Genetic parameters of milk, fat, and protein yields in the first three lactations, using an animal model and restricted maximum likelihood

Milk, fat, and protein yields of Holstein cows from the States of New York and California in the United States were used to estimate (co)variances among yields in the first three lactations, using an animal model and a derivative-free restricted maximum likelihood (REML) algorithm, and to verify if yields in different lactations are the same trait. The data were split in 20 samples, 10 from each state, with means of 5463 and 5543 cows per sample from California and New York. Mean heritability estimates for milk, fat, and protein yields for California data were, respectively, 0.34, 0.35, and 0.40 for first; 0.31, 0.33, and 0.39 for second; and 0.28, 0.31, and 0.37 for third lactations. For New York data, estimates were 0.35, 0.40, and 0.34 for first; 0.34, 0.44, and 0.38 for second; and 0.32, 0.43, and 0.38 for third lactations. Means of estimates of genetic correlations between first and second, first and third, and second and third lactations for California data were 0.86, 0.77, and 0.96 for milk; 0.89, 0.84, and 0.97 for fat; and 0.90, 0.84, and 0.97 for protein yields. Mean estimates for New York data were 0.87, 0.81, and 0.97 for milk; 0.91, 0.86, and 0.98 for fat; and 0.88, 0.82, and 0.98 for protein yields. Environmental correlations varied from 0.30 to 0.50 and were larger between second and third lactations. Phenotypic correlations were similar for both states and varied from 0.52 to 0.66 for milk, fat and protein yields. These estimates are consistent with previous estimates obtained with animal models. Yields in different lactations are not statistically the same trait but for selection programs such yields can be modelled as the same trait because of the high genetic correlations.

String-averaging expectation-maximization for maximum likelihood estimation in emission tomography

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Inferences about the coefficient of correlation in the standard bivariate normal distribution

The study of the association between two random variables that have a joint normal distribution is of interest in applied statistics; for example, in statistical genetics. This article, targeted to applied statisticians, addresses inferences about the coefficient of correlation (ρ) in the bivariate normal and standard bivariate normal distributions using likelihood, frequentist, and Baycsian perspectives. Some results are surprising. For instance, the maximum likelihood estimator and the posterior distribution of ρ in the standard bivariate normal distribution do not follow directly from results for a general bivariate normal distribution. An example employing bootstrap and rejection sampling procedures is used to illustrate some of the peculiarities.

Análise clássica e bayesiana do modelo Weibull modificado generalizado

Pós-graduação em Matematica Aplicada e Computacional - FCT

Cluster and meta-analyses of genetic parameters for feed intake traits in growing beef cattle

A data set based on 50 studies including feed intake and utilization traits was used to perform a meta-analysis to obtain pooled estimates using the variance between studies of genetic parameters for average daily gain (ADG); residual feed intake (RFI); metabolic body weight (MBW); feed conversion ratio (FCR); and daily dry matter intake (DMI) in beef cattle. The total data set included 128 heritability and 122 genetic correlation estimates published in the literature from 1961 to 2012. The meta-analysis was performed using a random effects model where the restricted maximum likelihood estimator was used to evaluate variances among clusters. Also, a meta-analysis using the method of cluster analysis was used to group the heritability estimates. Two clusters were obtained for each trait by different variables. It was observed, for all traits, that the heterogeneity of variance was significant between clusters and studies for genetic correlation estimates. The pooled estimates, adding the variance between clusters, for direct heritability estimates for ADG, DMI, RFI, MBW and FCR were 0.32 +/- 0.04, 0.39 +/- 0.03, 0.31 +/- 0.02, 0.31 +/- 0.03 and 0.26 +/- 0.03, respectively. Pooled genetic correlation estimates ranged from -0.15 to 0.67 among ADG, DMI, RFI, MBW and FCR. These pooled estimates of genetic parameters could be used to solve genetic prediction equations in populations where data is insufficient for variance component estimation. Cluster analysis is recommended as a statistical procedure to combine results from different studies to account for heterogeneity.

Computer intensive methods for controlling bias in a generalized species diversity index

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Bayesian Analysis of Spectral ARMA Model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Assessing relationships between genetic evaluations using robust regression with an application to holsteins in Uruguay

Globalization of dairy cattle breeding has created a need for international sire proofs. Some early methods for converting proofs from one population to another are based on simple linear regression. An alternative robust regression method based on the t-distribution is presented, and maximum likelihood and Bayesian techniques for analysis are described, including the situation in which some proofs are missing. Procedures were used to investigate the relationship between Holstein sire proofs obtained by two Uruguayan genetic evaluation programs. The results suggest that conversion equations developed from data including only sires having proofs in both populations can lead to distorted results, relative to estimates obtained using techniques for incomplete data. There was evidence of non-normality of regression residuals, which constitutes an additional source of bias. A robust estimator may not solve all problems, but can provide simple conversion equations that are less sensitive to outlying proofs and to departures from assumptions.

Estimates of genetic parameters for visual scores and their correlation with production and reproductive traits in Brahman cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Parâmetros Genéticos para a Produção de Leite, Gordura e Proteína em Bubalinos

The objective of this study was to estimate the genetic parameters affecting milk production (MP), fat (%F) and protein (%P) contents of buffalo milk. Restricted Maximum Likelihood (REML) using MTDFREML program under animal model analyzed a total of 1744 lactations records from 1268 cows. The means were: MP = 1259.47 +/- 523.09 kg, %F = 6.87 +/- 0.88% and %P = 3.91 +/- 0.61%. The estimates of repeatability and heritability coefficients were: MP = 0.38 and 0.24, %F = 0.28 and 0.21 and %P = 0.30 and 0.26, respectively. The estimated genetic and phenotypic correlations were MP x %F = -0.18 and -0.62, MP x %P = -0.23 and -0.59 and %F x %P = 0.50 and 0.77, respectively. According to these results it is possible to conclude that selection is a proper way to increase milk yield, fat and protein percentage. Although negative low values of genetic correlations among traits, it should be take into account that simultaneous selection based on these traits could not be so efficient.

Índices de seleção para um rebanho Caracu de duplo propósito

Neste trabalho, objetivou-se determinar índices de seleção para um rebanho da raça Caracu de duplo propósito, cujo objetivo de seleção (H) incluiu a venda de bezerros desmamados e a produção de leite. As características que compuseram H foram: produção total de leite, idade ao primeiro parto, período de serviço, peso à desmama e duração da vida produtiva. Foram propostos dois índices de seleção para H. Os critérios de seleção adotados no índice 1 foram: produção de leite na primeira lactação, primeiro período de serviço, peso à desmama (PD) e perímetro escrotal. No índice 2, foram consideradas as mesmas características, sendo, entretanto, o ganho médio diário do nascimento à desmama empregado como critério de seleção para PD. As análises estatísticas para a obtenção dos componentes de (co)variâncias e das estimativas dos parâmetros genéticos e fenotípicos foram realizadas pelo método da máxima verossimilhança restrita livre de derivada, por um modelo animal (uni e bi-característica). As informações zootécnicas e genealógicas, os preços e as quantidades dos insumos e dos produtos foram obtidos no escritório da empresa estudada. Os custos de produção e as receitas da atividade pecuária foram determinados para o período de 1994 a 2000. A equação de lucro foi tomada em base anual, usando-se valores médios para número de animais por categoria, características biológicas e preços..¹ O valor econômico para cada característica foi obtido pela derivada parcial da função de lucro em relação à característica em questão. Os dois índices econômicos de seleção trariam considerável resposta para o objetivo proposto. Entretanto, o índice 1, que incluiu PD, seria um pouco mais eficiente em termos de resposta à seleção total.

Estimates of genetic parameters for visual scores and daily weight gain in Brangus animals

(Co) variance components were estimated for visual scores of conformation (CY), early finishing (PY) and muscling (MY) at 550 days of age (yearling), average daily gain from weaning to yearling (GWY), conformation (CW), early finishing (PW) and muscling (MW) scores at weaning, and average daily gain from birth to weaning (GBW) in animals forming the Brazilian Brangus breed born between 1986 and 2002 from the livestock files of GenSys Consultants Associados S/C Ltda. The data set contained 53 683; 45 136; 52 937; 56 471; 24 531; 21 166; 24 006 and 25 419 records for CW, PW, MW, GBW, CY, PY, MY and GWY, respectively. Data were analyzed by the restricted maximum likelihood method using single-and two-trait animal models. Direct heritability estimates obtained by single-trait analysis were 0.12, 0.14, 0.13 and 0.14 for CY, PY and MY scores and GWY, respectively. A positive association was observed between the same visual scores at weaning and yearling, with correlations ranging from 0.64 to 0.94. Estimated correlations between GBW and weaning and yearling scores ranged from 0.60 to 0.77. The genetic correlation between GBW and GWY was low (0.10), whereas correlations of 0.55, 0.37 and 0.47 were observed between GWY and CY, PY and MY, respectively. Moreover, GWY showed a weak correlation with CW (0.10), PW (-0.08) and MW (-0.03) scores. These results indicate that selection of the traits that was studied would result in a small response. In addition, selection based on average daily gain may have an indirect effect on visual scores as the correlations between GWY and visual scores were generally strong.

Genetic associations between weight at maturity and maturation rate with ages and weights at first and second calving in Canchim beef cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Association of an insulin-like growth factor 1 gene microsatellite with phenotypic variation and estimated breeding values of growth traits in Canchim cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genotype-environment interaction for post-weaning traits in Nellore beef cattle

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)