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Background: Selecting animals for feed efficiency directly impacts the profitability of the beef cattle industry, which contributes to minimizing the environmental footprint of beef production. Genetic and environmental factors influence animal feed efficiency, leading to phenotypic variability when exposed to different environmental conditions (i.e., temperature and nutritional level). Thus, our aim was to assess potential genotype-by-environment (G × E) interactions for dry matter intake (DMI) and residual feed intake (RFI) in Nellore cattle (Bos taurus indicus) based on bi-trait reaction norm models (RN) and evaluate the genetic association between RFI and DMI across different environmental gradient (EG) levels. For this, we used phenotypic information on 12,958 animals (young bulls and heifers) for DMI and RFI recorded during 158 feed efficiency trials., Results: The heritability estimates for DMI and RFI across EG ranged from 0.26 to 0.54 and from 0.07 to 0.41, respectively. The average genetic correlations (± standard deviation) across EG for DMI and RFI were 0.83 ± 0.19 and 0.81 ± 0.21, respectively, with the lowest genetic correlation estimates observed between extreme EG levels (low vs. high) i.e. 0.22 for RFI and 0.26 for DMI, indicating the presence of G × E interactions. The genetic correlation between RFI and DMI across EG levels decreased as the EG became more favorable and ranged from 0.79 (lowest EG) to 0.52 (highest EG). Based on the estimated breeding values from extreme EG levels (low vs. high), we observed a moderate Spearman correlation of 0.61 (RFI) and 0.55 (DMI) and a selection coincidence of 53.3% and 40.0% for RFI and DMI, respectively., Conclusions: Our results show evidence of G × E interactions on feed efficiency traits in Nellore cattle, especially in feeding trials with an average daily gain (ADG) that is far from the expected of 1 kg/day, thus increasing reranking of animals., (© 2023. The Author(s).)

This study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFI test ) and for the whole population (RFI pop ) in Nellore beef cattle. It also aimed to evaluate the correlations between RFI pop and RFI test with growth, reproductive, and carcass traits. Genotypic and phenotypic records from 8354 animals were used. An analysis of variance (ANOVA) was performed to verify the adequacy of the regression equations applied to estimate the RFI test and RFI pop . The (co)variance components were obtained using the single-step genomic best linear unbiased prediction under single and two-trait animal model analyses. The genetic and phenotypic correlations between RFI test and RFI pop with dry matter intake, frame, growth, reproduction, and carcass-related traits were evaluated. The prediction ability and bias were estimated to compare the RFI test and RFI pop genomic breeding values (GEBV). The RFI pop ANOVA showed a higher significance level (p < 0.0001) than did the RFI test for the fixed effects. The RFI pop displayed higher additive genetic variance estimated than the RFI test , although the RFI pop and RFI test displayed similar heritabilities. Overall, the RFI test showed higher residual correlations with growth, reproductive, and carcass traits, while the RFI pop displayed higher genetic correlations with such traits. The GEBV for the RFI test was slightly biased than GEBV RFI pop . The approach to calculate the RFI influenced the decomposition and estimation of variance components and genomic prediction for RFI. The application of RFI pop would be more appropriate for genetic evaluation purpose to adjust or correct for non-genetic effects and to decrease the prediction bias for RFI., (© 2022. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.)

A bioeconomic model was developed to calculate the economic value (ev) of reproductive and growth performance, feed efficiency and carcass traits of a seedstock Nellore herd. Data from a full-cycle cattle operation (1,436 dams) located in the Brazilian Cerrado were assessed. The ev was calculated by the difference in profit before and after one-unit improvement in the trait, with others remaining unchanged. The ev was standardized by the phenotypic standard deviation of each trait. Preweaning average daily gain (ADG) was the most economically important trait evaluated (R$ 58.04/animal/year), followed by age at first calving (R$ 44.35), postweaning ADG (R$ 31.43), weight at 450 days (R$ 25.36), accumulated productivity (R$ 21.43), ribeye area (R$ 21.35), calving interval (R$ 19.97), feed efficiency (R$ 15.24), carcass dressing per cent (R$ 8.27), weight at 120 days (R$ 6.22), weight at 365 days (R$ 6.06), weight at weaning (210 days, R$ 5.82), stayability (R$ 5.70) and the probability of early calving (R$ 0.32). The effects of all traits on profits are evidence that their selection may result in the economic and genetic progress of the herd if there is genetic variability., (© 2021 Wiley-VCH GmbH.)