On fitting curves to lactation data

Author:

Cobby J. M.,Le Du Y. L. P.

Abstract

ABSTRACTThe usual method of fitting the model y = Anb exp(−cn) to lactation data, by a multiple regression of logey on n and logen, can result in an ill-fitting curve. An analysis of the untransformed data provides a better fit but requires more extensive computation and a simple approximation to this procedure is given. Since the parameters of this model have no direct biological interpretation two alternative models are introduced, each having a parameter measuring the persistency of lactation.

Publisher

Cambridge University Press (CUP)

Subject

Animal Science and Zoology

Cited by 122 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

1. Improving Lactation Curve Prediction by Incorporating Weather and Cow Behaviour;2023 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON);2023-03-22

2. Evaluation of nonlinear models to predict milk yield and composition of beef cows: A meta-analysis;Animal Feed Science and Technology;2022-12

3. Yarı entansif koşullarda yetiştirilen Saanen keçilerinde kısmi laktasyon süt verimlerinin tahmini;Ege Üniversitesi Ziraat Fakültesi Dergisi;2022-07-04

4. Comparison of models for lactation curves of Holstein, Brown Swiss, and F1 crossbred cows under subtropical conditions;Tropical Animal Health and Production;2022-05-31

5. Estimation of genetic parameters of Wood’s lactation curve parameters using Bayesian and REML methods for milk production trait of Holstein dairy cattle;Journal of Applied Animal Research;2022-05-27

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