Suchergebnisse

The objective of this work was to estimate growth curves and genetic parameters from birth to 650 days of age of Nelore cattle raised in pasture in two production regions of the Mato Grosso do Sul State, Brazil (233,835 weight records from 47,459 cattle were analyzed). Genetic parameters were determined by random regression using Legendre orthogonal polynomials of cubic order, and age at weighing was considered in the model as a fixed effect to model the average growth trajectory. In the models, the effects of the contemporary group were considered as fixed and, as covariates, the animal age at weighing and the cow age at calving were nested in the animal age class (linear and quadratic effects), forming eight age classes. All models included the direct genetic additive, maternal genetic, and animal permanent environment as random effects, and the most appropriate model to describe the studied effects was defined according to the AIC and BIC criteria. Heritability estimates for birth weight varied between the two production regions, Campo Grande-Dourados (R1) and Alto Taquari-Bolsão (R2) and R1 (0.36 ± 0.02) and R2 (0.28 ± 0.03), and there were variations in the estimates at advanced ages. In both regions, the highest heritability values at 650 days of age were 0.47 ± 0.03 and 0.65 ± 0.02 for R1 and R2, respectively, with high heritability reflecting the high values of additive genetic variance. The random regression methodology was efficient in estimating growth curves and genetic parameters. Growth curves were different when they were estimated separately by sex, birth season, and production region. Genetic parameters estimated separately by region indicate differences in additive genetic variance, maternal additive, and animal permanent environment for weights up to 650 days of age.

The objectives of this work were to evaluate the genotype-environment interaction, and estimate genetic parameters, genetic trends, and performance dissimilarity-weight gain from birth to weaning (WGBW), adjusted weight to 205 days (W205), weight gain from weaning to 18 months of age (WG18), and adjusted weight to 550 days (W550)-in Nellore animals born between 1986 and 2012, and raised in pasture-based system in three different environmental gradients in Brazil. Data of 62,001 animals-11,729 raised in the Alto Taquari/Bolsão region (ATBR), 21,143 raised in the Campo Grande/Dourados region (CGDR) and 29,129 raised in the western São Paulo/Paraná region (SPPR) in Brazil-were used. The contemporary groups were defined by sex, location, and birth year and season, with at least nine individuals, two different environments, and breeding bulls with at least five progenies. The statistical model contained the direct additive and residual genetic effects (random effects), and environmental and contemporary group effects (fixed effects). Genetic parameters, genotype-environment interaction and genetic trends were estimates using animal model (uni- and/or bi- traits). The level of similarity between regions was evaluated using principal components. The animals raised in the CGDR had superior performance regarding the traits evaluated. The direct heritability estimates ranged from 0.39 to 0.44 (WGBW), 0.41 to 0.45 (W205), 0.42 to 0.55 (WG18) and 0.60 to 0.62 (W550). The maternal heritability of the traits ranged from 0.20 (WGBW), 0.12 to 0.18 (W205), 0.00 to 0.06 (WG18) and 0.02 to 0.22 (W550). According to the Spearman correlation, the ranking of the breeding bulls in the regions evaluated were different. The mean of Euclidean distance indicated low similarity between ATBR and CGDR (43.20), and ATBR and SPPR (29.24). CGDR and SPPR presented similarity of 17.84. The breed values increased over the years in the traits evaluated. The cumulative variance percentage of the first two main components explained 99.99% variation among the regions, and the weight gains of the animals were the most important to differentiate the regions. A genotype-environment interaction was found for the traits evaluated, thus, the breeding bull selected with superior genetic merit for one region might not be the best for others.