2019•Welwitschia International Journal of Agricultural SciencesOpen access

Genetic and non-genetic factors influencing birth weight in the Tuli cattle breed of Zimbabwe

T Magwaba, Marvelous Sungirai, K Hove, Simon K. Awala

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Abstract

Genetic and non-genetic factors were estimated for birth weight in the Tuli cattle breed of Zimbabwe. Performance records ( n = 1154) were obtained from the Livestock Identification Trust (LIT) for the period (2008–2014) for three farms; X ( n = 494), Z ( n = 143) and Y ( n = 517). We used the Restricted Maximum Likelihood (REML) for fitting the Sire model. The model used the farm, season, sex, year and dam age as fixed effects while the sire was fitted as a random variable. Best Linear Unbiased Prediction (BLUP) was used to predict breeding values (BVs). The mean birth weight was (30.89±0.128). Wet season had higher birth (31.62±0.27) weight than dry season (30.62±0.144); however, the difference was not statistically significant. The other factors, farm, sex, year and dam age had a significant effect (P <0.05) on birth weight. Heritability and repeatability estimates were 0.44 and 0.35, respectively. Based on the results, the high heritability estimate for birth weight suggests that the trait responds well to selection. Sire breeding values ranged from -4.400 to 6.845 with the majority of sires between -2 and 2, showing that there was stabilising selection over the years to minimise both overweights and underweights.

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Genetic and non-genetic factors were estimated for birth weight in the Tuli cattle breed of Zimbabwe. Performance records ( n = 1154) were obtained from the Livestock Identification Trust (LIT) for the period (2008–2014) for three farms; X ( n = 494), Z ( n = 143) and Y ( n = 517). We used the Restricted Maximum Likelihood (REML) for fitting the Sire model. The model used the farm, season, sex, year and dam age as fixed effects while the sire was fitted as a random variable. Best Linear Unbiased Prediction (BLUP) was used to predict breeding values (BVs). The mean birth weight was (30.89±0.128). Wet season had higher birth (31.62±0.27) weight than dry season (30.62±0.144); however, the difference was not statistically significant. The other factors, farm, sex, year and dam age had a significant effect (P <0.05) on birth weight. Heritability and repeatability estimates were 0.44 and 0.35, respectively. Based on the results, the high heritability estimate for birth weight suggests that the trait responds well to selection. Sire breeding values ranged from -4.400 to 6.845 with the majority of sires between -2 and 2, showing that there was stabilising selection over the years to minimise both overweights and underweights.

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Available abstract

Genetic and non-genetic factors were estimated for birth weight in the Tuli cattle breed of Zimbabwe. Performance records ( n = 1154) were obtained from the Livestock Identification Trust (LIT) for the period (2008–2014) for three farms; X ( n = 494), Z ( n = 143) and Y ( n = 517). We used the Restricted Maximum Likelihood (REML) for fitting the Sire model. The model used the farm, season, sex, year and dam age as fixed effects while the sire was fitted as a random variable. Best Linear Unbiased Prediction (BLUP) was used to predict breeding values (BVs). The mean birth weight was (30.89±0.128). Wet season had higher birth (31.62±0.27) weight than dry season (30.62±0.144); however, the difference was not statistically significant. The other factors, farm, sex, year and dam age had a significant effect (P <0.05) on birth weight. Heritability and repeatability estimates were 0.44 and 0.35, respectively. Based on the results, the high heritability estimate for birth weight suggests that the trait responds well to selection. Sire breeding values ranged from -4.400 to 6.845 with the majority of sires between -2 and 2, showing that there was stabilising selection over the years to minimise both overweights and underweights.

Key concepts: Sire, Best linear unbiased prediction, Heritability, Restricted maximum likelihood, Breed, Biology, Birth weight, Animal science

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