A study of the growth and fertility of different beef cattle genotypes in a tropical environment with implications for the genetic improvement of productivity

One method of improving the genetic performance of beef cattle in any environment is to select for improved growth and fertility using Estimated Breeding values (EBV's) to identify the superior animals. Improving the accuracy of these EBV's requires the use of datasets and models that are appropriate to that environment. A study of the growth and fertility of beef cattle from a dry tropical environment was undertaken using data from CSIRO's National Cattle Breeding Station, "'Belmont" (23°S, 150E). The data were collected from 1974 to 1990 from Hereford-Shorthorns (HS), Braham x HS (BX) and low (BL) and high (BH) grade Brahmans. Components of the models of growth and fertility were analysed using a least-squares analysis of variance.The dependent variables that described growth were calf day of birth (CBDAY) and the growth variables of birth weight (BWT) and age-adjusted weights at a 200 day weaning weight (WWT),365 day yearling weight (YWT) and a 550 day final weight (FWT). The dependent variables that described female fertility were pregnancy success, the heifer's day of birth (HBDAY), cow liveweight at the start of the breeding season (IWT), cow weight gain per day during the breeding season (MWGD) and the day of calving (DAYOC). Environmental category, genotype and the combined effects of cow age and previous lactational status (AGEPLS) were used as fixed effects for both growth and fertility. If the BWT of a calf crop was above the overall mean for BWT, the calf crop was assigned to a S2goodS3 years (low stress) environmental category and if the BWT was below the overall mean BWT, the calf crop was assigned to a S2poorS3 years (high stress) environmental category. This procedure was repeated for WWT, YWT and FWT. Environmental categories of S2goodS3, S2averageS3 and S2poorS3 years were based on pregnancy rate and were used in the analysis of all fertility variables. The relative performance of the genotypes was explained in terms of production potential (i.e. growth and fertility able to be achieved when environmental stress is negligible) and resistance to environmental stress. The production potential of the BL was less than the HS, similar to BX but higher than that of the BH. The productivity in the environments of relatively high stress was least for HS, intermediate for BX and highest for BL and BH. Whereas 3 year old maidens achieved relatively high pregnancy rates their calves were associated with the lowest growth rates. Lactating cows, especially young lactating cows, had lower productivity than non-lactating cows. The 5+ year old non-lactating cows were consistently the most productive class of AGEPLS. For lactating cows, HS (70.9%) were more fertile than both BX (59.9%) and BL (61.1%) which were more fertile than BH (49.9%). For 3 year maidens and nonlactating cows the genotypes ranked in a similar order but the differences were small. Sex of calf was a significant effect for growth but not for fertility. Compared to female calves, male calves were born later, heavier and maintained higher rates of growth. Interactions between genotype and environmental category were also explained in terms of stress. The interaction between genotype and AGEPLS for growth was only significant for WWT and the AGEPLS effect on calves was reduced as the Brahman content increased. For pregnancy rate, the AGEPLS effect on HS was minor compared to the effect on the BH. Of the four growth variables, the interaction between AGELPS and environmental category was only significant for FWT. The effect of AGEPLS on FWT in good years was minor compared to the effect poor years. The time of calving variables were significant covarities in the analysis of both growth (CBDAY) and fertility (HBDAY) and DAYOC). IWT and MWGD were significant positive regressions for fertility but IWT was shown to be more important than MWGD. Increasing the IWT of heifers would increase their reproductive rate but this increase would be greater in the BH than in other genotypes. Increasing the IWT of lactating cows would also increase their reproductive rate but the response would be greatest in the poor and least in the good years. Components of the models were discussed with relevance to constructing models of growth and fertility that can be used in genetic improvement programs for northern Australia..