Contribution of Fat Adjustment to Residual Feed Intake Estimation in Beef Cattle

Including fat thickness as a covariate in the regression model used to calculate residual feed intake (RFI) could help preserve carcass quality traits, such as marbling, flavour and juiciness, by accounting for variation in fat deposition. This study aimed to: (1) investigate the benefits of adjusting RFI for rump fat thickness (RFT); (2) estimate variance components and genetic correlations between RFI-calculated with (RFI<sub>F</sub>) and without (RFI<sub>W</sub>) adjustment for RFT-and growth, reproduction and carcass traits using genomic information in beef cattle; and (3) compute accuracy, bias and dispersion of RFI<sub>F</sub> and RFI<sub>W</sub> genomic breeding values predicted using single-step GBLUP (ssGBLUP). We hypothesised that adjusting for RFT would account for a small proportion of RFI variability, and that genetic parameter estimates would support more balanced selection decisions. Phenotypic records were collected from 9094 Nellore animals (3253 females and 5952 males) over 14 feed efficiency tests conducted from 2011 to 2024. The pedigree included 17,407 animals, of which 5812 were genotyped. Linear and threshold animal models were applied for continuous and categorical traits, respectively. Heritability estimates were low for RFI<sub>W</sub> (0.17) and RFI<sub>F</sub> (0.16), with a strong genetic correlation between them (0.98), and a weak genetic correlation between RFI<sub>W</sub> and RFT (0.15). Spearman correlations between RFI<sub>F</sub> and RFI<sub>W</sub> breeding values were high: 0.98 in females and 0.95 in males. Genetic correlations of RFI<sub>W</sub> and RFI<sub>F</sub> with growth, reproduction and carcass traits ranged from -0.33 to 0.35. Prediction accuracy was similar for RFI<sub>F</sub> (0.43) and RFI<sub>W</sub> (0.44), whereas bias (0.00 for RFI<sub>w</sub> and 0.00 for RFI<sub>F</sub>) and dispersion (0.05 for RFI<sub>w</sub> and 0.03 for RFI<sub>F</sub>) showed minor differences. Although RFI<sub>F</sub> captured slightly more genetic variability, the impact was minimal and no differences were observed between RFI<sub>F</sub> and RFI<sub>W</sub>. The genetic correlations between RFI and traits related to growth, reproduction and carcass were close to zero to moderate, indicating that selection for RFI is unlikely to negatively impact these other traits. However, it is essential to consider the full set of traits in the selection process to avoid potential drawbacks to the overall genetic progress of the herd.

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Journal
Journal of Animal Breeding and Genetics
Published
2026-02-23
DOI
https://doi.org/10.1111/jbg.70045
Primary Topic
Genetic and phenotypic traits in livestock
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article
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article

Contribution of Fat Adjustment to Residual Feed Intake Estimation in Beef Cattle

M. J. I. Yokoo, C. R. Marcondes, Larissa Bordin Temp, R. D. Sainz et al.
Journal of Animal Breeding and Genetics
Genetic and phenotypic traits in livestock
article

Contribution of Fat Adjustment to Residual Feed Intake Estimation in Beef Cattle

M. J. I. Yokoo, C. R. Marcondes, Larissa Bordin Temp, R. D. Sainz, Jorge Hidalgo, Fernando de Oliveira Bussiman, Fernando Baldi, Letícia Pereira, Daniela Lourenco
article en

Abstract

Including fat thickness as a covariate in the regression model used to calculate residual feed intake (RFI) could help preserve carcass quality traits, such as marbling, flavour and juiciness, by accounting for variation in fat deposition. This study aimed to: (1) investigate the benefits of adjusting RFI for rump fat thickness (RFT); (2) estimate variance components and genetic correlations between RFI-calculated with (RFI<sub>F</sub>) and without (RFI<sub>W</sub>) adjustment for RFT-and growth, reproduction and carcass traits using genomic information in beef cattle; and (3) compute accuracy, bias and dispersion of RFI<sub>F</sub> and RFI<sub>W</sub> genomic breeding values predicted using single-step GBLUP (ssGBLUP). We hypothesised that adjusting for RFT would account for a small proportion of RFI variability, and that genetic parameter estimates would support more balanced selection decisions. Phenotypic records were collected from 9094 Nellore animals (3253 females and 5952 males) over 14 feed efficiency tests conducted from 2011 to 2024. The pedigree included 17,407 animals, of which 5812 were genotyped. Linear and threshold animal models were applied for continuous and categorical traits, respectively. Heritability estimates were low for RFI<sub>W</sub> (0.17) and RFI<sub>F</sub> (0.16), with a strong genetic correlation between them (0.98), and a weak genetic correlation between RFI<sub>W</sub> and RFT (0.15). Spearman correlations between RFI<sub>F</sub> and RFI<sub>W</sub> breeding values were high: 0.98 in females and 0.95 in males. Genetic correlations of RFI<sub>W</sub> and RFI<sub>F</sub> with growth, reproduction and carcass traits ranged from -0.33 to 0.35. Prediction accuracy was similar for RFI<sub>F</sub> (0.43) and RFI<sub>W</sub> (0.44), whereas bias (0.00 for RFI<sub>w</sub> and 0.00 for RFI<sub>F</sub>) and dispersion (0.05 for RFI<sub>w</sub> and 0.03 for RFI<sub>F</sub>) showed minor differences. Although RFI<sub>F</sub> captured slightly more genetic variability, the impact was minimal and no differences were observed between RFI<sub>F</sub> and RFI<sub>W</sub>. The genetic correlations between RFI and traits related to growth, reproduction and carcass were close to zero to moderate, indicating that selection for RFI is unlikely to negatively impact these other traits. However, it is essential to consider the full set of traits in the selection process to avoid potential drawbacks to the overall genetic progress of the herd.

Journal of Animal Breeding and Genetics
University of Georgia (US), Universidade de São Paulo (BR), Brazilian Agricultural Research Corporation (BR), University of California, Davis (US), Universidade Estadual Paulista (Unesp) (BR), Ministry of Agriculture, Livestock, and Food Supply (BR)
Openalex Percentile: Top 43%
Genetic and phenotypic traits in livestock
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