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Genetic Parameter Estimates for Carcass and Meat Quality Traits and Their Genetic Associations With Sexual Precocity Indicator Traits in Nellore Cattle

大理石纹肉 生物 肉牛 遗传力 肌内脂肪 最佳线性无偏预测 遗传相关 限制最大似然 肉的嫩度 温柔 动物科学 陛下 选择(遗传算法) 生物技术 遗传变异 遗传学 统计 最大似然 基因 数学 人工智能 计算机科学
作者
Leonardo Machestropa Arikawa,Lúcio Flávio Macêdo Mota,Patrícia Iana Schmidt,Bruna Maria Salatta,Sindy Liliana Caivio Nasner,João Barbosa da Silva Neto,Larissa Fernanda Simielli Fonseca,Ana Fabrícia Braga Magalhães,Delvan Alves da Silva,Roberto Carvalheiro,Luis Artur Loyola Chardulo,Lúcia Galvão de Albuquerque
出处
期刊:Journal of Animal Breeding and Genetics [Wiley]
标识
DOI:10.1111/jbg.12927
摘要

ABSTRACT For developing beef cattle breeding programmes, it is essential to understand the genetic basis of economically relevant traits, such as carcass, meat quality and female sexual precocity. However, the direct selection of most of these traits is a challenge for producers because of the high cost and measurement difficulty. Genetic correlation estimates between carcass and meat quality traits obtained after slaughter and sexual precocity indicator traits in Nellore are limited in the literature. Thus, this study aimed to estimate genetic parameters for longissimus muscle area (LMA), backfat thickness (BF), hot carcass weight (HCW), shear force tenderness (SF), marbling score (MARB), intramuscular fat content (IMF), age at first calving (AFC), heifer pregnancy (HP) and scrotal circumference (SC) in Nellore cattle, using pedigree and genomic information. For this, data from 6910 young bulls with phenotypic information for carcass and meat traits, 230,682 for sexual precocity indicator traits, and 17,850 animals genotyped with or imputed to the Illumina Bovine HD BeadChip were used. The (co)variance components and genetic parameters were estimated considering BLUP and single‐step GBLUP (ssGBLUP) models via Bayesian inference using the GIBBSF90+ software. The multi‐trait animal model included additive and residual genetic effects as random; the fixed effects of contemporary group (for all traits) and date of analysis as classes (for BF, SF and MARB); and the linear effects of age at slaughter (all carcass and meat traits) and age at yearling (YW and SC) as covariates. Heritability estimates ranged from 0.13 to 0.34 for carcass and meat quality traits, and for SC, AFC and HP, were 0.33, 0.07 and 0.29, respectively. Favourable genetic correlations were estimated between YW‐HCW (0.79 ± 0.03), YW‐LMA (0.28 ± 0.05), YW‐SC (0.35 ± 0.03), HCW‐LMA (0.44 ± 0.05), HCW‐SF (−0.22 ± 0.09), HCW‐SC (0.19 ± 0.05), MARB‐IMF (0.90 ± 0.07), SF‐IMF (−0.20 ± 0.11), BF‐MARB (0.29 ± 0.08), BF‐IMF (0.22 ± 0.09), BF‐AFC (−0.21 ± 0.07) and BF‐HP (0.24 ± 0.10). In general, the correlations between carcass traits and those of meat quality were low to moderate. Additionally, carcass and meat quality traits did not exhibit strong genetic correlations with female precocity indicators. So, to achieve significant genetic advances in female sexual indicator traits, carcass composition and meat quality, these traits must compose selection indices for Nellore cattle.
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