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生殖指数与荷斯坦奶牛的生育结果、产奶量和存活率的关系。

Associations of reproductive indices with fertility outcomes, milk yield, and survival in Holstein cows.

机构信息

Department of Animal Sciences, Colorado State University, Fort Collins 80521.

Department of Animal Sciences, University of Florida, Gainesville 32611.

出版信息

J Dairy Sci. 2020 Jul;103(7):6647-6660. doi: 10.3168/jds.2019-17867. Epub 2020 Apr 29.

Abstract

The study is part of a research effort investigating potential associations between genomic variation and fertility of Holstein cows. The objective was to compare the reproductive performance of Holstein cows in 3 categories of 2 reproductive indices (RI) that were developed for the allocation of cows in a ranking for potential fertility, based on the predicted probability of pregnancy. The associations between categories of the developed indices and multiple fertility variables in a large multistate population of Holstein cows were tested. In addition, we analyzed associations among the RI categories with milk yield and survival. Based on phenotypic information from individual cows, 2 reproductive indices (RI1 and RI2) were developed, representing a predicted probability that a cow will become pregnant at first artificial insemination postpartum, as a function of explanatory variables used in a logistic model. Data from a total of 11,733 cows calving in 16 farms located in 4 regions of the United States (Northeast, Midwest, Southeast, and Southwest) were available. Cows were enrolled at parturition and monitored weekly for reproductive events, health status, milk yield, and survival. To develop the indices, potential significant effects were initially tested by univariate analyses. Effects with P ≤ 0.05 were offered to the multivariate analysis, and the final models were determined through backward elimination, considering potentially significant interactions. The final model for RI1 included the random effect of farm and a complement of significant fixed effects as explanatory variables influencing a pregnancy outcome: (1) incidence of retained fetal membranes; (2) metritis; (3) clinical endometritis; (4) lameness at 35 days in milk (DIM); (5) resumption of postpartum ovulation by 50 DIM; (6) season of calving; and (7) parity number. The model for RI2 included (1) parity number; (2) body condition score at 40 DIM; (3) incidence of retained fetal membranes; (4) metritis; (5) resumption of postpartum ovulation by 50 DIM; (6) region; (7) subclinical ketosis; (8) mastitis; (9) clinical endometritis; and (10) milk yield at the first milk test after calving; as well as the interaction effects of postpartum resumption of ovulation by 50 DIM × region; mastitis × region; and milk yield at the first milk test after calving × parity number. Multivariate logistic regression, ANOVA, and survival analysis were used to test the correspondence between the resulting RI and individual fertility, milk yield, and survival from the population. To facilitate the analyses, the resulting RI values were categorized as low for cows in the lowest quartile, medium for cows within the interquartile range, or high for cows in the top quartile. We found consistent agreement between categories of the predicted RI and the measures of fertility and survival collected from individual cows. We conclude that the proposed RI represent a viable approach to refine the allocation of cows into potential low- and high-fertility populations.

摘要

这项研究是一项旨在调查基因组变异与荷斯坦奶牛生育能力之间潜在关联的研究工作的一部分。目的是比较基于预测妊娠概率分配用于潜在生育能力排名的 3 种 2 种生殖指数 (RI) 类别中荷斯坦奶牛的繁殖性能。在一个大型多状态荷斯坦奶牛群体中,测试了开发指数的类别与多个生育变量之间的关联。此外,我们还分析了 RI 类别与产奶量和存活率之间的关联。根据个体奶牛的表型信息,开发了 2 种生殖指数 (RI1 和 RI2),代表了奶牛在产后首次人工授精时怀孕的预测概率,作为逻辑模型中使用的解释变量的函数。共有来自美国 4 个地区(东北部、中西部、东南部和西南部)的 16 个农场的 11733 头奶牛产犊的数据可用。奶牛在分娩时被纳入研究,并每周监测生殖事件、健康状况、产奶量和存活率。为了开发这些指数,最初通过单变量分析测试了潜在的显著影响。P≤0.05 的影响因素被纳入多变量分析,最终模型通过向后消除确定,同时考虑了潜在的显著交互作用。RI1 的最终模型包括农场的随机效应和一组对妊娠结果有影响的显著固定效应作为解释变量:(1)胎衣不下发生率;(2)子宫内膜炎;(3)临床子宫内膜炎;(4)产后 35 天跛行(DIM);(5)产后 50 天恢复排卵;(6)产犊季节;(7)胎次数。RI2 的模型包括(1)胎次数;(2)产后 40 天的体况评分;(3)胎衣不下发生率;(4)子宫内膜炎;(5)产后 50 天恢复排卵;(6)地区;(7)亚临床酮病;(8)乳腺炎;(9)临床子宫内膜炎;(10)产后首次泌乳试验的产奶量;以及产后 50 天恢复排卵×地区、乳腺炎×地区和产后首次泌乳试验的产奶量×胎次数的交互作用。使用多元逻辑回归、方差分析和生存分析来测试人群中产生的 RI 与个体生育能力、产奶量和存活率之间的一致性。为了便于分析,将产生的 RI 值分类为最低四分位数的奶牛为低,四分位距内的奶牛为中,最高四分位数的奶牛为高。我们发现预测 RI 类别与个体奶牛生育力和存活率的测量结果之间存在一致的一致性。我们得出结论,所提出的 RI 代表了一种可行的方法,可以细化将奶牛分配到潜在的低生育力和高生育力群体中。

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