Using of Conspicuous of Body Angularities Type Traits to Milk Yields as Dairy Cattle Selection Preferences

Q4 Agricultural and Biological Sciences Basrah Journal of Agricultural Sciences Pub Date : 2023-06-30 DOI:10.37077/25200860.2023.36.1.19
S. Prabowo, M. Garip
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Abstract

Numerous papers have been published on body cattle angularities subject in a few backward decades. However, the preeminent body angularities to the milk yield are unstipulated assertively. Hence, the current odyssey was to determine the transcendence body angular of dairy cattle interrelated with the milk yield for selection preferences. In total, 121 head of Holstein cows and seven reputable cattle body angularities were engaged as samples and measured variables for investigation. The software R version 4.2.1 and RStudio was operated simultaneously to facilitate statistical analysis. Later, the principal components (PCA), correlation, and regression analysis were carried out in that order. The PCA specified the thurl angle (TLA), hock side view angle (HSA), hock back views angle (HBA), and fore udder angle (FUA) as crucial factors of body cattle angularities. Then, the correlation analysis appointed HBA and TLA in series as the best trait related to milk yields. The regression analysis was merely entrusted to the HBA as a factor for prognosticating milk yield potency. Thus, the upshot of the ongoing exploration prompted the HBA as the main priority for milk yield selection preferences, followed by TLA. Both were usable on the calf, heifer, and cow selection scheme but should be enforced regularly.
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利用体角型性状对产奶量的显著性作为奶牛的选择偏好
在过去的几十年里,关于牛体角的研究已经发表了大量的论文。然而,卓越的身体角度奶产量没有明确规定。因此,目前的工作是确定奶牛的超越体角与产奶量的关系,以进行选择偏好。总共以121头荷斯坦奶牛和7头声誉良好的牛体角为样本和测量变量进行调查。同时使用R 4.2.1版软件和RStudio进行统计分析。然后依次进行主成分分析(PCA)、相关分析和回归分析。主成分分析确定了飞旋角(TLA)、飞节侧视角(HSA)、飞节后视角(HBA)和前乳房角度(FUA)是体牛角度的关键因素。然后,通过相关分析确定HBA和TLA串联为与产奶量相关的最佳性状。回归分析仅委托HBA作为预测产奶量效力的因素。因此,正在进行的探索的结果提示HBA是奶产量选择偏好的主要优先级,其次是TLA。这两种方法都适用于小牛、小母牛和奶牛的选择方案,但应定期执行。
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来源期刊
Basrah Journal of Agricultural Sciences
Basrah Journal of Agricultural Sciences Environmental Science-Pollution
CiteScore
1.20
自引率
0.00%
发文量
35
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