Random regression models in the evaluation of the growth curve of Simbrasil beef cattle.

Random regression models were used to estimate the types and orders of random effects of (co)variance functions in the description of the growth trajectory of the Simbrasil cattle breed. Records for 7049 animals totaling 18,677 individual weighings were submitted to 15 models from the third to the fifth order including as fixed effects sex, contemporary group, feeding regimen, and type of reproduction and as random effects additive direct genetic effect, animal permanent environment, maternal additive genetic effect, and maternal permanent environment. The best-fit model presented order five to additive direct genetic effect, animal permanent environment, and maternal additive effect, with 6 classes of residual variances, and the maternal permanent environment effect was not significant, likely owing to the low average number of calves per cow. However, the model chosen for the growth curve presents three classes of residual variances, because even not showing the best fit it is more parsimonious, in addition to promoting a more realistic estimate of heritability.

Evaluation of alternative schemes for recording body weights in meat-type quails by using random regression.

Data from 8759 meat-type quails from the UFV1 strain and 9128 from the UFV2 strain were used to assess the possibility of reducing the number of body weight records in genetic evaluations. The evaluated animals were weighed weekly since hatching to the 6th week of life, with up to 7 records of body weight for each bird. The data were evaluated by random regression models, with 9 alternative schemes of data recording, which included 4 records for each scheme and their covariance functions for additive and permanent environmental effects of order 3, fitting 4 intervals for residual variance, and a complete scheme, with 7 records, order of fit 6 for additive and permanent environmental effects and 7 intervals for residual variance. Estimates of heritability for body weight at the 6th week varied from 0.45 to 0.53 for the UFV1 strain and from 0.28 to 0.54 for UFV2 strain. The schemes that had more records in points at the final extreme of the age range showed better estimates, which was likely due to certain properties of polynomial regression that led to biased results in the final extreme of the age range when data are unbalanced. The reduction of the number of body weight records taken during the growth phase is feasible, with little change to breeding value estimates, when 4 body weight records are used in random regression models.

Environmental and genetic factors affecting the weaning-estrus interval in sows.

We examined the effects of environmental and genetic factors on the weaning-to-estrus interval (WEI) in sows. In order to perform the analyses of the environmental factors, 8104 observations of the 1st to the 6th WEI were carried out, while 6548 observations of the 1st to the 3rd WEI were carried out for the analyses of genetic factors. The environmental model included as fixed effects, herd, genetic line, year and season of birth, as well as the covariates, age of sow at farrowing, litter size at birth and lactation length. Genetic analysis was performed by repeatability and multitrait models. The mean and coefficient of variation for WEI were 7.02 days and 100.6%, respectively. The linear effect of lactation length and the quadratic effect of the age of sow at farrowing affected the WEI. Herd, year and season of farrowing were significant sources of variation for WEI, and there was no influence of genetic line or of litter size at birth. Heritability estimated by the repeatability model was 0.04, while heritabilities obtained by the multitrait model were 0.07, 0.02 and 0.07 for the first three WEI, respectively. Estimates of genetic correlations among the different WEI were of moderate to low magnitude. It was concluded that environmental factors, such as year and season of farrowing, lactation length, age of sow at farrowing and herd, should be considered in the model for best estimation of genetic parameters for this trait. Although with only a small possible genetic gain, selection can be made based on the first WEI.

Avaliação de características de desempenho e de carcaça de codornas de corte por meio da análise de componentes principais / Evaluation of production and carcass traits of meat - type quails by principal components analysis

Foram utilizados dados de 288 codornas de corte (Coturnix coturnix coturnix) para avaliar a possibilidade de resumir a informação contida no complexo de variáveis originais, eliminando-se variáveis inexpressivas por meio da técnica de componentes principais. Foram registrados o peso vivo (PVIVO) e pesos do peito (PPEITO), das coxas (PCOXA), da gordura abdominal (GA), das vísceras comestíveis (fígado, moela e coração) (FIG, MOELA e CORA) e da carcaça eviscerada (PCEVIS). As carcaças foram secas e trituradas para a avaliação do teor matéria seca (MS), gordura (GORD) e proteína bruta (PB). Dos 11 componentes principais, sete (63,6 por cento) apresentaram variância menor que 0,7 (autovalor inferior a 0,7), sendo sugeridas para descarte, respectivamente, em ordem de menor importância, para explicar a variação total das seguintes variáveis: PCEVIS, PPEITO, PCOXA, CORA, FIG MOELA e GORD. Com base nos resultados, recomenda-se manter as seguintes variáveis em experimentos futuros: PVIVO, MS, PB e GA.

Records on 288 meat type quails (Coturnix coturnix coturnix) were used to identify independent and informative variables by eliminating inexpressive variables by means of principal component analysis. The following performance traits were recorded: live body weight (LBW), eviscerated carcass weight (CW), whole leg weight (WLW), breast weight (BW), abdominal fat pad weight (FW), and giblets weight (liver, gizzard, and heart) (LIW, GW, and HW). The carcasses were also dried and grounded to evaluate dry matter (DM), fat (FA,T) and crude protein (CP) contents. Out of 11 principal components, seven (63.6 percent) showed variance lower than 0.7 (eigenvalue lower than 0.7). The following traits were discarded because they showed inexpressive contribuitions for the total variation: CW, BW, WLW, HW, LIW, GW, and FAT. Based on the results, it is recommended to record the following variables in future experiments: LBW, DM, CP, and FW.