Hostname: page-component-8448b6f56d-m8qmq Total loading time: 0 Render date: 2024-04-19T12:00:30.825Z Has data issue: false hasContentIssue false

Heritability and repeatability of milk coagulation properties predicted by mid-infrared spectroscopy during routine data recording, and their relationships with milk yield and quality traits

Published online by Cambridge University Press:  02 July 2013

F. Tiezzi
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
D. Pretto
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
M. De Marchi
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
M. Penasa
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
M. Cassandro*
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
Get access

Abstract

The aim of this study was to estimate (co)variance components for milk coagulation properties (MCP) predicted by mid-infrared spectroscopy (MIRS) during routine milk recording, and to assess their relationships with yield and quality traits. A total of 63 470 milk samples from Holstein-Friesian cows were analyzed for MCP, pH and quality characteristics using MIRS. Casein to protein and protein to fat ratios were calculated from information obtained by MIRS. Records were collected across 1 year on 16 089 cows in 345 herds. The model used for genetic analysis included fixed effects of parity and stage of lactation, and random effects of herd-test-day, cow permanent environmental, animal additive genetic and residual. (Co)variance components were assessed in a Bayesian framework using the Gibbs Sampler. Estimates of heritabilities were consistent with those reported in the literature, being moderate for MCP (0.210 and 0.238 for rennet coagulation time (RCT) and curd firmness (a30), respectively), milk contents (0.213 to 0.333) and pH (0.262), and low for somatic cell score (0.093) and yield traits (0.098 to 0.130). Repeatabilities were 0.391 and 0.434 for RCT and a30, respectively, and genetic correlations were generally low, with estimates greater than 0.30 (in absolute value) only for a30 with fat, protein and casein contents. Overall, results suggest that genetic evaluation for MCP predicted by MIRS is feasible at population level, and several repeated measures per cow during a lactation are required to estimate reliable breeding values for coagulation traits.

Type
Breeding and genetics
Copyright
Copyright © The Animal Consortium 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aleandri, R, Schneider, JC, Buttazzoni, LG 1989. Evaluation of milk for cheese production based on milk characteristics and Formagraph measures. Journal of Dairy Science 72, 19671975.Google Scholar
Bonfatti, V, Cecchinato, A, Gallo, L, Blasco, A, Carnier, P 2011. Genetic analysis of detailed milk protein composition and coagulation properties in Simmental cattle. Journal of Dairy Science 94, 51835193.Google Scholar
Bynum, DG, Olson, NF 1982. Influence of curd firmness at cutting on yield and recovery of milk constituents. Journal of Dairy Science 65, 22812290.Google Scholar
Cassandro, M, Comin, A, Ojala, M, Dal Zotto, R, De Marchi, M, Gallo, L, Carnier, P, Bittante, G 2008. Genetic parameters of milk coagulation properties and their relationships with milk yield and quality traits in Italian Holstein cows. Journal of Dairy Science 91, 371376.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, 53045313.Google Scholar
Cipolat-Gotet, C, Cecchinato, A, De Marchi, M, Penasa, M, Bittante, G 2012. Comparison between mechanical and near-infrared methods for assessing coagulation properties of bovine milk. Journal of Dairy Science 95, 68066819.Google Scholar
Comin, A, Cassandro, M, Chessa, S, Ojala, M, Dal Zotto, R, De Marchi, M, Carnier, P, Gallo, L, Pagnacco, G, Bittante, G 2008. Effects of composite β- and κ-casein genotypes on milk coagulation, quality, and yield traits in Italian Holstein cows. Journal of Dairy Science 91, 40224027.CrossRefGoogle ScholarPubMed
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, 41034112.CrossRefGoogle ScholarPubMed
De Marchi, M, Dal Zotto, R, Cassandro, M, Bittante, G 2007. Milk coagulation ability of five dairy cattle breeds. Journal of Dairy Science 90, 39863992.CrossRefGoogle ScholarPubMed
De Marchi, M, Toffanin, V, Cassandro, M, Penasa, M 2013. Prediction of coagulating and noncoagulating milk samples using mid-infrared spectroscopy. Journal of Dairy Science 96, 47074715.Google Scholar
De Marchi, M, Penasa, M, Tiezzi, F, Toffanin, V, Cassandro, M 2012. Prediction of milk coagulation properties by Fourier transform mid-infrared spectroscopy (FTMIR) for genetic purposes, herd management and dairy profitability. Proceedings of the 38th International Committee for Animal Recording (ICAR) Meeting, 28 May – 1 June 2012, Cork, Ireland. http://www.icar.org/Cork_2012/Manuscripts/Published/Cassandro.pdf.Google Scholar
De Marchi, M, Penasa, M, Cecchinato, A, Mele, M, Secchiari, P, Bittante, G 2011. Effectiveness of mid-infrared spectroscopy to predict fatty acid composition of Brown Swiss bovine milk. Animal 5, 16531658.CrossRefGoogle ScholarPubMed
De Marchi, M, Fagan, CC, O'Donnell, CP, Cecchinato, A, Dal Zotto, R, Cassandro, M, Penasa, M, Bittante, G 2009. Prediction of coagulation properties, titratable acidity, and pH of bovine milk using mid-infrared spectroscopy. Journal of Dairy Science 92, 423432.CrossRefGoogle ScholarPubMed
Formaggioni, P, Sandri, S, Franceschi, P, Malacarne, M, Mariani, P 2005. Milk acidity, curd firming time, curd firmness and protein and fat losses in the Parmigiano-Reggiano cheesemaking. Italian Journal of Animal Science 4 (suppl. 2), 239241.Google Scholar
Geary, U, Lopez-Villalobos, N, Garrick, DJ, Shalloo, L 2010. Development and application of a processing model for the Irish dairy industry. Journal of Dairy Science 93, 50915100.Google Scholar
Ikonen, T, Morri, S, Tyrisevä, A-M, Ruottinen, O, Ojala, M 2004. Genetic and phenotypic correlations between milk coagulation properties, milk production traits, somatic cell count, casein content and pH of milk. Journal of Dairy Science 87, 458467.Google Scholar
Jensen, HB, Holland, JW, Poulsen, NA, Larsen, LB 2012. Milk protein genetic variants and isoforms identified in bovine milk representing extremes in coagulation properties. Journal of Dairy Science 95, 28912903.Google Scholar
Johnson, ME, Chen, CM, Jaeggi, JJ 2001. Effect of rennet coagulation time on composition, yield, and quality of reduced-fat Cheddar cheese. Journal of Dairy Science 84, 10271033.Google Scholar
Klei, L, Yun, J, Sapru, A, Lynch, J, Barbano, D, Sears, P, Galton, D 1998. Effects of milk somatic cell count on cottage cheese yield and quality. Journal of Dairy Science 81, 12051213.CrossRefGoogle ScholarPubMed
Kübarsepp, I, Henno, M, Viinalass, H, Sabre, D 2005. Effect of κ-casein and β-lactoglobulin gentoypes on the milk rennet coagulation properties. Agronomy Research 3, 5564.Google Scholar
Lindström, UB, Antila, V, Syväjärvi, J 1984. A note on some genetic and non-genetic factors affecting clotting time of Ayrshire milk. Acta Agriculturae Scandinavica 34, 349355.CrossRefGoogle Scholar
López, MB, Lomholt, SB, Qvist, KB 1998. Rheological properties and cutting time of rennet gels. Effect of pH and enzyme concentration. International Dairy Journal 8, 289293.Google Scholar
Nájera, AI, de Renobales, M, Barron, LJR 2003. Effects of pH, temperature, CaCl2 and enzyme concentrations on the rennet-clotting properties of milk: a multifactorial study. Food Chemistry 80, 345352.CrossRefGoogle Scholar
Okigbo, LM, Richardson, GH, Brown, RJ, Ernstrom, CA 1985. Effects of pH, calcium chloride, and chymosin concentration on coagulation properties of abnormal and normal milk. Journal of Dairy Science 68, 25272533.Google Scholar
Penasa, M, Cassandro, M, Pretto, D, De Marchi, M, Comin, A, Chessa, S, Dal Zotto, R, Bittante, G 2010. Short communication: influence of composite casein genotypes on additive genetic variation of milk production traits and coagulation properties in Holstein-Friesian cows. Journal of Dairy Science 93, 33463349.Google Scholar
Politis, I, Ng-Kwai-Hang, KF 1988. Effects of somatic cell counts and milk composition on the coagulating properties of milk. Journal of Dairy Science 71, 17401746.Google Scholar
Pretto, D, López-Villalobos, N, Penasa, M, Cassandro, M 2012. Genetic response for milk production traits, somatic cell score, acidity and coagulation properties in Italian Holstein-Friesian population under current and alternative selection indices and breeding objectives. Livestock Science 150, 5966.CrossRefGoogle Scholar
Pretto, D, De Marchi, M, Penasa, M, Cassandro, M 2013. Effect of milk composition and coagulation traits on Grana Padano cheese yield under field conditions. Journal of Dairy Research 80, 15.Google Scholar
Pretto, D, Kaart, T, Vallas, M, Jõudu, I, Henno, M, Ancilotto, L, Cassandro, M, Pärna, E 2011. Relationships between milk coagulation property traits analyzed with different methodologies. Journal of Dairy Science 94, 43364346.Google Scholar
Soyeurt, H, Dardenne, P, Dehareng, F, Lognay, G, Veselko, D, Marlier, M, Bertozzi, C, Mayeres, P, Gengler, N 2006. Estimating fatty acid content in cow milk using mid-infrared spectrometry. Journal of Dairy Science 89, 36903695.Google Scholar
Tyrisevä, A-M, Ikonen, T, Ojala, M 2003. Repeatability estimates for milk coagulation traits and non-coagulation of milk in Finnish Ayrshire cows. Journal of Dairy Research 70, 9198.Google Scholar
Tyrisevä, A-M, Vahlsten, T, Ruottinen, O, Ojala, M 2004. Noncoagulation of milk in Finnish Ayrshire and Holstein-Friesian cows and effect of herds on milk coagulation ability. Journal of Dairy Science 87, 39583966.CrossRefGoogle ScholarPubMed
Vallas, M, Bovenhuis, H, Kaart, T, Pärna, K, Kiiman, H, Pärna, E 2010. Genetic parameters for milk coagulation properties in Estonian Holstein cows. Journal of Dairy Science 93, 37893796.CrossRefGoogle ScholarPubMed
Vallas, M, Kaart, T, Värv, S, Pärna, K, Jõudu, I, Viinalass, H, Pärna, E 2012. Composite β-κ-casein genotypes and their effect on composition and coagulation of milk from Estonian Holstein cows. Journal of Dairy Science 95, 67606769.CrossRefGoogle ScholarPubMed