Ojo Ayooluwa O, Mulim Henrique A, Garcia Andre, Retallick-Riley Kelli, Miller Stephen P, Oliveira Hinayah R
Department of Animal Sciences, Purdue University, West Lafayette, Indiana, USA.
Angus Genetics Inc. American Angus Association, St. Joseph, Missouri, USA.
J Anim Breed Genet. 2025 Jun 30. doi: 10.1111/jbg.70002.
Mature cow size, often defined by mature cow weight (MWT), height (MHT) and body condition score (BCS), is crucial to cow-calf profitability, maintenance efficiency and reproductive performance. Although MWT and MHT are often included in national cattle evaluations by many breed organisations, BCS adjustments are applied less consistently. This study investigated the impact of different modelling approaches on the estimation of breeding values for MWT, with a focus on how BCS is accounted for across models. The dataset provided by American Angus Association comprised 382,156 MWT and BCS records from 209,491 cows. Four modelling approaches were evaluated: Model 1 does not consider BCS; Model 2 treated BCS as a categorical fixed effect; Model 3 used pre-adjusted records standardised for BCS and age; and Model 4 used a recursive model to assess MWT as a genetically independent trait from BCS. Spearman correlations between breeding values predicted across models ranged from 0.79 (between Models 1 and 4) to 0.95 (between Models 1 and 2), indicating that 5%-21% of bulls could have different rankings depending on the model used. Concordance in sire selection was assessed between the top 10% of sires in each model, and model-pair comparison revealed differences ranging from 19% (between Models 1 and 2) to 40% (between Models 3 and 4). These differences highlight the potential for model choice to influence the selection outcomes. Model selection can significantly affect the sire rankings, highlighting the importance of carefully selecting the model that best aligns with the selection objectives and the underlying biology of the traits being evaluated. Although Model 4 offers theoretical advantages, this study does not allow for a definitive conclusion on its overall effectiveness, as no simulations were performed. Additional research is needed to confirm its advantages.
成熟母牛的体型,通常由成熟母牛体重(MWT)、身高(MHT)和体况评分(BCS)来定义,对于母牛-犊牛的盈利能力、饲养效率和繁殖性能至关重要。尽管许多品种组织在国家牛只评估中经常纳入MWT和MHT,但BCS调整的应用却不太一致。本研究调查了不同建模方法对MWT育种值估计的影响,重点关注各模型中BCS的处理方式。美国安格斯协会提供的数据集包含来自209,491头母牛的382,156条MWT和BCS记录。评估了四种建模方法:模型1不考虑BCS;模型2将BCS视为分类固定效应;模型3使用针对BCS和年龄进行标准化的预调整记录;模型4使用递归模型将MWT评估为与BCS遗传独立的性状。各模型预测的育种值之间的斯皮尔曼相关性在0.79(模型1和模型4之间)至0.95(模型1和模型2之间)之间,这表明根据所使用的模型,5%-21%的公牛可能会有不同的排名。评估了每个模型中排名前10%的公牛之间的选种一致性,模型对比较显示差异范围从19%(模型1和模型2之间)到40%(模型3和模型4之间)。这些差异凸显了模型选择对选择结果产生影响的可能性。模型选择会显著影响公牛排名,这突出了仔细选择最符合选择目标和所评估性状潜在生物学特性的模型的重要性。尽管模型4具有理论优势,但由于未进行模拟,本研究无法就其整体有效性得出明确结论。需要进一步研究来证实其优势。