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Genetic parameters of total milk yield and factors describing the shape of lactation curve in dairy buffaloes

Published online by Cambridge University Press:  07 November 2011

Rúsbel R Aspilcueta-Borquis
Affiliation:
Department of Animal Science, São Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil, 14884 900
Fernando Baldi
Affiliation:
Department of Animal Science, São Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil, 14884 900
Francisco R Araujo Neto
Affiliation:
Department of Animal Science, São Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil, 14884 900
Lucia G Albuquerque
Affiliation:
Department of Animal Science, São Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil, 14884 900 Conselho Nacional de Desenvolvimento Científico e Tecnologico (CNPq) and Instituto Nacional de Ciência e Tecnologia – Ciência Animal (INCT- CA), Viçosa, MG, Brazil, 36570 000
Milthon Muñoz-Berrocal
Affiliation:
Universidad Nacional Agraria de la Selva, Aptdo. 156, UNAS-Tingo Maria-Peru
Humberto Tonhati*
Affiliation:
Department of Animal Science, São Paulo State University (FCAV/UNESP), Jaboticabal, SP, Brazil, 14884 900 Conselho Nacional de Desenvolvimento Científico e Tecnologico (CNPq) and Instituto Nacional de Ciência e Tecnologia – Ciência Animal (INCT- CA), Viçosa, MG, Brazil, 36570 000
*
*For correspondence; e-mail: [email protected]

Abstract

The objective of this study was to apply factor analysis to describe lactation curves in dairy buffaloes in order to estimate the phenotypic and genetic association between common latent factors and cumulative milk yield. A total of 31 257 monthly test-day milk yield records from buffaloes belonging to herds located in the state of São Paulo were used to estimate two common latent factors, which were then analysed in a multi-trait animal model for estimating genetic parameters. Estimates of (co)variance components for the two common latent factors and cumulated 270-d milk yield were obtained by Bayesian inference using a multiple trait animal model. Contemporary group, number of milkings per day (two levels) and age of buffalo cow at calving (linear and quadratic) as covariate were included in the model as fixed effects. The additive genetic, permanent environmental and residual effects were included as random effects. The first common latent factor (F1) was associated with persistency of lactation and the second common latent factor (F2) with the level of production in early lactation. Heritability estimates for F1 and F2 were 0·12 and 0·07, respectively. Genetic correlation estimates between F1 and F2 with cumulative milk yield were positive and moderate (0·63 and 0·52). Multivariate statistics employing factor analysis allowed the extraction of two variables (latent factors) that described the shape of the lactation curve. It is expected that the response to selection to increase lactation persistency is higher than the response obtained from selecting animals to increase lactation peak. Selection for higher total milk yield would result in a favourable correlated response to increase the level of production in early lactation and the lactation persistency.

Type
Research Article
Copyright
Copyright © Proprietors of Journal of Dairy Research 2011

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