Estimation of (co)variance components and genetic parameters for weights of red-winged tinamou using random regression models

The objective of this work was to determine genetic parameters for body weight of tinamou in captivity. It was used random regression models in analyses of data by considering the direct additive genetic (DA) and permanent environmental effects of the animal (PE) as random effects. Residual variances were modeled by using a fifth-order variance function. The mean population growth curve was fitted by sixth-order Legendre orthogonal polynomials. Direct additive genetic effects and animal environmental permanent effect were modeled by using Legendre polynomials of order two to nine. The best results were obtained by models with orders of fit of 6 for direct additive genetic effect and of order 3 for permanent effect by Akaike information criterion and of order 3 for both additive genetic effect and permanent effect by Schwarz Bayesian information criterion and likelihood ratio test. Heritability estimates ranged from 0.02 to 0.57. The first eigenvalue explained 94% and 90% of the variation from additive direct and permant environmental effects, respectively. Selection of tinamou for body weight is more effective after 112 days of age.Com este trabalho objetivou-se determinar parâmetros genéticos para peso corporal de perdizes em cativeiro. Foram utilizados modelos de regressão aleatória na análise dos dados considerando os efeitos genéticos aditivos diretos (AD) e de ambiente permanente de animal (AP) como aleatórios. As variâncias residuais foram modeladas utilizando-se funções de variância de ordem 5. A curva média da população foi ajustada por polinômios ortogonais de Legendre de ordem 6. Os efeitos genéticos aditivos diretos e de ambiente permanente de animal foram modelados utilizando-se polinômios de Legendre de segunda a nona ordem. Os melhores resultados foram obtidos pelos modelos de ordem 6 de ajuste para os efeitos genéticos aditivos diretos e de ordem 3 para os de ambiente permanente pelo Critério de Informação de Akaike e ordem 3 para ambos os efeitos pelos Critério de Informação Bayesiano de Schwartz e Teste de Razão de Verossimilhança. As herdabilidades estimadas variaram de 0,02 a 0,57. O primeiro autovalor respondeu por 94 e 90% da variação decorrente de efeitos aditivos diretos e de ambiente permanente, respectivamente. A seleção de perdizes para peso corporal é mais efetiva a partir de 112 dias de idade

Modelos de regressão aleatória na seleção de codornas de corte para produção de ovos

O objetivo deste trabalho foi avaliar modelos de regressão aleatória com diferentes ordens de polinômios de Legendre, quanto ao melhor ajuste para a produção de ovos de codornas de corte. Foram avaliados os grupos genéticos UFV1 e UFV2 de codornas de corte, de origens distintas, do programa de melhoramento genético da Universidade Federal de Viçosa. Determinou-se a produção semanal de ovos de 1.294 matrizes, da 6ª até a 57ª semana de idade, das quais 644 do grupo genético UFV1 e 650 do UFV2. Utilizou-se o modelo animal em regressão aleatória pelo programa Wombat e, para modelar as trajetórias das características com o tempo, aplicaram-se as funções polinomiais de Legendre. Foram feitas comparações pelo critério de informação de Akaike, critério de informação bayesiano de Schwarz, logaritmo da função de verossimilhança e teste da razão de verossimilhança. O modelo com K = 3, para efeitos fixos, Ka = 4, para efeitos genéticos, e Kc = 4, para efeito de ambiente, propicia melhor ajuste para ambas as linhagens, não provoca grandes alterações nos componentes de variância e fornece melhores estimativas de herdabilidade

Gendered self-views across 62 countries: a test of competing models

Social role theory posits that binary gender gaps in agency and communion should be larger in less egalitarian countries, reflecting these countries’ more pronounced sex-based power divisions. Conversely, evolutionary and self-construal theorists suggest that gender gaps in agency and communion should be larger in more egalitarian countries, reflecting the greater autonomy support and flexible self-construction processes present in these countries. Using data from 62 countries (N = 28,640), we examine binary gender gaps in agentic and communal self-views as a function of country-level objective gender equality (the Global Gender Gap Index) and subjective distributions of social power (the Power Distance Index). Findings show that in more egalitarian countries, gender gaps in agency are smaller and gender gaps in communality are larger. These patterns are driven primarily by cross-country differences in men’s self-views and by the Power Distance Index (PDI) more robustly than the Global Gender Gap Index (GGGI). We consider possible causes and implications of these findings

Comparison of different covariance structure used for experimental design with repeated measurement

This study was conducted to compare performance of univariate and multivariate approaches used for analyzing experiments with repeated measurement and determine the best covariance structure for the data studied. In this study, univariate ANOVA, Geisser-Greenhouse Epsilon and Huynth-Feldt Epsilon were used as univariate approaches while profile analysis, Containment, Satterthwaite and Kenward-Roger approaches in general linear mixed model were applied as multivariate approaches. Annual amounts of wheat production from 65 provinces in seven geographical regions of Turkey from 1982 to 1999 were used as research material. A total of 1170 production values were obtained. In General Linear Model, nine various covariance structures (CS, CSH, UN, HF, AR (1), ARH (1), ANTE (1), TOEP and TOEPH) were applied. AIC and AICC criteria were used to determine the most appropriate covariance pattern for fitting data. In the study, "spherity assumption" for amounts of wheat production of provinces was violated. Application of Containment, Satterthwaite and Kenward-Roger approaches in general linear model and determination of covariance structure with the best fit were provided. According to AIC and AICC fitting criteria, it was determined that CS covariance structure gave the best fit to data set. As a result, covariance structure is compound symmetry (CS) in standard univariate ANOVA, and unstructured (UN) covariance structure in MANOVA. However, determination of the most appropriate covariance structure for data set is possible in multivariate general linear model. Containment, Satterthwaite, and Kenward-Roger approaches gave similar results since total sample size was sufficient. On the other hand, usage of Containment, Satterthwaite and Kenward-Roger approaches in analyzing experiments with repeated measurement were suggested to allow selection of the most suitable covariance structure for data set

Variance components and genetic parameter estimates using random regression models on test day milk yields of Holstein Friesians [Siyah Alacalarda Şansa Bagli{dotless} Regresyon Modelleri Kullani{dotless}larak Denetim Günü Süt Veriminin Varyans Bileşenleri ve Genetik Parametrelerinin Tahminlenmesi]

Genetic parameters for test day milk yields of Holstein Friesian cows were estimated by random regression with Legendre polynomials. The analyzes were applied to 5918 first lactation test day milk yields of 612 Holstein Friesian cows calving from 1987 to 1993 in Dalaman, Tahirova, Sarimsakli and Türkgeldi State Farms. Estimated genetic variances for test day milk yields were larger at extremes of the lactation. Permanent environmental variances mostly decreased in middle part of the lactation. The heritability values for test day milk yields were from 0.26 to 0.57. The genetic correlations between test day milk yields (TD1-TD9) with the last test day milk yield (TD10) were changed from -0.10 to 0.96 and it was high between consecutive test day milk yields, but decreased when the intervals between the test days increased. In random regression models it can be concluded that higher order polynomials were recommended for a sufficient fit of the (co)variance structures over the lactation but a reduction of the orders can also be used for computational simplicity due to small numbers of parameters

Effect of different residual variances on genetic parameters of test day milk yields [Denetim günü süt veriminin genetik parametre tahminine farklı hata varyanslarının etkisi]

Heterogeneous residual variance effects on genetic parameters were examined for test day milk yields of Turkish Holsteins. A third order random regression models including the fixed, random additive genetic and permanent environmental effects were used. One of these models, RV10, residual variances is assumed to be different for each test day milk yields. The RV1 model has constant residual variance for each test day. Sequential (RV2 to RV9) and non-sequential (NRV2 to NRV9) groups of residual variances were also described in the models in order to compare estimates of variance components. The univariate analysis of milk yields for each test days was performed to define variance groups. The predicted residual variances ranged from 5.62 to 11.75 and from 5.61to 11.71 for RV and NRV models, respectively. Estimates of additive genetic variances changed between 0.55-6.76 for RV and 0.08-2.46 for NRV models. Permanent environmental variances were found between 2.36 and 18.60 for RV and 6.92 to 18.85 for NRV models. Heritability estimates varied from 0.02 to 0.43 for RV and 0.01 to 0.13 for NRV models. As a result, more accurate genetic parameter estimates are achieved by controlling the residual variances. RV10 model should be preferred to define details of the milk yield residual variances for each test day. However, RV5 model has been determined that an alternative model as compared with RV10. © 2015, Veteriner Fakultesi Dergisi. All rights reserved