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Genetic parameters of milk fatty acid profile in sheep: comparison between gas chromatographic measurements and Fourier-transform IR spectroscopy predictions

Published online by Cambridge University Press:  17 July 2018

F. Correddu*
Affiliation:
Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia, 39, 07100 Sassari, Italy
M. Cellesi
Affiliation:
Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia, 39, 07100 Sassari, Italy
J. Serdino
Affiliation:
Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia, 39, 07100 Sassari, Italy
M. G. Manca
Affiliation:
Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia, 39, 07100 Sassari, Italy
M. Contu
Affiliation:
Associazione regionale allevatori della Sardegna, 09128 Cagliari, Italy
C. Dimauro
Affiliation:
Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia, 39, 07100 Sassari, Italy
I. Ibba
Affiliation:
Associazione regionale allevatori della Sardegna, 09128 Cagliari, Italy
N. P. P. Macciotta
Affiliation:
Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia, 39, 07100 Sassari, Italy
*
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Abstract

Fatty acid (FA) composition is a key component of sheep milk nutritional quality. However, breeding for FA composition in dairy sheep is hampered by the logistic and phenotyping costs. This study was aimed at estimating genetic parameters for sheep milk FA and to test the feasibility of their routine measurement by using Fourier-transform IR (FTIR) spectroscopy. Milk FA composition of 989 Sarda ewes farmed in 48 flocks was measured by gas chromatography (FAGC). Moreover, FTIR spectrum was collected for each sample, and it was used to predict FA composition (FAFTIR) by partial least squares regression: 700 ewes were used for estimating model parameters, whereas the remaining 289 animals were used to validate the model. One hundred replicates were performed by randomly assigning animals to estimation and validation data set, respectively. Variance components for both measured and predicted traits were estimated with an animal model that included the fixed effects of parity, days in milking interval, lambing month, province, altitude of flock location, the random effects of flock-test-date and animal genetic additive. Genetic correlations among FAGC, and between corresponding FAGC and FAFTIR were estimated by bivariate analysis. Coefficients of determination between FAGC and FAFTIR ranged from moderate (about 0.50 for odd- and branched-chain FA) to high (about 0.90 for de novo FA) values. Low-to-moderate heritabilities were observed for individual FA (ranging from 0.01 to 0.47). The largest value was observed for GC measured C16:0. Low–to-moderate heritabilities were estimated for FA groups. In most of cases, heritabilites were slightly larger for FAGC than FAFTIR. Estimates of genetic correlations among FAGC showed a large variability in magnitude and sign. The genetic correlation between FAFTIR and FAGC was higher than 60% for all investigated traits. Results of the present study confirm the existence of genetic variability of the FA composition in sheep and suggest the feasibility of using FAFTIR as proxies for these traits in large scale breeding programs.

Type
Research Article
Copyright
© The Animal Consortium 2018 

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References

Banni, S, Heys, SD and Wahle, KWJ 2003. Conjugated linoleic acids as anticancer nutrients: studies in vivo and cellular mechanisms. In Advances in conjugated linoleic acid research (ed. W Christie, J-L Sébédio and R Adlof), pp. 267282. AOCS Press, Champaign, IL, USA.Google Scholar
Barillet, F, Marie, C, Jacquin, M, Lagriffoul, G and Astruc, JM 2001. The French Lacaune dairy sheep breed: use in France and abroad in the last 40 years. Livestock Production Science 71, 1729.Google Scholar
Boichard, D, Govignon-Gion, A, Larroque, H, Maroteau, C, Palhiere, I, Tosser-Klopp, G, Rupp, R, Sánchez, MP and Brochard, M 2014. Déterminisme génétique de la composition en acides gras et protéines du lait des ruminants, et potentialités de sélection. Inra Production Animales 27, 283298.Google Scholar
Bonfatti, V, Vicario, D, Lugo, A and Carnier, P 2017. Genetic parameters of measures and population-wide infrared predictions of 92 traits describing the fine composition and technological properties of milk in Italian Simmental cattle. Journal of Dairy Science 100, 55265540.Google Scholar
Caredda, M, Addis, M, Ibba, I, Leardi, R, Scintu, MF, Piredda, G and Sanna, G 2016. Prediction of fatty acid content in sheep milk by mid-infrared spectrometry with a selection of wavelengths by genetic algorithms. LWT-Food Science and Technology 65, 503510.Google Scholar
Carta, A, Casu, S and Salaris, S 2009. Invited review: current state of genetic improvement in dairy sheep. Journal of Dairy Science 92, 58145833.Google Scholar
Chen, S, Bobe, G, Zimmerman, S, Hammond, EG, Luhman, CM, Boylston, TD, Freeman, AE and Beitz, DC 2004. Physical and sensory properties of dairy products from cows with various milk fatty acid compositions. Journal of Agricultural and Food Chemistry 52, 34223428.Google Scholar
Correddu, F, Serdino, J, Manca, MG, Cosenza, G, Pauciullo, A, Ramunno, L and Macciotta, NPP 2017. Use of multivariate factor analysis to characterize the fatty acid profile of buffalo milk. Journal of Food Composition and Analysis 60, 2531.Google Scholar
Czulak, J, Hammond, LA and Horwood, JF 1974. Cheese and cultured dairy products from milk with high linoleic acid content: I. Manufacture and physical and flavor characteristics. Australian Journal of Dairy Technology 29, 124.Google Scholar
De Marchi, M, Penasa, M, Cecchinato, A, Mele, M, Secchiari, P and Bittante, G 2011. Effectiveness of mid-infrared spectroscopy to predict fatty acid composition of Brown Swiss bovine milk. Animal 5, 16531658.Google Scholar
De Marchi, M, Toffanin, V, Cassandro, M and Penasa, M 2014. Invited review: mid-infrared spectroscopy as phenotyping tool for milk traits. Journal of Dairy Science 97, 11711186.Google Scholar
Dervishi, E, Serrano, M, Joy, M, Sarto, P, Somera, A, González-Calvo, L, Berzal-Herranzd, B, Molino, F, Martinez-Royo, A and Calvo, JH 2015. Structural characterisation of the acyl CoA: diacylglycerol acyltransferase 1 (DGAT1) gene and association studies with milk traits in Assaf sheep breed. Small Ruminant Research 131, 7884.Google Scholar
Food and Agriculture Organization of the United Nations Statistics Division 2014. Statistical Database of the Food and Agriculture Organization of the United Nations, FAOSTAT. Retrieved on 10 May 2017 from http://faostat3.fao.org/faostat-gateway/go/to/home/E.Google Scholar
Ferrand-Camels, M, Palhiere, I, Brochard, M, Leray, O, Astruc, JM, Aurel, MR, Barbey, S, Bouvier, F, Brunschwig, P, Caillat, H, Douguet, M, Faucon-Lahalle, F, Gelé, M, Thomas, G, Trommenschlager, JM and Larroque, H 2014. Prediction of fatty acid profiles in cow, ewe, and goat milk by mid-infrared spectrometry. Journal of Dairy Science 97, 1735.Google Scholar
Gama, MAS, Garnsworthy, PC, Griinari, JM, Leme, PR, Rodrigues, PHM, Souza, LWO and Lanna, DPD 2008. Diet-induced milk fat depression: association with changes in milk fatty acid composition and fluidity of milk fat. Livestock Science 115, 319331.Google Scholar
Garnsworthy, PC, Feng, S, Lock, AL and Royal, MD 2010. Short communication: heritability of milk fatty acid composition and stearoyl-CoA desaturase indices in dairy cows. Journal of Dairy Science 93, 17431748.Google Scholar
Groeneveld, E, Kovac, M and Mielenz, N 2010. VCE user’s guide and reference manual version 6.0. Retrieved on 10 September 2015 from ftp://ftp.tzv.fal.de/ pub/vce6/doc/vce6-manual-3.1-A4.pdf.Google Scholar
Heck, JM, van Valenberg, HJ, Bovenhuis, H, Dijkstra, J and van Hooijdonk, TC 2012. Characterization of milk fatty acids based on genetic and herd parameters. Journal of Dairy Research 79, 3946.Google Scholar
Kieseker, FG and Eustace, IJ 1975. Manufacture by conventional churning of butter high in linoleic acid: technology, physical properties and sensory evaluation. Australian Journal of Dairy Technology 30, 17-22.Google Scholar
Lopez-Villalobos, N, Spelman, RJ, Melis, J, Davis, SR, Berry, SD, Lehnert, K, Holroyd, SE, MacGibbon, AKH and Snell, RG 2014. Estimation of genetic and crossbreeding parameters of fatty acid concentrations in milk fat predicted by mid-infrared spectroscopy in New Zealand dairy cattle. Journal of Dairy Research 81, 340349.Google Scholar
Manca, MG, Serdino, J, Gaspa, G, Urgeghe, P, Ibba, I, Contu, M, Fresi, P and Macciotta, NPP 2016. Derivation of multivariate indices of milk composition, coagulation properties, and individual cheese yield in dairy sheep. Journal of Dairy Science 99, 45474557.Google Scholar
Mele, M, Dal Zotto, R, Cassandro, M, Conte, G, Serra, A, Buccioni, A, Bittante, G and Secchiari, P 2009. Genetic parameters for conjugated linoleic acid, selected milk fatty acids, and milk fatty acid unsaturation of Italian Holstein-Friesian cows. Journal of Dairy Science 92, 392400.Google Scholar
Nudda, A, Battacone, G, Boaventura Neto, O, Cannas, A, Francesconi, AHD, Atzori, AS and Pulina, G 2014. Feeding strategies to design the fatty acid profile of sheep milk and cheese. Revista Brasileira de Zootecnia 43, 445456.Google Scholar
Nudda, A, McGuire, MA, Battacone, G and Pulina, G 2005. Seasonal variation in conjugated linoleic acid and vaccenic acid in milk fat of sheep and its transfer to cheese and ricotta. Journal of Dairy Science 88, 13111319.Google Scholar
Parodi, PW 1999. Conjugated linoleic acid and other anticarcinogenic agents of bovine milk fat. Journal of Dairy Science 82, 13391349.Google Scholar
Pegolo, S, Cecchinato, A, Casellas, J, Conte, G, Mele, M, Schiavon, S and Bittante, G 2016. Genetic and environmental relationships of detailed milk fatty acids profile determined by gas chromatography in Brown Swiss cows. Journal of Dairy Science 99, 13151330.Google Scholar
Rutten, MJM, Bovenhuis, H and Van Arendonk, JAM 2010. The effect of the number of observations used for Fourier transform infrared model calibration for bovine milk fat composition on the estimated genetic parameters of the predicted data. Journal of Dairy Science 93, 48724882.Google Scholar
Sánchez, JP, San Primitivo, F, Barbosa, E, Varona, L and De La Fuente, LF 2010. Genetic determination of fatty acid composition in Spanish Churra sheep milk. Journal of Dairy Science 93, 330339.Google Scholar
Schennink, A, Heck, JM, Bovenhuis, H, Visker, MH, van Valenberg, HJ and van Arendonk, JA 2008. Milk fatty acid unsaturation: genetic parameters and effects of stearoyl-CoA desaturase (SCD1) and acyl CoA: diacylglycerol acyltransferase 1 (DGAT1). Journal of Dairy Science 91, 21352143.Google Scholar
Signorelli, F, Contarini, G, Annicchiarico, G, Napolitano, F, Orrù, L, Catillo, G, Haenlein, GFW and Moioli, B 2008. Breed differences in sheep milk fatty acid profiles: opportunities for sustainable use of animal genetic resources. Small Ruminant Research 78, 2431.Google Scholar
Soyeurt, H, Dardenne, P, Dehareng, F, Lognay, G, Veselko, D, Marlier, M, Bertozzi, C, Mayeres, P and Gengler, N 2006. Estimating fatty acid content in cow milk using mid-infrared spectrometry. Journal of Dairy Science 89, 36903695.Google Scholar
Soyeurt, H, Dehareng, F, Gengler, N, McParland, S, Wall, E, Berry, DP, Coffey, M and Dardenne, P 2011. Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries. Journal of Dairy Science 94, 16571667.Google Scholar
Soyeurt, H, Gillon, A, Vanderick, S, Mayeres, P, Bertozzi, C and Gengler, N 2007. Estimation of heritability and genetic correlations for the major fatty acids in bovine milk. Journal of Dairy Science 90, 44354442.Google Scholar
Stoop, WM, Van Arendonk, JAM, Heck, JML, Van Valenberg, HJF and Bovenhuis, H 2008. Genetic parameters for major milk fatty acids and milk production traits of Dutch Holstein-Friesians. Journal of Dairy Science 91, 385394.Google Scholar
Tudisco, R, Grossi, M, Calabrò, S, Cutrignelli, MI, Musco, N, Addi, L and Infascelli, F 2014. Influence of pasture on goat milk fatty acids and Stearoyl-CoA desaturase expression in milk somatic cells. Small Ruminant Research 122, 3843.Google Scholar
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