Persistency of lactation using random regression models and different fixed regression modeling approaches

Abstract

-Milk yield test-day records on the first three lactations of 25,500 Holstein cows were used to estimate genetic parameters and predict breeding values for nine measures of persistency and 305-d milk yield in a random regression animal model using two criteria to define the fixed regression. Legendre polynomials of fourth and fifth orders were used to model the fixed and random regressions of lactation curves. The fixed regressions were adjusted for average milk yield on populations (single) or subpopulations (multiple) formed by cows that calved at the same age and in the same season. Akaike Information (AIC) and Bayesian Information (BIC) criteria indicated that models with multiple regression lactation curves had the best fit to test-day milk records of first lactations, while models with a single regression curve had the best fit for the second and third lactations. Heritability and genetic correlation estimates between persistency and milk yield differed significantly depending on the lactation order and the measures of persistency used. These parameters did not differ significantly depending on the criteria used for defining the fixed regressions for lactation curves. In general, the heritability estimates were higher for first (0.07 to 0.43), followed by the second (0.08 to 0.21) and third (0.04 to 0.10) lactation. The rank of sires resulting from the processes of genetic evaluation for milk yield or persistency using random regression models differed according to the criteria used for determining the fixed regression of lactation curve.

Valores econômicos para as características de produção, funcionais e de fertilidade em sistemas de produção de leite no Sul do Brasil

“…A phenotypic and genetic (co)variance matrix (table III), positive defined (Van Der Werf, 1999), was estimated using the phenotypic and genetic parameters from national and international literature (Andrade et al, 2007;Prata et al, 2015;Pritchard et al, 2013;Campos et al, 2015;Cobuci and Costa, 2012;Petrini et al, 2016). This was then used to calculate the discounted economic value by multiplying the economic value by the cumulative discounted expression (Brascamp, 1978) to and then a linear selection index, which predicts the breeding goal as accurately as possible, given the information that is available in the form of EBV for individual traits:…”

Fitting mathematical models to lactation curves from holstein cows in the southwestern region of the state of Parana, Brazil

“…The model of Wood is the best to describe an entire lactation, and because of that it is widely used for practical purposes e.g., selection of superior animals, in comparison with other lactation curve models (Molento et al 2004, Cobuci and Costa 2012, Gloria et al 2012). Papajcsik and Bodero (1988) compared 20 models of the lactation curve and concluded that Wood's model and a modified form of it provided the best representations of the lactation curve of Holstein cows in southwest Queensland (Australia).…”

“…Accurate fitting of lactation curves contributes towards making decisions about management and breeding of animals that can be adjusted according to predictions of milk production at some stage of lactation (Cobuci et al 2000(Cobuci et al , 2012.…”

Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle

“…Among various functions, Legendre’s polynomials have been the most used ones. The random effects are usually modeled with polynomials of the same order ( Cobuci et al, 2006 ; Cobuci and Costa, 2012 ), however, evidences in favor of using lower order polynomials to model the additive genetic effect in comparison to the permanent environment effect have also been reported ( Pool et al, 2000 ; Lopez-Romero and Carabaño, 2003 ; Bignardi et al, 2009 ). Besides estimating genetic parameters along the lactation curve, the RRM also allow the prediction of breeding values for lactation persistency, as these values are estimated at any time during lactation period ( Jamrozik et al, 1997 ).…”

“…Recent studies on assessment of lactation persistency in tropical regions reported unfavorable genetic association between milk yield and persistency ( Dorneles et al, 2009b ; Cobuci et al, 2012 ; Khorshidie et al, 2012 ; Pereira et al, 2012 ). Despite many studies on genetic parameter estimation via RRM as well as evaluation of lactation persistency in Holstein cows have been carried out in Brazil, there are no studies on Girolando breed.…”