 427 ± 495 625 ± 391 *** ethyl decanoate 1390c 1146 ± 1867 983 ± 1411 NS

Total ethyl esters 5814 ± 8930 12079 ± 10610 *** propyl acetate 721 974 79 ± 210 565 ± 1094 NS


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propyl butanoate 902c 1127c 96 ± 196 1050 ± 1561 * propyl hexanoate 1097c 1311c 56 ± 144 971 ± 1353 ** propyl octanoateb 1291 ND 52 ± 76

Total propyl esters 231 ± 550 2638 ± 4084 *** butyl acetate 823c 1080c 33 ± 79 263 ± 463 NS butyl butanoate 999c 1217c 55 ± 145 313 ± 380 NS butyl hexanoate 1192c 1396c 26 ± 54 134 ± 168 *

Total butyl esters 114 ± 278 710 ± 1011 NS 1-methylpropyl acetate 766 986 106 ± 194 282 ± 293 * isobutyl butanoate 946c 1133 322 ± 562 1196 ± 1486 * isobutyl hexanoate 1135c 1313c 201 ± 349 1332 ± 1726 *** 3-methylbutyl hexanoate 1251 ND 16 ± 27 isobutyl octanoate b 1325 1496 21 ± 30 116 ± 163 ** isobutyl decanoateb 1515 ND 34 ± 58

Total branched-alkyl esters 650 ± 1135 2976 ± 3753 *** 2-propanone 514c 817c 1865 ± 2189 1588 ± 2030 NS 2-butanone 605c 904c 7256 ± 5243 6647 ± 5784 NS 2-pentanone 693c 976c 4594 ± 2346 2181 ± 1598 * 2-hexanone 796c 1088c 74 ± 75 66 ± 152 NS 2-heptanone 896c 1186c 4819 ± 3601 4264 ± 9161 NS 2-octanone 996c 16 ± 26 48 ± 126 NS 8-nonen-2-oneb 1089 55 ± 111 40 ± 105 NS 2-nonanone 1096c 1378c 724 ± 823 899 ± 1615 NS 2-undecanoneb 1294c 52 ± 63 50 ± 48 NS

Total methyl ketones 19455 ± 14477 15783 ± 20619 NS 3-octanoneb 992 ND 23 ± 43 4-heptanone 881 293 ± 831 ND

Total higher alkyl ketones 293 ± 831 23 ± 43 NS 2,3-butanedione 598c 981c 2172 ± 1383 1237 ± 1338 * 3-hydroxy-2-butanone 745c 1290c 1660 ± 2934 ND

Total diketones and derived 3832 ± 4317 1237 ± 1338 * 2-propenal 510 506 ± 1028 ND hexanal 805c 1083c 20 ± 27 13 ± 18 NS heptanal 906c 58 ± 80 63 ± 130 NS nonanal 1108c 88 ± 30 75 ± 63 NS

Total straight aldehydes 672 ± 1165 151 ± 211 NS 3-methylbutanal 656c 916c 1136 ± 589 732 ± 650 NS 2-methylbutanal 664 ND 206 ± 437 Total branched-chain aldehydes 1136 ± 589 938 ± 1087 NS 1,2,4-trimethyl cyclopentaneb 890 20 ± 19 26 ± 43 NS 2,2,4,6,6-pentamethyl heptaneb 991 20 ± 39 33 ± 57 NS undecane 1100c 70 ± 51 46 ± 65 NS

Total alkanes 110 ± 109 105 ± 165 NS 1,3-pentadiene 536 667 4929 ± 4730 6550 ± 5221 NS 3-methylene heptaneb 791 835 85 ± 34 69 ± 33 NS 1-octene/4-octene 798 836 ND 28 ± 60 t-3-octene 801c 837c 57 ± 33 141 ± 99 ** toluene 771c 1043c 80 ± 123 380 ± 123 *** alpha-pinene 937c 24 ± 51 ND Total unsaturated hydrocarbons 5175 ± 4971 7168 ± 5536 NS


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dimethyl sulphide 530c 729c ND 715 ± 1468 carbon disulphide 547c 727 524 ± 1516 ND

Total sulphur compounds 524 ± 1516 715 ± 1468 NS 2-butoxy ethanol 916 1390 24 ± 57 ND 3-methyl-1-butanol acetate 885 1127 15 ± 21 26 ± 41 NS

Total other compounds 39 ± 78 26 ± 41 NS a LRI: linear retention index; ND, not detected; NS, not significant; * P ≤ 0.05; ** P ≤20 0.01; *** P ≤ 0.001 21 b Volatile compounds not previously described in Idiazabal cheese. 22 c Positively identified compounds by comparison with LRI and mass spectra of 23 authentic standards. 24


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Table 4. 25 Odour-active compounds detected by means of GC-O and their estimated odour impact ratios (OIR) 26 in winter and spring manufactured Idiazabal cheeses after 120 and 180 days of ripening. 27

OIRcOdour descriptor Odour familya OTb

Winter Spring

Acids acetic acid pungent, sour Sour 22000 <1 <1 butanoic acid rancid, cheesy, sharp Rancid 50 13 13 hexanoic acid sweaty, goat-like, rancid Sweat 290 5 4 heptanoic acid sweaty, rancid Sweat 3000 <1 <1 octanoic acid sweaty, soapy, waxy Sweat 3000 <1 <1 decanoic acid fatty, soapy Sweat 10000 <1 <1

Alcohols 1-hexanol flowery, fruity Fermented fruit 50 <1 1 2-butanol alcohol, sweet, fruity Fermented fruit 59 5 12 2-pentanol alcohol, fruity, Fermented fruit ― 2-heptanol fruity, sweet, green Herb 5 4 8

Esters ethyl butanoate fruity, apple-like, sweet Stone or pip fruit 1 83 160 ethyl 3-methylbutanoate fruity, sweet Stone or pip fruit 0.2 - 16 ethyl hexanoate fruity, apple-like, mouldy Stone or pip fruit 1 107 305 ethyl octanoate fruity, winey Fermented fruit 70 <1 <1 ethyl decanoate fruity, winey, fatty Fermented fruit 122 <1 <1 propyl butanoate fruity, sweet, pineapple-like Exotic fruit 124 <1 1 propyl hexanoate fruity, pineapple-like, fatty Exotic fruit ― butyl acetate fruity, sweet Stone or pip fruit 66 <1 <1 butyl butanoate fruity, pineapple-like, fatty Exotic fruit 100 <1 <1 butyl hexanoate fruity, pineapple-like, mouldy Exotic fruit 700 <1 <1 1-methylpropyl acetate fruity, citric Exotic fruit ― isobutyl butanoate fruity, sweet, pineapple-like Exotic fruit ― isobutyl hexanoate fruity, pineapple-like, sweet Exotic fruit ―

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Table 4. 25 Odour-active compounds detected by means of GC-O and their estimated odour impact ratios (OIR) 26 in winter and spring manufactured Idiazabal cheeses after 120 and 180 days of ripening. 27

OIRcOdour descriptor Odour familya OTb

Winter Spring

Acids acetic acid pungent, sour Sour 22000 <1 <1 butanoic acid rancid, cheesy, sharp Rancid 50 13 13 hexanoic acid sweaty, goat-like, rancid Sweat 290 5 4 heptanoic acid sweaty, rancid Sweat 3000 <1 <1 octanoic acid sweaty, soapy, waxy Sweat 3000 <1 <1 decanoic acid fatty, soapy Sweat 10000 <1 <1

Alcohols 1-hexanol flowery, fruity Fermented fruit 50 <1 1 2-butanol alcohol, sweet, fruity Fermented fruit 59 5 12 2-pentanol alcohol, fruity, Fermented fruit ― 2-heptanol fruity, sweet, green Herb 5 4 8

Esters ethyl butanoate fruity, apple-like, sweet Stone or pip fruit 1 83 160 ethyl 3-methylbutanoate fruity, sweet Stone or pip fruit 0.2 - 16 ethyl hexanoate fruity, apple-like, mouldy Stone or pip fruit 1 107 305 ethyl octanoate fruity, winey Fermented fruit 70 <1 <1 ethyl decanoate fruity, winey, fatty Fermented fruit 122 <1 <1 propyl butanoate fruity, sweet, pineapple-like Exotic fruit 124 <1 1 propyl hexanoate fruity, pineapple-like, fatty Exotic fruit ― butyl acetate fruity, sweet Stone or pip fruit 66 <1 <1 butyl butanoate fruity, pineapple-like, fatty Exotic fruit 100 <1 <1 butyl hexanoate fruity, pineapple-like, mouldy Exotic fruit 700 <1 <1 1-methylpropyl acetate fruity, citric Exotic fruit ― isobutyl butanoate fruity, sweet, pineapple-like Exotic fruit ― isobutyl hexanoate fruity, pineapple-like, sweet Exotic fruit ―


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28 isobutyl octanoate fruity, herbaceous, fatty Fermented fruit �

Ketones 2-pentanone sweet, fruity Exotic fruit � 2-heptanone musty, soapy Musty 5 48 37 2-nonanone musty, floral, fruity, soapy Musty 5 7 8 2-undecanone fruity, herbaceous Exotic fruit 7 <1 <1

Aldehydes nonanal sweet, fatty-floral Floral 1 4 3

Hydrocarbons t-3-octene sharp, herb, leather-like Herb �

a Odour family classification taken from Barron et al. (2005a). 29 b OT: odour thresholds in water, except for 2-butanol in air. Units expressed as µg L-1or µg kg-1. 30 Data are taken from the following: Rychlik, Schieberle, & Grosch (1998), Fazzalari (1978), van 31 Gemart (2003), Moio, Piombino, & Addeo (2000), Preininger & Grosch (1994), Sablé & 32 Cottenceau (1999), Takeoka, Flath, Mon, Teranishi, & Guentert (1990); a dash � indicates odour 33 threshold in water not found in the literature. 34 c OIR: odour impact ratio corresponds to abundance / (vial volume × odour threshold).35

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2. Discusión general

En general, el efecto de la estacionalidad asociada a cambios en el manejo de

la alimentación de los rebaños se tradujo en mayores contenidos de proteína,

grasa, extracto seco y minerales (calcio y magnesio) en la leche procedente de

los rebaños en pastoreo en época avanzada de lactación frente a la leche de

los rebaños que permanecían en pesebre al inicio de la lactación.

En la primera campaña, en la que se compararon las leches de rebaños

estabulados al inicio de la lactación frente a la leche de los rebaños en

pastoreo hacia el final de la lactación, se observó que una relación

concentrado:forraje superior a 3 en la dieta de los animales en estabulación

produjo un mayor contenido de calcio en la leche y una menor proporción de

grasa en la misma. Por otro lado, en las ovejas en estado de lactación

avanzada que se alimentaban en régimen de pastoreo a tiempo parcial, se

encontraron niveles más elevados de calcio en las muestras de leche

procedentes de los rebaños que más tiempo (16-19 horas/día) permanecieron

en el pasto.

La evolución de cada una de las variables de composición a lo largo de la

época productiva (segunda campaña) fue distinta, pero los incrementos más

notables sucedieron de abril a mayo tras un mes de alimentación basada en

pasto. A partir de ese cambio pronunciado, algunas variables como extracto

seco, proteína, caseína y calcio, se estabilizaron, mientras que otras

continuaron su evolución ascendente hasta el final de la campaña (grasa y

magnesio).

Otros autores han obtenido resultados análogos en estudios de influencia de

distintos manejos de alimentación en diferentes condiciones con ganado ovino,

caprino y bovino (Coulon et al., 1998; Sevi et al., 2000; Soryal et al., 2004;

Pulina et al., 2006).


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Estos cambios en la composición afectaron a las propiedades tecnológicas de

la leche, en cuanto a su aptitud a la coagulación, y a la textura de la cuajada.

De forma general, se obtuvieron cuajadas más firmes y más resistentes a la

compresión con las muestras de leche de los rebaños en pastoreo que con las

muestras de leche de los rebaños alimentados en pesebre al inicio de la época

productiva (Guinee et al., 1997; Auldist et al., 2002).

En la primera campaña, a partir de las leches de los rebaños estabulados al

inicio de la lactación, se obtuvieron cuajadas más resistentes a la compresión

en aquellos rebaños alimentados con una dieta con relación

concentrado:forraje más alta. Sin embargo, la firmeza de la cuajada fue menor

en estas leches que las leches procedentes de ovejas alimentadas con mayor

cantidad de concentrados y menos forraje. Como más adelante se discute al

explicar el significado de estas dos variables tecnológicas, una mayor relación

concentrado:forraje provocó un mayor grado de estructuración del gel de

cuajada (mayor resistencia a la compresión) debido a la mayor presencia de

calcio en la leche (Lucey et al., 2003), y una menor firmeza del gel debido al

menor contenido de grasa atrapada en la cuajada (Guinee et al., 1997; Clark y

Sherbon, 2000).

En la segunda campaña, al igual que las variables de composición, los

parámetros de coagulación y textura también evolucionaron durante la época

productiva de forma distinta. La resistencia a la compresión de la cuajada

alcanzó una meseta a partir del tercer mes (abril) y la firmeza de la cuajada

siguió aumentando hasta el final del estudio (julio).

En cuanto al tiempo de coagulación, en el estudio de la evolución a lo largo del

periodo productivo, éste aumentó mientras que en la primera campaña no se

encontraron diferencias significativas (P > 0.05) entre la leche de los rebaños

estabulados y la de los rebaños que pastaron. En este sentido diferentes

autores han obtenido resultados contradictorios (Auldist et al., 2002; Pellegrini

et al., 2004; Joudu et al., 2008).


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En la primera campaña se observaron buenas correlaciones entre el contenido

de proteína y grasa de la leche y la firmeza de coágulo y cuajada, y entre el

contenido en calcio de la leche y la resistencia a la compresión de la cuajada.

Sin embargo, en la segunda campaña, se observaron altas correlaciones entre

el contenido de proteína y extracto seco de la leche y la resistencia a la

compresión de la cuajada, y entre el contenido de grasa, calcio y magnesio de

la leche y la firmeza de la cuajada. La firmeza y la resistencia a la compresión

de la cuajada son variables tecnológicas muy relacionadas entre sí, y que

definen el parámetro consistencia de la cuajada. De los resultados observados

en la primera y segunda campaña se deduce que las cantidades de grasa,

proteína y sales minerales influyen, en todo caso, sobre la consistencia de la

cuajada. En este sentido, las proteínas (en especial las caseínas) y los

minerales (calcio y magnesio) son responsables de formar la estructura del gel

(Lucey et al., 2003), mientras que la mayor cantidad de grasa atrapada en

dicha estructura contribuye a una mayor firmeza de la cuajada (Guinee et al.,

1997; Clark y Sherbon, 2000).

Al margen de esas correlaciones, en ambas campañas se confirmó la alta

correlación existente entre el pH de la leche y el tiempo de coagulación, lo cual

corroboró la influencia preponderante del pH frente a otro tipo de factores,

como la composición de la leche, en la velocidad de coagulación enzimática

(Bencini, 2002; Nájera et al., 2003). En la segunda campaña se encontró una

nueva correlación negativa entre el nitrógeno no proteico y la firmeza del

coágulo. Aunque no se han encontrado referencias previas al respecto, algunos

autores han indicado que la urea, principal componente de esta fracción

proteica, puede interferir en el proceso de coagulación de la leche (Guinot,

1992; Verdier-Metz et al., 2001).

A partir de la aplicación del análisis de componentes principales (PCA), las

muestras de leche de la primera campaña se distribuyeron separadamente en

función de la alimentación de los animales como muestras de animales

estabulados o de animales en pastoreo. Por otra parte, en las muestras de

leche de animales estabulados se pudieron agrupar de forma diferenciada las

muestras de animales alimentados con alta o baja relación concentrado:forraje.


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Asimismo, en las muestras de animales en pastoreo se diferenciaron los

grupos correspondientes a muestras de leche de animales con alto o bajo

número de horas en pasto. En las muestras de la segunda campaña, y

mediante la aplicación de un análisis discriminante, se pudieron clasificar y

diferenciar completamente las muestras de leche de animales alimentados

exclusivamente en pesebre de las muestras de animales aclimatados al

régimen de pastoreo. El contenido en grasa y magnesio de la leche junto con la

firmeza de la cuajada fueron las variables discriminantes de dichas muestras.

Estas variables, a diferencia del resto de los componentes y parámetros

tecnológicos de la leche, estaban relacionadas con la evolución de la

composición de la leche al final de la época de lactación bajo un manejo de

régimen en pastoreo. Todas estas observaciones fueron indicativas de la

influencia del manejo del rebaño sobre la calidad y propiedades tecnológicas

de la leche, y en particular del efecto del manejo del rebaño en pastoreo a

tiempo parcial.

Ante el interés de disponer de herramientas para certificar con fiabilidad la

procedencia de los productos lácteos de animales en régimen de pastoreo se

detectó la necesidad de buscar compuestos marcadores de este tipo de

alimentación, así como de poder cuantificarlos de forma sencilla y fiable. La

metodología de micro-extracción en fase sólida (SPME) permite una fácil

preparación de muestra, y ha sido frecuentemente utilizada para el análisis de

terpenos (Carpino et al., 2004b; Povolo et al., 2007). Así pues, se desarrolló un

método SPME-GC-MS para analizar y cuantificar de manera sencilla y fiable el

contenido de terpenos en la grasa láctea utilizando 1,3,5-triisopropilbenzeno

como patrón interno. El principal inconveniente que dificulta la puesta a punto

de este tipo de metodología por espacio de cabeza es el efecto matriz debido al

sustrato utilizado a modo de solución de calibración (Lord & Pawlyszin, 2000;

Cornu et al., 2001; Vlachos et al., 2007). El método propone el empleo de una

grasa láctea libre de terpenos (o en cantidades presentes por debajo de su

límite de cuantificación) como la mejor solución para minimizar los problemas

derivados del efecto matriz frente a un aceite sintético y un disolvente orgánico

(metanol) usados como matriz de calibración. Este método es capaz de

cuantificar concentraciones muy bajas, menores de 7 µg/kg para la mayoría de


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los monoterpenos, y por encima de 52 µg/kg para los sesquiterpenos, con

precisión y exactitud aceptables.

A la hora de comprobar la adecuación de este tipo de compuestos como

herramienta de trazabilidad del tipo de dieta a lo largo de la época productiva

en condiciones de campo, se observó una clara influencia de la alimentación de

los animales en régimen de pastoreo a tiempo parcial sobre el contenido total

de terpenos en las muestras de leche, el cual fue más alto que en los meses de

estabulación intensiva, como cabía esperar (Carpino et al., 2004b; Cornu et al.,

2005). Sin embargo, se detectaron grandes diferencias en los máximos de

acumulación de monoterpenos y sesquiterpenos individuales a lo largo del

periodo productivo, y hubo también una gran variabilidad en la leche de los

diferentes rebaños comerciales dentro de cada mes debida a diferentes causas

como son factores medioambientales, climatología, características del suelo,

composición botánica y localización de los pastos, estado de maduración de

cada especie herbácea, manejo del pastoreo, y las características intrínsecas

de cada rebaño. Por todo esto, con los resultados disponibles hasta el

momento, obtenidos en este estudio o aportados por otros autores

(Schlichtherle-Cerny et al., 2004; Prache et al., 2005; Sivadier et al., 2008),

resulta difícil proponer con garantía un compuesto terpénico marcador del uso

de pastoreo a tiempo parcial frente a manejos en intensivo con alimentos a

base de concentrado y forrajes. Sin embargo, pueden resaltarse algunos de los

resultados obtenidos. Los terpenos α-pineno y β-cariofileno se correlacionaron

con la evolución estacional, y han sido detectados también por otros autores en

la leche de rumiantes tras la ingesta de alimentos que contienen terpenos

(forrajes y hierba del pasto) (Viallon et al., 2000; Tornambé et al., 2006).

También cabe destacar que los sesquiterpenos únicamente se detectaron en

las leches de los rebaños en pastoreo. Por ello, de acuerdo a otros resultados

cuantitativos obtenidos en estudios análogos por otros autores (Favaro et al.,

2005), β-cariofileno podría ser propuesto como compuesto marcador diferencial

de manejo de pasto frente a manejo intensivo con concentrados y forrajes,

aunque quedan por resolver todavía cuestiones muy importantes para

considerar éste, u otro compuesto terpénico, como marcador de pastoreo.

Algunas de estas cuestiones son la presencia de β-cariofileno en distintos tipos


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de forraje según su origen y modo de conservación, y los niveles de

acumulación del compuesto que deben considerarse mínimos para considerar

una leche procedente de un sistema de pastoreo frente a un sistema intensivo.

Es pues necesaria una mayor profundización en este ámbito, haciéndose

necesario contextualizar este tipo de estudios en cada caso de interés. En el

caso de las Denominaciones de Origen y otros organismos de control y

certificación, el interés no es otro que el de proteger los productos de calidad o

diferenciarlos de otros productos debido al manejo en pastoreo.

En lo referente a la calidad nutricional funcional de los quesos, aquellos

elaborados a partir de leche de los rebaños alimentados a base de hierba

fresca presentaron un perfil de ácidos grasos más saludable que los quesos

procedentes de los mismos rebaños en estabulación. La grasa de los quesos

de pasto presentó un menor contenido de ácidos grasos saturados y un mayor

contenido de ácidos grasos insaturados. Esto se tradujo en un descenso

notable (1.5 veces menor) del índice aterogénico en la grasa de los quesos de

los rebaños en régimen de pastoreo en comparación con los quesos de los

rebaños alimentados en pesebre.

Los quesos de primavera de pasto tuvieron niveles más altos de ácidos grasos

deseables desde un punto de vista nutricional funcional, tales como el ácido

ruménico, el trans-vaccenico, el docosahexaenoico (DHA) y el grupo de los

ácidos grasos ramificados, entre otros. Cabe destacar que la concentración de

los isómeros CLAs en los quesos se multiplicó por 2.5 como consecuencia de

la alimentación de pasto en primavera. Varios autores han descrito incrementos

similares y los resultados presentados aquí concuerdan con los trabajos de

otros investigadores (Nudda et al., 2005; Atti et al., 2006; Khanal et al., 2008;

Rego et al., 2008).

En la aplicación del análisis de componentes principales a las muestras de

queso de todos los rebaños, se extrajeron dos componentes principales que

explicaron el 84.2 % de la varianza total. En su representación bidimensional,

se pudo observar que las muestras de queso se agruparon en función del

manejo empleado, es decir, manejo con alimentación en pesebre en los meses


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de invierno y manejo en pastoreo en los meses de primavera y verano. La

ingesta de concentrado se asoció al incremento de la grasa saturada en el

queso, mientras que la ingesta de hierba fresca fue responsable del incremento

de la grasa insaturada durante la época productiva.

En cuanto a la fracción volátil de los quesos, se encontraron diferencias

significativas (P ≤ 0.05) en la composición de los compuestos volátiles debidas

a la estacionalidad asociada al tipo de manejo alimenticio del rebaño entre los

quesos de invierno y los procedentes de animales en pastoreo, a pesar de la

gran variabilidad observada entre los rebaños comerciales dentro de cada

época de elaboración y tiempo de maduración del queso. Esta variabilidad fue

debida fundamentalmente al carácter artesanal de la producción de queso

Idiazabal, y puso de manifiesto el efecto preponderante de los parámetros

tecnológicos empleados en la elaboración del queso para el desarrollo de

compuestos volátiles durante la maduración. El manejo de los rebaños en

pastoreo redundó en un mayor contenido de ésteres y alcoholes en el queso

Idiazabal, y un descenso de la proporción de compuestos carbonílicos.

Por otra parte, desde el punto de vista de las propiedades sensoriales de los

quesos, los resultados de la olfatometría pusieron de manifiesto que el ácido n-

butanoico, los ésteres etil butanoato y etil hexanoato, junto con la metil-cetona

2-heptanona, fueron los principales compuestos con impacto aromático

respecto a su contribución al aroma global de las muestras de queso Idiazabal.

Estudios previos han encontrado correlaciones positivas entre los ácidos

grasos de cadena corta y los descriptores de olor “penetrante”, “rancio”, “cuajo”

y “salmuera” (Barron et al., 2005a; 2007). Los etil ésteres también se han

correlacionado con los descriptores de olor a “cuajo”, “penetrante” y “salmuera”

en el queso Idiazabal y en otros tipos de queso (Lawlor et al., 2002; Barron et

al., 2005a). Los quesos elaborados a partir de la leche de los rebaños en

pastoreo tuvieron mayor relación de impacto odorante (OIR) de ésteres y

alcoholes, lo cual podría ser indicativo de que éstos quesos presentarían notas

olfativas más afrutadas y dulces que los quesos elaborados a partir de la leche

de los rebaños durante el periodo de estabulación invernal (Barron et al,

2005a). Dado que no fue posible la realización de análisis sensoriales de los


180


162

quesos de los rebaños comerciales muestreados en este estudio, es necesario

confirmar los resultados olfatométricos obtenidos con resultados

diferenciadores de los atributos sensoriales de los quesos elaborados a partir

de leche de animales estabulados frente a los de aquellos elaborados a partir

de leche de animales en régimen de pastoreo.

Capítulo 5. CONCLUSIONES

capÍtulo 5. conclusiones

183

Capítulo 5. Conclusiones

165

En vista de los resultados obtenidos se llegó a las siguientes conclusiones:

1. La estacionalidad asociada a cambios en el manejo de la alimentación de

los rebaños sometidos a régimen de pastoreo a tiempo parcial afectó a la

composición y a las propiedades tecnológicas de la leche:

1.1. El manejo de los rebaños en estado de lactación avanzada en régimen

de pastoreo a tiempo parcial redundó en contenidos superiores de

proteína, grasa, extracto seco, calcio y magnesio en la leche. Estos

cambios fueron responsables de una mayor firmeza y resistencia a la

compresión de la cuajada, propiedades tecnológicas que afectan a la

textura del queso final. El tiempo de coagulación fue afectado

principalmente por el pH de la leche en el proceso de formación de la

cuajada.

1.2. La diferente relación concentrado:forraje utilizada para la alimentación

de los rebaños en los meses de estabulación provocó ligeros cambios

en la composición de la leche, los cuales afectaron a la mayor o menor

firmeza de la cuajada. En los meses de pastoreo, el mayor o menor

tiempo de permanencia de los animales en el pasto, apenas modificó la

composición de la leche, viéndose únicamente afectado su contenido en

calcio, y sin efecto significativo sobre las propiedades de coagulación.

2. El manejo de los rebaños en pastoreo a tiempo parcial afectó sensiblemente

a la composición de terpenos de la leche:

2.1. El método SPME-GC-MS desarrollado proporciona una herramienta

sencilla y fiable para la cuantificación de terpenos en muestras de leche

utilizando 1,3,5-triisopropilbenzeno como patrón interno. Este método

permite la detección de muy pequeñas cantidades de monoterpenos y

sesquiterpenos en grasa láctea, pudiendo ser utilizado en estudios de

trazabilidad de leches procedentes de animales en pastoreo.


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166

2.2. El contenido total de terpenos aumentó al pasar de la alimentación

basada exclusivamente en concentrado y forraje a la alimentación de

los animales en régimen de pastoreo a tiempo parcial, y los

sesquiterpenos únicamente fueron detectados en leches de rebaños

aclimatados al pastoreo.

2.3. A pesar de la alta correlación observada entre los sesquiterpenos, en

particular β-cariofileno, y la evolución estacional de los rebaños, no fue

posible proponer ningún compuesto marcador del manejo en régimen

de pastoreo a tiempo parcial debido a la gran variabilidad observada en

la acumulación de terpenos individuales durante el período productivo

en cada rebaño comercial.

3. La estacionalidad asociada a cambios en el manejo de la alimentación de

los rebaños sometidos a régimen de pastoreo a tiempo parcial afectó a la

calidad nutricional funcional y tecnológica del queso:

3.1. La composición de los ácidos grasos de los quesos fue distinta en

función del manejo del rebaño. La calidad nutricional funcional de los

quesos elaborados a partir de la leche de los rebaños en pastoreo fue

superior porque presentaron un perfil de ácidos grasos más saludable.

Los quesos de pastoreo contenían menos grasa saturada, más grasa

insaturada y niveles más altos de ácido ruménico, trans-vaccenico y

docosahexaenoico.

3.2. La composición de los compuestos volátiles de los quesos también se

vio afectada por el manejo de los rebaños, redundando en propiedades

olfativas diferenciadas. Los quesos de pastoreo presentaron mayor

contenido en ésteres y alcoholes, y menores cantidades de compuestos

cabonílicos que los quesos elaborados con la leche de los rebaños en el

período de estabulación invernal. A su vez, el impacto aromático

determinado por olfatometría de los ésteres y alcoholes fue superior en

los quesos de pastoreo. Este hecho, podría ser indicativo de una mayor

capÍtulo 5. conclusiones

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presencia de notas afrutadas y dulces en los quesos de pastoreo frente

a los quesos de rebaños alimentados exclusivamente en pesebre.

3.3. Con independencia de la época de elaboración, ácido butanoico, etil

butanoato, etil hexanoato y 2-heptanona fueron los compuestos con

mayor impacto aromático en los quesos, lo cual pone de manifiesto la

importancia de estos compuestos en el desarrollo del olor y aroma

característico del queso Idiazabal.

4. El manejo del rebaño en pastoreo a tiempo parcial, permite producir leche y

queso de buena calidad desde punto de vista nutricional funcional y

tecnológico, aprovechando al máximo los recursos naturales disponibles y

contribuyendo a la sostenibilidad del propio manejo y del entorno.

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TESIS DOCTORALES PUBLICADAS

Nº 1. La raza Latxa: Sistemas de producción y características reproductivas. Eduardo uriartE EgurcEgui

Nº 2. Estudio y puesta a punto de un método simplificado de control lechero cualitativo en la raza ovina Latxa y su inclusión en el plan de selección. gustavo adolfo Maria lEvrino

Nº 3. Implicaciones tecnológicas de la composición química del pescado con especial referencia a los lípidos. rogElio Pozo carro

Nº 4. Estudio de suelos de Vizkaia. Margarita doMingo urartE

Nº 5. El Maedi o neumonía progresiva en el conjunto de las enfermedades respiratorias crónicas del ganado ovino en la Comunidad Autónoma Vasca. lorEnzo gonzálEz angulo

Nº 6. Estudio experimental de las fases iniciales de la paratuberculosis ovina. raMón a. JustE Jordan

Nº 7. Identificación, origen y factores fisicoquímicos que condicionan la contaminación por elementos metálicos de sedimentos de ríos. Estilita ruiz roMEra

Nº 8. Análisis financiero de proyectos de inversión en repoblaciones forestales. álavaro aunos góMEz

Nº 9. Desarrollo y evaluación del sistema integrado de diagnóstico y recomendación (DRIS) para la fertilización de las praderas permanentes. Marta Rodríguez Julia

Nº 10. Estudio de las mieles producidas en la Comunidad Autónoma del País Vasco. María tErEsa sancho ortiz

Nº 11. La biomasa microbiana como agente de las transformaciones de nitrógeno en el suelo tras el enterrado de la paja de cereal. JEsús ángEl ocio arMEntia

Nº 12. Análisis jurídico y económico de la implementación de la política agraria comunitaria en la Comunidad Autónoma del País Vasco. BEatriz PérEz dE las hEras

Nº 13. Nemátodos formadores de quistes (Globodera spp.) en patata (Solanum tuberosum L.): caracteri-zación taxonómica, reproducción y actividad de las formas juveniles. azucEna salazar Bayona

Nº 14. Ensayo comparativo de tres métodos de tratamiento antihelmítico estratégico en rebaños de ove-jas latxas. ana luisa gracia PérEz

Nº 15. Estudio sobre una encefalitis vírica similar al Louping-ill en el ganado ovino de la Comunidad Autónoma Vasca. daniEl fErnándEz dE luco Martinéz

Nº 16. Análisis de caracteres involucrados en la selección y mejora de Lupinus hispanicus Boiss. et Reuter. vErónica arriEta Pico

Nº 17. Contribución al estudio de fermentaciones artesanales e industriales de Rioja Alavesa. Milagros viñEgra garcía

Nº 18. Estudio del manejo de la alimentación en los rebaños ovinos de raza Latxa y su influencia sobre los resultados reproductivos y de producción de leche. luis Mª. orEgui lizarraldE

Nº 19. El sector pesquero vizcaíno, 1800-1960. Análisis de la interacción de los elementos ambiental, extractivo y comercial en la pesquería. José agustín Maiz alcorta

Nº 20. Epidemiología, diagnóstico y control de la paratuberculosis ovina en la Comunidad Autónoma del País Vasco. J. J. aduriz rEcaldE

Nº 21. Agrupación de poblaciones locales de maíz (Zea mays L.) mediante caracteres morfológicos y parámetros ambientales. José ignacio ruiz dE galarrEta góMEz

Nº 22. Estudio del potencial melífero de Bizkaia. aMElia cErvEllo MartínEz

Nº 23. Influencia de los procesos de salado y ahumado sobre las características fisicoquímicas del queso Idiazabal (compuestos nitrogenados). francisco c. iBañEz Moya

Nº 24. El Euskal Artzain Txakurra (el perro pastor vasco) descripción y tipificación racial. Mariano góMEz fErnándEz

Nº 25. Evaluación de diferentes ciclos de selección recurrente en dos poblaciones sintéticas de maíz. gotzonE garay solachi

Nº 26. Valoración agronómica de la gallinaza: Compostaje. adolfo MEnoyo PuEllEs

Nº 27. Relación clima-vegetación en la Comunidad Autónoma del País Vasco. aMElia ortuBay fuEntEs

Nº 28. Influencia de los procesos de salado y ahumado tradicional sobre las características microbioló-gicas y organolépticas del queso Idiazabal. francisco J. PérEz Elortondo

Nº 29. Mastitis en la oveja Latxa: epidemiología, diagnóstico y control. Juan c. Marco MElEro

Nº 30. Contribución al conocimiento anatomopatológico y diagnóstico de la tuberculosis caprina y ovina por Mycobacterium bovis. M.ª MontsErrat gutiérrEz cancEla

Nº 31. Estudio de factores que pueden influir en la calidad de la pluma de gallos Eusko-oiloa (Variedad Marradune) para la fabricación de moscas artificiales utilizadas en la pesca de la trucha. rosa M.ª Echarri toMé

Nº 32. Estudio de la fracción lipídica durante la maduración del queso Idiazabal. Influencia de los pro-cesos tecnológicos del tiempo de permanencia en salmuera y ahumado. ana isaBEl náJEra ortigosa

Nº 33.- Influencia del tipo de cuajo y adición de cultivo iniciador sobre los compuestos nitrogenados durante la maduración del queso Idiazabal. M.ª solEdad vicEntE Martín

Nº 34. Estudio de la infección por Borrelia burgdorferi, grupo Ehrlichia phagocytophila y virus de la encefalitis ovina en las poblaciones de ixódidos de la Comunidad Autónoma Vasca. Marta Barral lahidalga

Nº 35. Lipolisis en el queso Idiazabal: efecto de la época de elaboración, del cultivo iniciador, de la pasteurización y del tipo de cuajo. fElisa chavarri díaz dE cErio

Nº 36. Aspectos inmunopalógicos de la paratuberculosis de los pequeños rumiantes. Respuesta inmune asociada a la vacunación. Juan ManuEl corPa arEnas

Nº 37. Desarrollo y evaluación de nuevas técnicas de diagnóstico del Maedi-Visna. ana BElén ExtraMiana alonso

Nº 38. Estudios sobre Patogenia y Diagnóstico de la Adenomatosis Pulmonar Ovina. María MErcEdEs garcía goti

Nº 39. Análisis de los factores de explotación que afectan a la producción lechera en los rebaños de raza Latxa de la CAPV. roBErto J. ruiz santos

Nº 40. Crecimiento y producción de repoblaciones de Pinus radiata D. Don en el Territorio Histórico de Gipuzkoa (País Vasco). luis Mario chauchard Badano

Nº 41. Puesta a punto de técnicas PCR en heces y de Elisa para el diagnóstico de la Paratuberculosis. Estudio de prevalencia en ganado bovino. JosEBa M. garrido urkullu

Nº 42. Epidemiología y diagnóstico de la leptospirosis y la neosporosis en explotaciones de bovino lechero de la CAPV. raquEl achaErandio galdos

Nº 43. Relaciones aire-agua en sustratos de cultivo como base para el control del riego. Metodología de laboratorio y modelización. valEntín tErés tErés

Nº 44. Zonas endémicas de enfermedad de Lyme en la CAPV: estudio del papel de los micromamíferos en el mantenimiento de Borrelia burgdorferi sensu lato en el medio natural. horacio gil gil

Nº 45. Optimización del esquema de mejora de la raza Latxa: análisis del modelo de valoración e intro-ducción de nuevos caractéres en el objetivo de selección. andrés lEgarza alBizu

Nº 46. Influencia de las condiciones de almacenamiento, reimplantación y lluvia ácida en la viabilidad de Pinus radiata D. Don. MirEn aMaia MEna PEtitE

Nº 47. Estudio sobre encefalopatías en peces: patogenicidad del nodavirus causante de la enfermedad y retinopatía vírica (ERV) y transmisión experimental del prión scrapie a peces. raquEl arangurEn ruiz

Nº 48. Enfermedades transmitidas por semilla en judía-grano (Phaseolus vulgaris L.): detección, control sanitario y mejora genética. ana María díEz navaJas

Nº 49. Pastoreo del ganado vacuno en zonas de montaña y su integración en los sistemas de producción de la CAPV. nErEa Mandaluniz astigarraga

Nº 50. Aspectos básicos de la mejora genética de patata (Solanum tuberosum L.) a nivel diploide. lEirE Barandalla urtiaga

nº 51. El cuajo de cordero en pasta: preparación y efecto en los procesos proteolíticos y lipolíticos de la maduración del queso de Idiazabal. Mª. ángElEs BustaMantE gallEgo

Nº 52. Dinámica de la población de atún blanco (Thunnus alalunga Bonnaterre 1788) del Atlántico Norte. Josu santiago Burrutxaga

nº 53. El pino radiata (Pinus radiata D.Don) en la historia forestal de la Comunidad Autónoma de eus-kadi. Análisis de un proceso de forestalismo intensivo. Mario MichEl rodríguEz

nº 54. Balance hídrico y mineral del pimiento de Gernika (Capsicum annuum L., cv Derio) en cultivo hidropónico. Relaciones con la producción. hugo Macía olivEr

nº 55. Desarrollo de métodos moleculares y su aplicación al estudio de la resistencia genética y patoge-nia molecular del Scrapie. david garcía crEsPo

nº 56. Estudio epidemiológico y experimental de la transmisión y control del virus Maedi-Visna en ovino lechero de raza Latxa del País Vasco. vEga álvarEz MaiztEgui

nº 57. Desarrollo y aplicación de técnicas de diagnóstico serológico para el estudio de la transmisión calostral y horizontal del virus Maedi-Visna (VMV) en ovino. Mara Elisa daltaBuit tEst

nº 58. Integral Study of Calving Ease in Spanish Holstein Population. EvangElina lóPEz dE Maturana lóPEz dE lacallE

nº 59. Caracterización Molecular, Detección y Resistencia de Mycobacterium avium subespecie paratu-berculosis. ikEr sEvilla agirrEgoMoskorta

nº 60. Desarrollo de un sistema de fertilización nitrogenada racional en trigo blando de invierno bajo condiciones de clima mediterráneo húmedo. M.ª arritokiEta ortuzar iragorri

nº 61. Estructura y dinámica de la materia orgánica del suelo en ecosistemas forestales templados: de los particular a lo general. nahia gartzia BEngoEtxEa

nº 62. Análisis sensorial del vino tinto joven de Rioja Alavesa: descripción y evaluación de la calidad. iñaki Etaio alonso

nº 63. Biología del gusano de alambre (Agriotes spp.) en la Llanada Alavesa y desarrollo de estrategias de control integrado en el cultivo de la patata. ana isaBEl ruiz dE azúa Estívariz

nº 64. La sucesión en la ganadería familiar: el ovino de leche en el País Vasco. guadaluPE raMos truchEro

nº 65. Identificación molecular de las especies de piroplasmas en las poblaciones de Inóxidos de la Comunidad Autónoma del País Vasco. Distribución y prevalencia de babesia y theileria en los ungulados domésticos y silvestre. MirEn JosunE garcía

nº 66. Estudio de variables inmunológicas y bacteriológicas en relación con la inmunización frente a paratuberculosis en los rumiantes. María v. gEiJo vázquEz

nº 67. Bacterias lácticas de sidra natural: implicación en alteraciones y potencial probiótico de cepas productoras de (1,3)(1,2)-ß-D-glucanos. gaizka garai iBaBE

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