Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-26T19:05:53.677Z Has data issue: false hasContentIssue false

Genetic parameters for milk mineral content and acidity predicted by mid-infrared spectroscopy in Holstein–Friesian cows

Published online by Cambridge University Press:  13 January 2015

V. Toffanin
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Legnaro, PD, Italy
M. Penasa*
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Legnaro, PD, Italy
S. McParland
Affiliation:
Livestock Systems Research Department, Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland
D. P. Berry
Affiliation:
Animal and Bioscience Research Department, Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland
M. Cassandro
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Legnaro, PD, Italy
M. De Marchi
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Legnaro, PD, Italy
*
Corresponding author: E-mail: [email protected]
Get access

Abstract

The aim of the present study was to estimate genetic parameters for calcium (Ca), phosphorus (P) and titratable acidity (TA) in bovine milk predicted by mid-IR spectroscopy (MIRS). Data consisted of 2458 Italian Holstein−Friesian cows sampled once in 220 farms. Information per sample on protein and fat percentage, pH and somatic cell count, as well as test-day milk yield, was also available. (Co)variance components were estimated using univariate and bivariate animal linear mixed models. Fixed effects considered in the analyses were herd of sampling, parity, lactation stage and a two-way interaction between parity and lactation stage; an additive genetic and residual term were included in the models as random effects. Estimates of heritability for Ca, P and TA were 0.10, 0.12 and 0.26, respectively. Positive moderate to strong phenotypic correlations (0.33 to 0.82) existed between Ca, P and TA, whereas phenotypic weak to moderate correlations (0.00 to 0.45) existed between these traits with both milk quality and yield. Moderate to strong genetic correlations (0.28 to 0.92) existed between Ca, P and TA, and between these predicted traits with both fat and protein percentage (0.35 to 0.91). The existence of heritable genetic variation for Ca, P and TA, coupled with the potential to predict these components for routine cow milk testing, imply that genetic gain in these traits is indeed possible.

Type
Research Article
Copyright
© The Animal Consortium 2015 

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

Bastin, C, Soyeurt, H and Gengler, N 2013. Genetic parameters of milk production traits and fatty acid contents in milk for Holstein cows in parity 1–3. Journal of Animal Breeding and Genetics 130, 118127.CrossRefGoogle ScholarPubMed
Caroli, AM, Poli, A, Ricotta, D, Banfi, G and Cocchi, D 2011. Invited review: dairy intake and bone health: a viewpoint from the state of the art. Journal of Dairy Science 94, 52495262.CrossRefGoogle Scholar
Cashman, KD 2011. Macroelements, nutritional significance. In Encyclopedia of dairy sciences, 2nd edition (ed. JW Fuquay, PF Fox and PLH McSweeney), pp. 925932. Academic Press, San Diego, CA, USA.CrossRefGoogle Scholar
Cashman, KD and Flynn, A 2003. Sodium effects on bone and calcium metabolism. In Nutritional aspects of Bone Health (ed. S New and JP Bonjour), pp. 267289. Royal Society of Chemistry, London, UK.Google Scholar
Cassandro, M, Comin, A, Ojala, M, Dal Zotto, R, De Marchi, M, Gallo, L, Carnier, P and 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 and 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.CrossRefGoogle Scholar
Cecchinato, A, Penasa, M, De Marchi, M, Gallo, L, Bittante, G and Carnier, P 2011. Genetic parameters of coagulation properties, milk yield, quality, and acidity estimated using coagulating and noncoagulating milk information in brown swiss and Holstein−Friesian cows. Journal of Dairy Science 94, 42054213.CrossRefGoogle ScholarPubMed
Colinet, FG, Soyeurt, H, Anceau, C, Vanlierde, A, Keyen, N, Dardenne, P, Gengler, N and Sindic, M 2010. Potential estimation of titratable acidity in cow milk using mid-infrared spectrometry. Proceedings of the 37th International Committee for Animal Recording (ICAR) Meeting, 31 May−4 June, Riga, Latvia. Retrieved May 15, 2014, from http://www.icar.org/Documents/Riga_2010/ppt/Colinet.pdf Google Scholar
De Marchi, M, Dal Zotto, R, Cassandro, M and 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 and Penasa, M 2014. Invited review: mid-infrared spectroscopy as phenotyping tool for milk traits. Journal of Dairy Science 97, 11711186.CrossRefGoogle ScholarPubMed
De Marchi, M, Bittante, G, Dal Zotto, R, Dalvit, C and Cassandro, M 2008. Effect of Holstein−Friesian and brown Swiss breeds on quality of milk and cheese. Journal of Dairy Science 91, 40924102.CrossRefGoogle Scholar
De Marchi, M, Fagan, CC, O'Donnell, CP, Cecchinato, A, Dal Zotto, R, Cassandro, M, Penasa, M and 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
Fossa, E, Pecorari, M, Sandri, S, Tosi, F and Mariani, P 1994. Il ruolo del contenuto in caseina del latte nella produzione del parmigiano-reggiano: composizione chimica, caratteristiche di coagulazione e comportamento tecnologico-caseario del latte. Scienza e Tecnica Lattiero Casearia 45, 519535.Google Scholar
Gilmour, AR, Gogel, BJ, Cullis, BR and Thompson, R 2009. ASReml User Guide Release 3.0 VSN International Ltd, Hemel Hempstead, HP1 1ES, UK. www.vsni.co.uk Google Scholar
Hansen, JV, Friggens, NC and Højsgaard, S 2006. The influence of breed and parity on milk yield, and milk yield acceleration curves. Livestock Science 104, 5362.CrossRefGoogle Scholar
Ikonen, T, Morri, S, Tyrisevä, AM, Ruottinen, O and 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.CrossRefGoogle Scholar
Kondyli, E, Katsiari, MC and Voutsinas, LP 2007. Variations of vitamin and mineral contents in raw goat milk of the indigenous Greek breed during lactation. Food Chemistry 100, 226230.CrossRefGoogle Scholar
Kume, S and Tanabe, S 1993. Effect of parity on colostral mineral concentrations of Holstein cows and value of colostrum as a mineral source for newborn calves. Journal of Dairy Science 76, 16541660.CrossRefGoogle ScholarPubMed
Kume, S, Yamamoto, E, Kudo, T, Toharmat, T and Nonaka, I 1998. Effect of parity on mineral concentration in milk and plasma of Holstein cows during early lactation. Asian-Australasian Journal of Animal Sciences 11, 133138.CrossRefGoogle Scholar
Malacarne, M, Franceschi, P, Formaggioni, P, Sandri, S, Mariani, P and Summer, A 2013. Influence of micellar calcium and phosphorus on rennet coagulation properties of cows milk. Journal of Dairy Research 81, 18.Google ScholarPubMed
Mariani, P, Bonatti, P and Pecorari, M 1989. Il latte ad acidità anomala. iv. fosforo solubile, cloruri e tipi di latte ipoacido. Scienza e Tecnica Lattiero Casearia 40, 215225.Google Scholar
Penasa, M, Tiezzi, F, Sturaro, A, Cassandro, M and De Marchi, M 2014. A comparison of the predicted coagulation characteristics and composition of milk from multi-breed herds of Holstein−Friesian, Brown Swiss and Simmental cows. International Dairy Journal 35, 610.CrossRefGoogle Scholar
Pretto, D, De Marchi, M, Penasa, M and Cassandro, M 2013. Effect of milk composition and coagulation traits on grana padano cheese yield under field conditions. Journal of Dairy Research 80, 15.CrossRefGoogle ScholarPubMed
Pretto, D, Kaart, T, Vallas, M, Jõudu, I, Henno, M, Ancilotto, L, Cassandro, M and Pärna, E 2011. Relationships between milk coagulation property traits analyzed with different methodologies. Journal of Dairy Science 94, 43364346.CrossRefGoogle ScholarPubMed
Rendel, JM and Robertson, A 1950. Estimation of genetic gain in milk yield by selection in a closed herd of dairy cattle. Journal of Genetics 50, 18.CrossRefGoogle Scholar
Romo, GA, Kellems, RO, Powell, K and Wallentine, V 1991. Some blood minerals and hormones in cows fed variable mineral levels and ionic balance. Journal of Dairy Science 74, 30683077.CrossRefGoogle ScholarPubMed
Şahan, N, Say, D and Kaçar, A 2005. Changes in chemical and mineral contents of Awassi ewes milk during lactation. Turkish Journal of Veterinary and Animal Sciences 29, 589593.Google Scholar
Shappell, NW, Herbein, JH, Deftos, L and Aiello, RJ 1987. Effects of dietary calcium and age on parathyroid hormone, calcitonin and serum and milk minerals in periparturient dairy cow. The Journal of Nutrition 117, 201207.CrossRefGoogle ScholarPubMed
Soyeurt, H, Bruwier, D, Gengler, N, Romnee, JM and Dardenne, P 2008a. Potential estimation of minerals content in cow milk using mid-infrared spectrometry. Proceedings of the 36th International Committee for Animal Recording (ICAR) Session and Interbull Meeting, 16−20 June, Niagara Falls. Retrieved May 5, 2014, from http://www.icar.org/niagara/Presentations/5%20Friday/WS%203/2%20-%20Soyeurt%20Minerals.pdf Google Scholar
Soyeurt, H, Arnould, VMR, Bruwier, D, Dardenne, P, Romnee, JM and Gengler, N 2008b. Relationship between lactoferrin, minerals, and somatic cells in bovine milk. Journal of Dairy Science 91 (E-suppl. 1), 15421543.Google Scholar
Soyeurt, H, Bruwier, D, Romnee, JM, Gengler, N, Bertozzi, C, Veselko, D and Dardenne, P 2009. Potential estimation of major mineral contents in cow milk using mid-infrared spectrometry. Journal of Dairy Science 92, 24442454.CrossRefGoogle ScholarPubMed
Tiezzi, F, Pretto, D, De Marchi, M, Penasa, M and Cassandro, M 2013. 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. Animal 7, 15921599.CrossRefGoogle ScholarPubMed
Toffanin, V, De Marchi, M, Lopez-Villalobos, N and Cassandro, M 2015. Effectiveness of mid-infrared spectroscopy for prediction of the contents of calcium and phosphorus, and titratable acidity of milk and their relationship with milk quality and coagulation properties. International Dairy Journal 41, 6873.CrossRefGoogle Scholar
Van de Braak, AE and Van’t Klooster, ATH 1987. Effect of calcium and magnesium intakes and feeding level during the dry period on bone resorption in dairy cows at parturition. Research in Veterinary Sciences 43, 712.CrossRefGoogle Scholar
Van Hulzen, KJE, Sprong, RC, van der Meer, R and Van Arendonk, JAM 2009. Genetic and nongenetic variation in concentration of selenium, calcium, potassium, zinc, magnesium, and phosphorus in milk of Dutch Holstein−Friesian cows. Journal of Dairy Science 92, 57545759.CrossRefGoogle ScholarPubMed