Genotype by environment interaction in different birth seasons for weight at 240, 365 and 450 days of age in Tabapuã cattle

Júnior, Severino Cavalcante de Sousa; Diaz, Iara Del Pilar Solar; Santos, Karina Rodrigues dos; Sousa, José Ernandes Rufino de; Sarmento, José Lindenberg Rocha; Filho, Raimundo Martins

doi:10.1590/s1516-35982012001000005

Cited by 7 publications

(4 citation statements)

References 15 publications

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“…In addition, within each region, changes in pasture growth between years can also cause genotype by environment interactions. For example, several studies in beef cattle (Sousa Júnior et al, 2012) and dairy cattle (Kearney et al, 2004;McCarthy and Veerkamp, 2012) found Optimal breeding objectives for varying pasture genotype by environment interactions for production traits when resources were different, either because of the time of year, amount of rainfall or amount of grain supplement provided. Therefore, genotype by environment interactions between regions could make it difficult to use one breeding scheme for all environments (e.g.…”

Section: Discussionmentioning

confidence: 99%

Breeding objectives for sheep should be customised depending on variation in pasture growth across years

Rose

Mulder

Thompson

et al. 2015

Animal

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Breeding programmes for livestock require economic weights for traits that reflect the most profitable animal in a given production system, which affect the response in each trait after selection. The profitability of sheep production systems is affected by changes in pasture growth as well as grain, meat and wool prices between seasons and across years. Annual pasture growth varies between regions within Australia's Mediterranean climate zone from low growth with long periods of drought to high growth with shorter periods of drought. Therefore, the objective of this study was to assess whether breeding objectives need to be adapted for regions, depending on how reliable the pasture growth is across years. We modelled farms with Merino sheep bred for wool and meat in 10 regions in Western Australia. Across these 10 regions, mean annual pasture growth decreased, and the CV of annual pasture growth increased as pasture growth for regions became less reliable. We calculated economic values for nine traits, optimising management across 11 years, including variation for pasture growth and wool, meat and grain prices between and within years from 2002 to 2012. These economic values were used to calculate responses to selection for each trait for the 10 regions. We identified two potential breeding objectives, one for regions with low or high reliability and the other for regions with medium reliability of pasture growth. Breeding objectives for high or low pasture growth reliability had more emphasis on live weight traits and number of lambs weaned. Breeding objectives for medium reliability of pasture growth had more emphasis on decreasing fibre diameter. Relative economic weights for fleece weight did not change across the regions. Regions with low or high pasture reliability had similar breeding objectives and response to selection, because the relationship between the economic values and CV of pasture growth were not linear for live weight traits and the number of lambs weaned. This non-linearity was caused by differences in distribution of pasture growth between regions, particularly during summer and autumn, when ewes were pregnant, with increases in energy requirements affecting the value of lambs weaned. In addition, increasing live weight increased the intake capacity of sheep, which meant that more poor quality pasture could be consumed during summer and autumn, which had more value in regions with low and high pasture reliability. We concluded that breeding values for sheep production systems should be customised depending on the reliability of pasture growth between years.

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Section: Discussionmentioning

confidence: 99%

Breeding objectives for sheep should be customised depending on variation in pasture growth across years

Rose

Mulder

Thompson

et al. 2015

Animal

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“…In Brazil, researches using random regression models have been conducted with the aim of studying growth characteristics of beef cattle (Sousa Júnior et al, 2012). According to Sakaguti et al (2003) while studying the Tabapuã breed, the RRM was applied to estimate functions of (co)variance for weights between 365 and 650 days old, however, due to the computational limitations, linear and quadratic models were adjusted only to the effects of the animal, not considering the maternal effects.…”

Section: Random Regression Modelsmentioning

confidence: 99%

Genetic evaluation studies in Tabapuã cattle breed using random regression models-Review

et al. 2018

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“…In Brazil, some studies using RRM have been conducted with the purpose of studying growth traits in beef cattle (DIAS et al, 2006;SOUSA JÚNIOR et al, 2012). Sakaguti et al…”

Section: Random Regression Modelsmentioning

confidence: 99%

Application of Random Regression Models for Growth Traits of Nellore Cattle in Brazil

Fonseca

Evangelista²,

Borges³

et al. 2016

Nucleus Animal.

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SUMMARY:Thepurpose of thisreview isto show the increase in number of researches on covariance components and genetic evaluation using random regression models (RRM) for growth traits of Nellore cattle. Random regression models (RRM), also known as infinite-dimension models have been used to estimate variance components and genetic parameters for weight of beef cattle. In addition, those models are a standard alternative for genetic analyses of longitudinal data, however, the availibility of computational resources for performing genetic evaluations widely is an obstacle. Traits related to animal growth are adopted as selection criteria in beef cattle breeding programs, because the remuneration of cattle breeders is made based on the weight of carcasses. In recent years, RRM have been adopted as standard procedure in relation to the analysis of longitudinal data in animal breeding.Keywords: Genetic evaluation. Longitudinal data. Nellore cattle. APLICAÇÃO DE MODELOS DE REGRESSÃO ALEATÓRIA PARA CARACTERÍSTICAS DE CRESCIMENTO DA RAÇA NELORE NO BRASILRESUMO: Objetivou-se com esta revisão de literatura compilar informações sob a avaliação genética utilizando modelos de regressão aleatória (MRA) para características de crescimento em bovinos da raça Nelore. Os modelos de regressão aleatória (MRA), denominados modelos de dimensão infinita, estão sendo utilizados para estimar os componentes de variância e parâmetros genéticos de pesos de bovinos de corte. Os MRA têm se tornado uma alternativa padrão para análises genéticas de dados longitudinais, onde um dos entraves destes modelos está relacionado à disponibilidade de memória e tempo computacional para a realização de avaliações genéticas em larga escala. Características relacionadas ao crescimento animal são adotadas em programas de melhoramento genético de bovinos de corte como critérios de seleção, pelo fato da remuneração, dos produtores, ser feita com base no peso das carcaças. Nos últimos anos, os MRA têm sido adotados como procedimento padrão para análise de dados longitudinais em melhoramento genético animal.Palavras-chave: Avaliação genética. Dados longitudinais. Nelore.

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Genotype by environment interaction in different birth seasons for weight at 240, 365 and 450 days of age in Tabapuã cattle

Cited by 7 publications

References 15 publications

Breeding objectives for sheep should be customised depending on variation in pasture growth across years

Breeding objectives for sheep should be customised depending on variation in pasture growth across years

Genetic evaluation studies in Tabapuã cattle breed using random regression models-Review

Application of Random Regression Models for Growth Traits of Nellore Cattle in Brazil

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