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Effectiveness of mid-infrared spectroscopy to predict fatty acid composition of Brown Swiss bovine milk

Published online by Cambridge University Press:  23 May 2011

M. De Marchi ,
M. Penasa ,
A. Cecchinato ,
M. Mele ,
P. Secchiari  and
G. Bittante
M. De Marchi
Affiliation:
Department of Animal Science, University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
M. Penasa*
Affiliation:
Department of Animal Science, University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
A. Cecchinato
Affiliation:
Department of Animal Science, University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
M. Mele
Affiliation:
Dipartimento di Agronomia e Gestione dell'Agroecosistema, University of Pisa, Via S. Michele degli Scalzi 2, 56124 Pisa, Italy
P. Secchiari
Affiliation:
Dipartimento di Agronomia e Gestione dell'Agroecosistema, University of Pisa, Via S. Michele degli Scalzi 2, 56124 Pisa, Italy
G. Bittante
Affiliation:
Department of Animal Science, University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
*
†E-mail: mauro.penasa@unipd.it
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Abstract

Mid-infrared spectroscopy (MIR) is used to predict fatty acid (FA) composition of individual milk samples (n = 267) of Brown Swiss cows. FAs were analyzed by gas chromatography as a reference method. Samples were scanned (4000 to 900 cm−1) by MIR, and predictive models were developed using modified partial least squares regressions with full cross-validation. The methods using a first derivative or multiplicative scatter corrected plus first derivative resulted, on average, in the best predictions. Coefficients of correlation between measured and predicted C8:0, C10:0, C12:0, C14:0, anteiso-C17:0, c9-C18:1, and medium- and long-chain FA, and saturated, monounsaturated and unsaturated FA ranged from 0.71 to 0.77, suggesting that prediction models can be implemented in milk recording schemes to routinely collect information on FA composition from the whole Brown Swiss population for breeding purposes.

Keywords

bovine milkfatty acidmid-infrared spectroscopyBrown Swiss
Type
Full Paper
Information
animal , Volume 5 , Issue 10 , 26 August 2011 , pp. 1653 - 1658
Copyright
Copyright © The Animal Consortium 2011

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References

Arnould, VMR, Soyeurt, H 2009. Genetic variability of milk fatty acids. Journal of Applied Genetics 50, 29–39.CrossRefGoogle ScholarPubMed
Bauman, DE, Lock, AL, Corl, BA, Ip, C, Salter, AM, Parodi, PW 2005. Milk fatty acids and human health: potential role of conjugated linoleic acid and trans fatty acids. In Ruminant physiology: digestion, metabolism and impact of nutritional on gene expression, immunology and stress (ed. K Sejrsen, T Hvelplund and MO Nielsen), pp. 523–555. Wageningen Academic Publishers, Wageningen, The Netherlands.Google Scholar
Bhattacharya, A, Banu, J, Rahman, M, Causey, J, Fernandes, G 2006. Biological effects of conjugated linoleic acids in health and disease. Journal of Nutritional Biochemistry 17, 789–810.CrossRefGoogle ScholarPubMed
Cecchinato, A, De Marchi, M, Gallo, L, Bittante, G, Carnier, P 2009. Mid-infrared spectroscopy predictions as indicator traits in breeding programs for enhanced coagulation properties of milk. Journal of Dairy Science 92, 5304–5313.CrossRefGoogle Scholar
Cecchinato, A, De Marchi, M, Penasa, M, Albera, A, Bittante, G 2011. The relevance of near-infrared reflectance spectroscopy predictions as indicator traits in breeding programs for enhanced beef quality. Journal of Animal Science, in press. doi:10.2527/jas.2010-3740.CrossRefGoogle Scholar
Chilliard, Y, Ferlay, A 2004. Dietary lipids and forages interactions on cow and goat milk fatty acid composition and sensory proprieties. Reproduction, Nutrition and Development 44, 467–492.CrossRefGoogle Scholar
Christie, WW 1982. A simple procedure of rapid transmethylation of glycerolipids and cholesteryl esters. Journal of Lipid Research 23, 1072–1075.CrossRefGoogle ScholarPubMed
Coates, J 2000. Interpretation of infrared spectra, a practical approach. In Encyclopedia of analytical chemistry (ed. RA Meyers), pp. 10815–10837. John Wiley & Sons, New York, NY, USA.Google Scholar
Coppa, M, Ferlay, A, Leroux, C, Jestin, M, Chilliard, Y, Martin, B, Andueza, D 2010. Prediction of milk fatty acid composition by near infrared reflectance spectroscopy. International Dairy Journal 20, 182–189.CrossRefGoogle Scholar
Dal Zotto, R, De Marchi, M, Cecchinato, A, Penasa, M, Cassandro, M, Carnier, P, Gallo, L, Bittante, G 2008. Reproducibility and repeatability of measures of milk coagulation properties and predictive ability of mid-infrared reflectance spectroscopy. Journal of Dairy Science 91, 4103–4112.CrossRefGoogle ScholarPubMed
De Marchi, M, Bonfatti, V, Cecchinato, A, Di Martino, G, Carnier, P 2009a. Prediction of protein composition of individual cow milk using mid-infrared spectroscopy. Italian Journal of Animal Science 8, 399–401.CrossRefGoogle Scholar
De Marchi, M, Fagan, CC, O'Donnell, CP, Cecchinato, A, Dal Zotto, R, Cassandro, M, Penasa, M, Bittante, G 2009b. Prediction of coagulation properties, titratable acidity, and pH of bovine milk using mid-infrared spectroscopy. Journal of Dairy Science 92, 423–432.CrossRefGoogle ScholarPubMed
DePeters, EJ, Medrano, JF, Reed, BA 1995. Fatty acid composition of milk fat from three breeds of dairy cattle. Canadian Journal of Animal Science 75, 267–269.CrossRefGoogle Scholar
German, JB, Gibson, RA, Krauss, RM, Nestel, P, Lamarche, B, van Staveren, WA, Steijns, JM, de Groot, LC, Lock, AL, Destaillats, F 2009. A reappraisal of the impact of dairy foods and milk fat on cardiovascular disease risk. European Journal of Nutrition 48, 191–203.CrossRefGoogle ScholarPubMed
Grummer, RR 1991. Effect of feed on the composition of milk fat. Journal of Dairy Science 74, 3244–3257.CrossRefGoogle ScholarPubMed
Haug, A, Hostmark, AT, Harstad, OM 2007. Bovine milk in human nutrition: a review. Lipids in Health and Disease 6, 25.CrossRefGoogle ScholarPubMed
Heuer, C, Luinge, HJ, Lutz, ETG, Schukken, YH, van der Maas, JH, Wilmink, H, Noordhuizen, JPTM 2001. Determination of acetone in cow milk by Fourier transform infrared spectroscopy for the detection of subclinical ketosis. Journal of Dairy Science 84, 575–582.CrossRefGoogle ScholarPubMed
Hewavitharana, AK, Brakel, BV 1997. Fourier transform infrared spectrometric method for rapid determination of casein in raw milk. Analyst (London) 122, 701–704.CrossRefGoogle Scholar
Hubert, M, Vanden Branden, K 2003. Robust methods for partial least squares regression. Journal of Chemometrics 17, 537–549.CrossRefGoogle Scholar
Jensen, RG 2002. The composition of bovine milk lipids: January 1995 to December 2000. Journal of Dairy Science 85, 295–350.CrossRefGoogle ScholarPubMed
Jensen, RG, Ferris, AM, Lammi-Keefe, CJ 1991. The composition of milk fat. Journal of Dairy Science 64, 3228–3243.CrossRefGoogle Scholar
Jørgensen, K, Næs, T 2004. A design and analysis strategy for situations with uncontrolled raw material variation. Journal of Chemometrics 18, 45–52.CrossRefGoogle Scholar
Kramer, JKGHernandez, M, Cruz-Hernandez, C, Kraft, J, Dugan, MER 2008. Combining results of two GC separations partly achieves determination of all cis- and trans-16:1, 18:1, 18:2 and 18:3 except CLA isomers of milk fat as demonstrated using Ag-ion SPE fractionation. Lipids 43, 259–273.CrossRefGoogle Scholar
Lefèvre, T, Subirade, M 2000. Interaction of β-lactoglobulin with phospholipids bilayers: a molecular level elucidation as revealed by infrared spectroscopy. International Journal of Biological Macromolecules 28, 59–67.CrossRefGoogle ScholarPubMed
Lynch, JM, Barbano, DM, Schweisthal, M, Fleming, JR 2006. Precalibration evaluation procedures for mid-infrared milk analyzers. Journal of Dairy Science 89, 2761–2774.CrossRefGoogle ScholarPubMed
Martens, H, Naes, T 1989. Methods for calibration. In Multivariate calibration (ed. H Martens and T Naes), Chapter 3, pp. 73–236. John Wiley & Sons Ltd., London, UK.Google Scholar
Mele, M 2009. Designing milk fat to improve healthfulness and functional properties of dairy products: from feeding strategies to a genetic approach. Italian Journal of Animal Science 8, 365–373.CrossRefGoogle Scholar
Mele, M, Dal Zotto, R, Cassandro, M, Conte, G, Serra, A, Buccioni, A, Bittante, G, 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, 392–400.CrossRefGoogle ScholarPubMed
Mensink, RP, Katan, MB 1992. Effect of dietary fatty acids on serum lipids and lipoproteins: a meta-analysis of 27 trials. Arteriosclerosis, Thrombosis, and Vascular Biology 12, 911–919.CrossRefGoogle ScholarPubMed
Pillonel, L, Luginbuhl, W, Picque, D, Schaller, E, Tabacchi, R, Bosset, JO 2003. Analytical methods for the determination of the geographic origin of Emmental cheese: mid- and near-infrared spectroscopy. European Food Research Technology 216, 174–178.CrossRefGoogle Scholar
Rutten, MJM, Bovenhuis, H, Hettinga, KA, van Valenberg, HJF, van Arendonk, JAM 2009. Predicting bovine milk fat composition using infrared spectroscopy based on milk samples collected in winter and summer. Journal of Dairy Science 92, 6202–6209.CrossRefGoogle Scholar
Shingfield, KJ, Ahvenjärvi, S, Toivonen, V, Ärölä, A, Nurmela, KVV, Huhtanen, P, Griinari J, M 2003. Effect of dietary fish oil on biohydrogenation of fatty acids and milk fatty acids content in cows. Animal Science 77, 165–179.CrossRefGoogle Scholar
Soyeurt, H, Dardenne, P, Lognay, G, Veselko, D, Mayeres, P, Gengler, N 2006. Estimating fatty acid content in cow milk using mid-infrared spectrometry. Journal of Dairy Science 89, 3690–3695.CrossRefGoogle ScholarPubMed
Soyeurt, H, Gillon, A, Vanderick, S, Mayeres, P, Bertozzi, C, Gengler, N 2007. Estimation of heritability and genetic correlations for the major fatty acids in bovine milk. Journal of Dairy Science 90, 4435–4442.CrossRefGoogle ScholarPubMed
Stoop, WM, Van Arendonk, JAM, Heck, JML, Van Valenberg, HJF, Bovenhuis, H 2008. Genetic parameters for major milk fatty acids and milk production traits of Dutch Holstein-Friesians. Journal of Dairy Science 91, 385–394.CrossRefGoogle ScholarPubMed
Williams, CM 2000. Dietary fatty acids and human health. Annales de Zootechnie 49, 165–180.CrossRefGoogle Scholar
Williams, PC 2001. Implementation of near-infrared technology. In Near infrared technology in the agriculture and food industries (ed. PC Williams and K Norris), 2nd edition, pp. 145–169. American Association of Cereal Chemists, St Paul, MN, USA.Google Scholar
Williams, P 2003. Near-infrared technology – getting the best out of light. A short course in the practical implementation of near infrared spectroscopy for the user, 1st edition. PDK Projects Inc., Nanaimo, Canada.Google Scholar