Test-day model of daily milk yield prediction across stages of lactation in Egyptian buffaloes

Author:

Amin A. A.

Abstract

Abstract. farms in Ismailia region, which exist east of Cairo. Two data sets were considered for analysis of variance according to lactation length. The first data set is TDY of the short lactation (5–10 months: LPS). The 2nd data set is the TDY of the long lactation (LPL > 305 days). Daily milk yield prediction equations were investigated using multiple lactations, separate lactations, and three groups of age at first calving. Polynomial regression functions were fitted to study the effect of stage of lactation on variation in test-day milk yield observations (TDY). Results of the present study showed that the effect of herd (farm, season and year of calving) on variation of TDY were significant and accounted for 35.22% of the total variance for the data set of LPL. Variations in TDY due to the effect of either order of lactation or age at first calving groups were significant and accounted for 8.25% and 13.50%, respectively of the total variance. The overall least-square means of TDY were 5.5 and 7.8 Kg for LPS and LPL, respectively. The highest frequencies of similar TDY observations appeared in the early months across stage of lactation. The peak of the measured TDY obtained among the 4th and the 6th month of lactation of the pooled parity data set. Prediction equation of TDY across days of lactation (Days in Milk:DIM) using pooled parities was as the following: Y = 3.4103 +.0466X − .0004X2 + .00001X3 − 1.03E-8X4 Prediction equation of TDY across months of lactation (Months in Milk:MIM) using pooled parity data set was as the following: Y = 1.9634 + 2.7927X − .8931X2 + .1602X3 − .0138X4. Prediction equations for TDY per parity and for each age at first calving group were computed.

Publisher

Copernicus GmbH

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3