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首页> 外文期刊>Journal of Animal Science >A model with heterogeneous thresholds for subjective traits: Fat cover and conformation score in the Pirenaica beef cattle1
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A model with heterogeneous thresholds for subjective traits: Fat cover and conformation score in the Pirenaica beef cattle1

机译:主观性状具有异质性阈值的模型:比雷牛(Pirenaica)肉牛的脂肪覆盖率和构象评分

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摘要

ACurrent selection schemes for livestock improvement use a wide variety of phenotypic traits. Some of them, such as sensory, type, or carcass traits, obtain their records from subjective grading performed by trained technicians. Data from this subjective evaluation usually involve classification under a categorical and arbitrary predefined scale, whose output may lead to strong departures from the Gaussian distribution. In addition, the scale of grading may be different according to different technicians. To study this phenomenon, we have analyzed subjective conformation (CON) and fat cover (FAT) scores in the Pirenaica beef cattle breed from data provided by 12 different slaughterhouses. Three statistical models were used: 1) a Gaussian linear model; 2) an ordered category threshold model; and 3) a specific slaughterhouse ordered category threshold model. These models were analyzed through a Bayesian analysis via a Gibbs sampler with a data augmentation step. Posterior mean estimates of heritability ranged from 0.23 to 0.26 for CON, and from 0.13 to 0.16 for FAT. Statistical models were compared by the deviance information criteria, and the slaughterhouse-specific ordered category threshold model was selected as the most plausible. This result was confirmed by the fact that the threshold estimates differed noticeably between slaughterhouses. Finally, the proposed model for genetic evaluation increased the expected selection response by up to 7.6% for CON and 11.2% for FAT. [PUBLICATION ABSTRACT]
机译:当前用于牲畜改良的选择方案利用了各种各样的表型性状。其中一些(例如感官,类型或car体特征)从受过培训的技术人员进行的主观评分中获得其记录。来自该主观评估的数据通常涉及分类和任意预定规模的分类,其输出可能导致与高斯分布的明显背离。另外,根据不同的技术人员,分级的规模可以不同。为了研究这种现象,我们从12个不同的屠宰场提供的数据中分析了比雷埃尼察肉牛品种的主观构象(CON)和脂肪覆盖(FAT)得分。使用了三个统计模型:1)高斯线性模型; 2)有序类别阈值模型; 3)特定的屠宰场订购类别阈值模型。这些模型通过使用数据增强步骤的Gibbs采样器通过贝叶斯分析进行了分析。对于CON,后遗传率的平均估计值范围为0.23至0.26,对于FAT,范围为0.13至0.16。通过偏差信息标准对统计模型进行了比较,并选择了屠宰场特定的有序类别阈值模型。屠宰场之间的阈值估计值明显不同,这一事实得到了证实。最后,提出的遗传评估模型将CON的预期选择响应提高了7.6%,将FAT的选择响应提高了11.2%。 [出版物摘要]

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