用自动挤奶系统日记录描述希俄斯羊泌乳曲线的模型比较

Maria Karangeli, Z. Abas, T. Koutroumanidis, Chrisovaladis Malesios, C. Giannakopoulos
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引用次数: 8

摘要

本研究的目的是:(i)比较描述希奥斯羊泌乳曲线的五种模型(Wood、Cobby & Le Du、Wilmink、Cappio Borlino、Djikstra); (ii)确定与环境因素(季节)和动物因素(胎次)相关的泌乳参数变化。使用了从自动挤奶系统获得的61,705份每日产奶量记录的数据库。每次泌乳均对泌乳模型进行单独调整。对参数估计值进行方差分析比较。模型比较的拟合优度度量为决定系数(R)、均方误差均值(MMSE)、赤池信息准则(AIC)、修正赤池信息准则(AICc)和贝叶斯信息准则(BIC)。Wood模型的信息标准最小(MMSE = 347.4681, AIC = 1,056.436, AICc = 1,056.733, BIC = 1,063.856),决定系数最高(R=0.79)。Djikstra模型的信息标准值最高(MMSE = 636.6438, AIC = 1,076.621, AICc = 1,077.117, BIC = 1,086.582),同时决定系数值最低(R=0.59)。总体而言,Wood(1967)模型的调整效果最好。尽管较新,但Djikstra(1997)的模型基于机制,参数数量较多,所使用的数据收敛性较低。Wood模型(1967)在仅用三个参数产生良好拟合测量方面具有更大的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Models for Describing the Lactation Curves of Chios Sheep Using Daily Records Obtained from an Automatic Milking System
The objectives of this study were: (i) to compare five models (Wood, Cobby & Le Du, Wilmink, Cappio Borlino, Djikstra) for describing the lactation curve of Chios sheep, (ii) to identify variation in lactation parameters related to environmental factors (season) and animal factors (parity). A data base on 61,705 recordings of daily milk production obtained from an automatic milking system was used. The lactation models were individually adjusted for each lactation. Analysis of variance was performed for the comparison of the parameter estimates. The goodness of fit measures used for comparisons of the models was the coefficient of determination (R), mean of mean square error (MMSE), Akaike information criterion (AIC), corrected Akaike information criterion (AICc) and Bayesian information criterion (BIC). Wood model had the lowest values for information criteria (MMSE = 347.4681, AIC = 1,056.436, AICc = 1,056.733, BIC = 1,063.856) and the highest value for the coefficient of determination (R=0.79). The highest values for information criteria were found for Djikstra’s model (MMSE = 636.6438, AIC = 1,076.621, AICc = 1,077.117, BIC = 1,086.582) having the same time the lowest value for the coefficient of determination (R=0.59). Overall, Wood (1967) model showed the best adjustment. Despite of being more recent, the model by Djikstra (1997) mechanist based and with a higher number of parameters showed a low convergence for the data used. Wood model (1967) has a greater advantage of producing a good fit measurement with only three parameters.
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