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Inferring individual cow effects, dairy system effects and feeding effects on latent variables underlying milk protein composition and cheese-making traits in dairy cattle

Published online by Cambridge University Press:  10 November 2017

Christos Dadousis ,
Claudio Cipolat-Gotet ,
Stefano Schiavon ,
Giovanni Bittante  and
Alessio Cecchinato
Christos Dadousis
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
Claudio Cipolat-Gotet
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
Stefano Schiavon
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
Giovanni Bittante
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
Alessio Cecchinato*
Affiliation:
Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
*
*For correspondence; e-mail: alessio.cecchinato@unipd.it
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Abstract

We examined the latent structure of 26 cheese related phenotypes in dairy cattle. Traits related to milk yield and quality (8 traits), milk protein fractions (8 traits), coagulation and curd firmness indicators (CF, 5 traits) and cheese-making phenotypes (cheese yields (%CY) and nutrient recoveries in the curd (REC), 5 traits) were analysed through multivariate factor analysis (MFA) using a varimax rotation. All phenotypes were measured in 1264 Brown Swiss cows. Ten mutual orthogonal, latent variables (factors; Fs) were obtained explaining 74% of the original variability. These Fs captured basic concepts of the cheese-making process. More precisely, the first 4 Fs, sorted by variance explained, were able to capture the underlying structure of the CY percentage (F1: %CY), the CF process with time (F2: CFt), the milk and solids yield (F3: Yield) and the presence of nitrogen (N) in the cheese (F4: Cheese N). Moreover, 4 Fs (F5: as1-β-CN, F7: κ-β-CN, F8: as2-CN and F9: as1-CN-Ph) were related to the basic milk caseins and 1 factor was associated with the α-LA whey protein (F10: α-LA). A factor describing udder health status (F6: Udder health), mainly loaded on lactose, other nitrogen compounds in the milk and SCS, was also obtained. Further, we inferred the effects of some potential sources of variation (e.g. stage of lactation and parity) including feeding and management systems. Stage of lactation had a significant effect for 7 of the 10 Fs, followed by parity of the cow (3 Fs), dairy system and feeding (3 Fs). Our work demonstrates the usefulness of MFA in reducing a large number of variables to a few latent factors with biological meaning and representing groups of traits that describe a complex process like cheese-making. Such an approach would be a valuable tool for studying the influence of different production environments and individual animal factors on protein composition and cheese-making related traits.

Keywords

Multivariate factor analysismilk proteincoagulationcurd firmnessindividual cheese yield
Type
Research Article
Information
Journal of Dairy Research , Volume 85 , Issue 1 , February 2018 , pp. 87 - 97
Copyright
Copyright © Hannah Dairy Research Foundation 2017 

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References

Ali, A & Shook, G 1980 An optimum transformation for somatic cell concentration in milk. Journal of Dairy Science 63 487–490 CrossRefGoogle Scholar
Bergamaschi, M, Biasioli, F, Cappellin, L, Cecchinato, A, Cipolat-Gotet, C, Cornu, A, Gasperi, F, Martin, B & Bittante, G 2015 Proton transfer reaction time-of-flight mass spectrometry: a high-throughput and innovative method to study the influence of dairy system and cow characteristics on the volatile compound fingerprint of cheeses. Journal of Dairy Science 98 8414–8427 Google Scholar
Bittante, G, Cipolat-Gotet, C & Cecchinato, A 2013a Genetic parameters of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process. Journal of Dairy Science 96 7966–7979 CrossRefGoogle ScholarPubMed
Bittante, G, Contiero, B & Cecchinato, A 2013b Prolonged observation and modelling of milk coagulation, curd firming, and syneresis. International Dairy Journal 29 115–123 CrossRefGoogle Scholar
Bittante, G, Cipolat-Gotet, C, Malchiodi, F, Sturaro, E, Tagliapietra, F, Schiavon, S & Cecchinato, A 2015 Effect of dairy farming system, herd, season, parity, and days in milk on modeling of the coagulation, curd firming, and syneresis of bovine milk. Journal of Dairy Science 98 2759–2774 CrossRefGoogle ScholarPubMed
Bobe, G, Beitz, D, Freeman, A & Lindberg, G 1999 Effect of milk protein genotypes on milk protein composition and its genetic parameter estimates. Journal of Dairy Science 82 2797–2804 Google Scholar
Bollen, K 1989 Structural Equations with Latent Variables. John Wiley & Sons, New York Google Scholar
Bonfatti, V, Grigoletto, L, Cecchinato, A, Gallo, L & Carnier, P 2008 Validation of a new reversed-phase high-performance liquid chromatography method for separation and quantification of bovine milk protein genetic variants. Journal of Chromatography A. 1195 101–106 Google Scholar
Bonfatti, V, Di Martino, G, Cecchinato, A, Vicario, D & Carnier, P 2010 Effects of β-κ-casein (CSN2-CSN3) haplotypes and β-lactoglobulin (BLG) genotypes on milk production traits and detailed protein composition of individual milk of simmental cows. Journal of Dairy Science 93 3797–3808 CrossRefGoogle ScholarPubMed
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 5183–5193 CrossRefGoogle ScholarPubMed
Cecchinato, A & Bittante, G 2016 Genetic and environmental relationships of different measures of individual cheese yield and curd nutrients recovery with coagulation properties of bovine milk. Journal of Dairy Science 99 1975–1989 CrossRefGoogle ScholarPubMed
Cecchinato, A, Cipolat-Gotet, C, Casellas, J, Penasa, M, Rossoni, A & Bittante, G 2013 Genetic analysis of rennet coagulation time, curd-firming rate, and curd firmness assessed over an extended period using mechanical and near-infrared instruments. Journal of Dairy Science 96 50–62 Google Scholar
Cipolat-Gotet, C, Cecchinato, A, De Marchi, M & Bittante, G 2013 Factors affecting variation of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process. Journal of Dairy Science 96 7952–7965 Google Scholar
Conte, G, Serra, A, Cremonesi, P, Chessa, S, Castiglioni, B, Cappucci, A, Bulleri, E & Mele, M 2016 Investigating mutual relationship among milk fatty acids by multivariate factor analysis in dairy cows. Livestock Science 188 124–132 Google Scholar
Dadousis, C, Cipolat-Gotet, C, Bittante, G & Cecchinato, A 2017a Inferring genetic parameters on latent variables underlying milk yield and quality, protein composition, curd firmness and cheese-making traits in dairy cattle. Animal. doi: 10.1017/S1751731117001616 Google Scholar
Dadousis, C, Pegolo, S, Rosa, GJM, Bittante, G & Cecchinato, A 2017b Genome-wide association and pathway-based analysis using latent variables related to milk protein composition and cheesemaking traits in dairy cattle. Journal of Dairy Science 100 9085–9102 Google Scholar
Dziuban, CD & Shirkey, EC 1974 When is a correlation matrix appropriate for factor analysis? Some decision rules. Psychological Bulletin 81 358 CrossRefGoogle Scholar
Ikonen, T, Morri, S, Tyrisevä, A, 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 87 458–467 Google Scholar
Kaiser, HF & Rice, J 1974 Little jiffy, Mark IV. Educational and Psychological Measurement 34 111–117 Google Scholar
Macciotta, NPP, Cecchinato, A, Mele, M & Bittante, G 2012 Use of multivariate factor analysis to define new indicator variables for milk composition and coagulation properties in brown Swiss cows. Journal of Dairy Science 95 7346–7354 Google Scholar
Manca, M, Serdino, J, Gaspa, G, Urgeghe, P, Ibba, I, Contu, M, Fresi, P & Macciotta, N 2016 Derivation of multivariate indices of milk composition, coagulation properties, and individual cheese yield in dairy sheep. Journal of Dairy Science 99 4547–4557 Google Scholar
Mele, M, Macciotta, N, Cecchinato, A, Conte, G, Schiavon, S & Bittante, G 2016 Multivariate factor analysis of detailed milk fatty acid profile: Effects of dairy system, feeding, herd, parity, and stage of lactation. Journal of Dairy Science 99 9820–9833 Google Scholar
Miglior, F, Sewalem, A, Jamrozik, J, Bohmanova, J, Lefebvre, D & Moore, R 2007 Genetic analysis of milk urea nitrogen and lactose and their relationships with other production traits in Canadian Holstein cattle. Journal of Dairy Science 90 2468–2479 CrossRefGoogle ScholarPubMed
NRC 2001 Nutrient Requirements of Dairy Cattle, 7th rev. Washington, DC: Natl. Acad. Press Google Scholar
Ostersen, S, Foldager, J & Hermansen, JE 1997 Effects of stage of lactation, milk protein genotype and body condition at calving on protein composition and renneting properties of bovine milk. Journal of Dairy Research 64 207–219 Google Scholar
R Core Team 2013 R: A Language and Environment for Statistical Computing. http://www.R-project.org/ Google Scholar
Revelle, W 2014 Psych: Procedures for Personality and Psychological Research. Evanston: Northwestern University, R Package Version. 1Google Scholar
Shuster, D, Harmon, R, Jackson, J & Hemken, R 1991 Suppression of milk production during endotoxin-induced mastitis. Journal of Dairy Science 74 3763–3774 Google Scholar
Stocco, G, Cipolat-Gotet, C, Bobbo, T, Cecchinato, A & Bittante, G 2016 Herd productivity and breed of cows affect milk composition, coagulation properties and curd firming and syneresis modeling. Journal of Dairy Science 100 129–145 Google Scholar
Sturaro, E, Cocca, G, Gallo, L, Mrad, M & Ramanzin, M 2009 Livestock systems and farming styles in eastern Italian Alps: An on-farm survey. Italian Journal of Animal Science 8 541–554 CrossRefGoogle Scholar
Sturaro, E, Marchiori, E, Cocca, G, Penasa, M, Ramanzin, M & Bittante, G 2013 Dairy systems in mountainous areas: Farm animal biodiversity, milk production and destination, and land use. Livestock Science 158 157–168 Google Scholar
Todaro, M, Scatassa, ML & Giaccone, P 2005 Multivariate factor analysis of girgentana goat milk composition. Italian Journal of Animal Science 4 403–410 Google Scholar
Vacca, G, Paschino, P, Dettori, M, Bergamaschi, M, Cipolat-Gotet, C, Bittante, G & Pazzola, M 2016 Environmental, morphological, and productive characterization of sardinian goats and use of latent explanatory factors for population analysis. Journal of Animal Science 94 3947–3957 Google Scholar
Walsh, S, Buckley, F, Berry, D, Rath, M, Pierce, K, Byrne, N & Dillon, P 2007 Effects of breed, feeding system, and parity on udder health and milking characteristics. Journal of Dairy Science 90 5767–5779 CrossRefGoogle ScholarPubMed
Yang, L, Yang, Q, Yi, M, Pang, Z & Xiong, B 2013 Effects of seasonal change and parity on raw milk composition and related indices in Chinese Holstein cows in northern China. Journal of Dairy Science 96 6863–6869 Google Scholar