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Analysis of Survival in Dairy Cows with Supplementary Data on Type Scores and Housing Systems from a Region of Northwest Germany

机译:使用德国西北部地区的类型得分和住房系统的补充数据分析奶牛的存活率

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In survival analysis, type traits can be included as covariates to evaluate their use as predictors for sur- vival. One problem in such an analysis is the availabil- ity of suitable data. Whereas data on the length of pro- ductive life (LPL) of individual cows can be retrieved from milk recording data, for type traits, all cows in the population must be scored for type at least once. In the present analysis, a dataset from the Osnabruck region in northwestern Germany, which fulfilled this requirement in recent years, was used. Data consisted of 169,733 cows with information on LPL for calving years 1980 to 1996 (dataset I) and of 39,233 cows with information on LPL and type for calving years 1990 to 1996 (dataset II). A further dataset (III) contained 43,116 cows from calving years 1987 to 1996 and in- cluded information on the housing system for each herd. The basic model included stage of lactation, relative production within herd, change of herd size, and year- season as time dependent effects; age at calving as a time-independent effect; and herd-year-season and sire as random effects. Other effects (information on type, housing system) were included additionally. For data- set II, the scores for 15 linear type traits were also included as corrected phenotypic values, estimated breeding values, and residuals from a previous BLUP analysis. The package Survival Kit 3.0 was used for all analyses. The results indicate a moderate heritability of 0.17 and 0.18 for true and functional LPL (dataset I). Almost all type traits analyzed (dataset II) exceeded a 0.001 level of significance in their effect on survival. The strongest relationships between survival and type were found for udder depth, fore udder attachment, and front teat placement. The main result from the comparison of housing systems (dataset III) was that bedding has a positive effect on survival.
机译:在生存分析中,类型特征可以作为协变量包括在内,以评估其作为生存预测因子的用途。这种分析的一个问题是合适数据的可用性。尽管可以从牛奶记录数据中获取有关单头母牛的繁殖寿命(LPL)的数据,但对于类型特征,必须对种群中的所有母牛进行至少一次类型评分。在当前的分析中,使用了德国西北部Osnabruck地区的数据集,该数据集近年来已满足这一要求。数据包括169733头1980年至1996年产犊的LPL信息的母牛(数据集I)和39233头1990年至1996年产犊的LPL信息和类型的母牛(数据集II)。另一个数据集(III)包含1987年至1996年产犊的43,116头母牛,并包括每头牛的住房系统信息。基本模型包括泌乳阶段,牛群内的相对产量,牛群大小的变化以及作为时间依赖性的年季。产犊年龄与时间无关;以及牧群年份季节和父亲作为随机效应。其他效果(有关类型,房屋系统的信息)也包括在内。对于数据集II,还包括15个线性型性状的分数,作为校正的表型值,估计的育种值和以前的BLUP分析得出的残差。软件包Survival Kit 3.0用于所有分析。结果表明,对于真实和功能性LPL(数据集I),适度的遗传力分别为0.17和0.18。几乎所有分析过的类型性状(数据集II)对生存的影响均超过0.001水平的显着性。在乳房深度,前乳房附着和前乳头放置方面发现了生存与类型之间最强的关系。比较住房系统(数据集III)的主要结果是,寝具对生存率有积极影响。

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