Sire x ecological region interaction in Bonsmara cattle

Nephawe, Khathutshelo Agree; Neser, F.W.C.; Roux, C. Z.; Theron, H.E.; Westhuizen, J. Van der; Erasmus, G.J.

doi:10.4314/sajas.v29i3.44203

Cited by 6 publications

(17 citation statements)

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“…The greater relative importance of S × CG during the subsequent phase of life of the animal might be explained by cumulative environmental effects on animal performance. These results agree with those reported by Bradfield et al (1997) for WW of Santa Gertrudis cattle (10% to 13%), by Nephawe et al (1999) for WW of Bonsmara cattle (6% to 14%) and by Neser et al (1996) for WW of Bonsmara cattle (8%).…”

Section: Resultssupporting

confidence: 92%

“…Nephawe et al (1999) observed consistently negative correlations between direct and maternal genetic effects for BW of Bonsmara cattle raised in four regions of South Africa when S × CG was omitted, whereas the correlations were mainly positive when S × CG was included in the model. Eler et al (2000) reported genetic correlations between direct and maternal effects for growth traits of Nelore cattle in Brazil that were close to zero or even positive when sire × herd interaction was included in the model, and that were always negative when this parameter was omitted.…”

Section: Resultsmentioning

confidence: 84%

“…Maternal heritability for BW and WW was overestimated on average by 36% and 24%, respectively, when S × CG was omitted. Nephawe et al (1999) reported 30% overestimation of maternal heritability for WW in Bonsmara cattle, corresponding to an average overestimation of total heritability for WW of 34%. In the present study, average overestimation of this parameter was 7% for BW and 13% for WW.…”

Section: Resultsmentioning

confidence: 94%

“…In that study, the genetic correlation of WW between two production environments was 0.66 when S × CG was omitted and 0.83 when this parameter was included. Nephawe et al (1999) estimated genetic correlations of 0.39 to 0.54 between WW of Bonsmara cattle across different regions of Africa when S × CG was omitted and these correlations ranged from 0.79 to 0.85 when S × CG was included in the model. In a study on Limousin cattle in the United States, Bertrand et al (1987) observed that the genetic correlations of BW and WW across regions increased when the effect of S × CG and cow × contemporary group interaction was included in the model.…”

Section: Resultsmentioning

confidence: 98%

“…Eler et al (2000) found that direct heritability estimates for BW and WW of Nelore cattle were overestimated by 76% and 22%, respectively, when sire × herd interaction was not included in the model. In a study on South African Bonsmara Genotype by production environment interaction cattle, Nephawe et al (1999) reported that the omission of S × CG in the model can overestimate direct heritability for WW by 180%. Maternal heritability estimates were also affected by inclusion of S × CG in the model.…”

Section: Resultsmentioning

confidence: 99%

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Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

Júnior

Eler

Bignardi

et al. 2014

Animal

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The objectives of the present study were: (1) to evaluate the importance of genotype × production environment interaction for the genetic evaluation of birth weight (BW) and weaning weight (WW) in a population of composite beef cattle in Brazil, and (2) to investigate the importance of sire × contemporary group interaction (S × CG) to model G × E and improve the accuracy of prediction in routine genetic evaluations of this population. Analyses were performed with one, two (favorable and unfavorable) or three (favorable, intermediate, unfavorable) different definitions of production environments. Thus, BW and WW records of animals in a favorable environment were assigned to either trait 1, in an intermediate environment to trait 2 or in an unfavorable environment to trait 3. The (co)variance components were estimated using Gibbs sampling in single-, bi-or three-trait animal models according to the definition of number of production environments. In general, the estimates of genetic parameters for BW and WW were similar between environments. The additive genetic correlations between production environments were close to unity for BW; however, when examining the highest posterior density intervals, the correlation between favorable and unfavorable environments reached a value of only 0.70, a fact that may lead to changes in the ranking of sires across environments. The posterior mean genetic correlation between direct effects was 0.63 in favorable and unfavorable environments for WW. When S × CG was included in two-or three-trait analyses, all direct genetic correlations were close to unity, suggesting that there was no evidence of a genotype × production environment interaction. Furthermore, the model including S × CG contributed to prevent overestimation of the accuracy of breeding values of sires, provided a lower error of prediction for both direct and maternal breeding values, lower squared bias, residual variance and deviance information criterion than the model omitting S × CG. Thus, the model that included S × CG can therefore be considered the best model on the basis of these criteria. The genotype × production environment interaction should not be neglected in the genetic evaluation of BW and WW in the present population of beef cattle. The inclusion of S × CG in the model is a feasible and plausible alternative to model the effects of G × E in the genetic evaluations.

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Section: Resultssupporting

confidence: 92%

Section: Resultsmentioning

confidence: 84%

Section: Resultsmentioning

confidence: 94%

Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 99%

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Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

Júnior

Eler

Bignardi

et al. 2014

Animal

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Multi-trait linear reaction norm model to describe the pattern of phenotypic expression of some economic traits in beef cattle across a range of environments

et al. 2014

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The multi-trait reaction norm (MTRN) model was extended to beef cattle reared under tropical conditions with the following objectives: to compare multi-trait (MT) and MTRN models regarding the genetic parameters obtained; and to characterize G × E, the pattern of phenotypic expression, and the environmental sensitivity of animals for postweaning weight gain (PWG), scrotal circumference (SC), and annual average productivity of the cow (PRODAM). There was divergence in the estimates between the MT and MTRN models when the posterior probability intervals of additive genetic variances and heritability coefficients of PWG and PRODAM were analyzed. The MTRN model indicated an increase in heritability for PWG and PRODAM with improvement of the environmental conditions. For SC, heritability was practically the same, irrespective of the environmental conditions. The genetic correlations between the traits studied were low but varied over environments by the MTRN model. Considering genetic correlations obtained by the MTRN model for the same trait, lower estimates were obtained between extreme favorable and unfavorable environments. This finding suggest re-ranking of breeding values in different environments mainly for PWG and PRODAM. Thus, G × E is more important for PWG and PRODAM than for SC and should be included in the genetic evaluation of these traits. The traits PWG and PRODAM can be considered plastic traits, whereas SC is poorly plastic. The genetic trends in individual animal slopes indicate that the population is moving towards greater plasticity. This could be a matter of concern for breeders since greater plasticity seems to limit heritability and, consequently, the responses to selection.

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Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil

et al. 2012

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Sire x ecological region interaction in Bonsmara cattle

Cited by 6 publications

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Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

Multi-trait linear reaction norm model to describe the pattern of phenotypic expression of some economic traits in beef cattle across a range of environments

Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil

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