Suppr超能文献

用于描述水牛(Bubalus bubalis)产奶量和奶成分泌乳曲线的非线性模型比较。

Comparison of non-linear models to describe the lactation curves for milk yield and composition in buffaloes (Bubalus bubalis).

作者信息

Ghavi Hossein-Zadeh N

机构信息

Department of Animal Science, Faculty of Agricultural Sciences,University of Guilan,PO Box 41635-1314,Rasht,Iran.

出版信息

Animal. 2016 Feb;10(2):248-61. doi: 10.1017/S1751731115001846. Epub 2015 Sep 10.

Abstract

In order to describe the lactation curves of milk yield (MY) and composition in buffaloes, seven non-linear mathematical equations (Wood, Dhanoa, Sikka, Nelder, Brody, Dijkstra and Rook) were used. Data were 116,117 test-day records for MY, fat (FP) and protein (PP) percentages of milk from the first three lactations of buffaloes which were collected from 893 herds in the period from 1992 to 2012 by the Animal Breeding Center of Iran. Each model was fitted to monthly production records of dairy buffaloes using the NLIN and MODEL procedures in SAS and the parameters were estimated. The models were tested for goodness of fit using adjusted coefficient of determination (Radj(2)), root means square error (RMSE), Durbin-Watson statistic and Akaike's information criterion (AIC). The Dijkstra model provided the best fit of MY and PP of milk for the first three parities of buffaloes due to the lower values of RMSE and AIC than other models. For the first-parity buffaloes, Sikka and Brody models provided the best fit of FP, but for the second- and third-parity buffaloes, Sikka model and Brody equation provided the best fit of lactation curve for FP, respectively. The results of this study showed that the Wood and Dhanoa equations were able to estimate the time to the peak MY more accurately than the other equations. In addition, Nelder and Dijkstra equations were able to estimate the peak time at second and third parities more accurately than other equations, respectively. Brody function provided more accurate predictions of peak MY over the first three parities of buffaloes. There was generally a positive relationship between 305-day MY and persistency measures and also between peak yield and 305-day MY, calculated by different models, within each lactation in the current study. Overall, evaluation of the different equations used in the current study indicated the potential of the non-linear models for fitting monthly productive records of buffaloes.

摘要

为了描述水牛的产奶量(MY)和成分的泌乳曲线,使用了七个非线性数学方程(伍德、达诺阿、西卡、内尔德、布罗迪、迪杰斯特拉和鲁克)。数据是1992年至2012年期间伊朗动物育种中心从893个牛群收集的水牛前三个泌乳期的116,117条产奶量、乳脂肪(FP)和乳蛋白(PP)百分比的测定日记录。使用SAS中的NLIN和MODEL程序将每个模型拟合到奶牛的月度生产记录,并估计参数。使用调整后的决定系数(Radj(2))、均方根误差(RMSE)、德宾-沃森统计量和赤池信息准则(AIC)对模型的拟合优度进行检验。由于RMSE和AIC值低于其他模型,迪杰斯特拉模型对水牛前三个胎次的产奶量和乳蛋白提供了最佳拟合。对于头胎水牛,西卡和布罗迪模型对乳脂肪提供了最佳拟合,但对于二胎和三胎水牛,西卡模型和布罗迪方程分别对乳脂肪的泌乳曲线提供了最佳拟合。本研究结果表明,伍德和达诺阿方程比其他方程更能准确估计产奶量峰值出现的时间。此外,内尔德和迪杰斯特拉方程分别比其他方程更能准确估计二胎和三胎时的峰值时间。布罗迪函数对水牛前三个胎次的产奶量峰值提供了更准确的预测。在本研究中,每个泌乳期内,不同模型计算的305天产奶量与持续性指标之间以及峰值产量与305天产奶量之间通常呈正相关。总体而言,对本研究中使用的不同方程的评估表明了非线性模型拟合水牛月度生产记录的潜力。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验