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Lactation curves of different cattle breeds under cooperative dairying conditions in Bangladesh

机译:孟加拉国合作乳业条件下不同牛品种的泌乳曲线

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This study was undertaken to compare and evaluate the parameters of 10 different mathematical models for their predictive ability in describing the lactation curves for daily milk yield of different genotypes under cooperative dairying in Bangladesh. A database consisting of 7340 herd-test records from 738 cows over the period 1999?¢????2001 was assembled. Breed combinations included Pabna cattle, Australian-Friesian-Sahiwal????Pabna, Holstein????Pabna, Jersey????Pabna and Sahiwal????Pabna. The estimated parameters of the mathematical models, and the predicted lactation milk yields differed significantly between genotypes. The models were evaluated by four fit statistics: Akaike information criteria, coefficient of determination ( R 2 ), root mean square prediction error (RMSPE) and concordance correlation coefficient (CCC). The AIC values indicated that the Ali model provided a good fit for all genotypes. The R 2 value suggested that the Legendre polynomial and Ali models were the best fit for all genotypes. CCC and RMSPE values indicated that the best models for all genotypes were Nelder and Wood. Since the CCC value was considered the most informative of the four fit statistics, the Nelder model was the best model to predict the full lactation profile based on test-day records for all genotypes. Using the Nelder model, the predicted 270 day milk yield of the Australian-Friesian-Sahiwal????Pabna genotype was higher (1823 kg) than the other genotypes (1509, 1650, 1531 and 1627 kg for Pabna, Australian-Friesian?¢????Sahiwhal????Pabna, Jersey????Pabna and Sahiwal????Pabna, respectively).
机译:进行这项研究是为了比较和评估10种不同数学模型的参数,以预测其在孟加拉国合作奶业下描述不同基因型日产奶量的泌乳曲线的预测能力。收集了一个数据库,该数据库包含1999年至2001年期间来自738头母牛的7340个牛群测试记录。品种组合包括Pabna牛,Australian-Friesian-Sahiwal,Pabna,Holstein,Pabna,Jersey,Pabna和Sahiwal,Pabna。数学模型的估计参数和预测的泌乳乳量在基因型之间存在显着差异。通过四个拟合统计量评估模型:Akaike信息准则,确定系数(R 2),均方根预测误差(RMSPE)和一致性相关系数(CCC)。 AIC值表明Ali模型为所有基因型提供了良好的拟合。 R 2值表明,Legendre多项式和Ali模型最适合所有基因型。 CCC和RMSPE值表明,所有基因型的最佳模型是Nelder和Wood。由于CCC值被认为是四个拟合统计量中最能提供信息的,因此Nelder模型是根据所有基因型的试验日记录预测全泌乳曲线的最佳模型。使用Nelder模型,澳大利亚-弗里斯兰-萨希瓦尔州的Pabna基因型的预测的270天奶产量比1896kg的其他基因型(1509、1650、1531和1627kg)高。 Sahiwhal,Pabna,泽西岛,Pabna和Sahiwal,Pabna)。

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