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Evaluation of National Research Council 2001 and Cornell Pennsylvania Miner softwares for predicting dry matter intake of Holstein cows during the midlactation
Published online by Cambridge University Press: 23 November 2017
Extract
Predicting dry matter intake (DMI), precisely and accurately is important to prepare balanced rations when on farm estimates of feed intake are not available (Hayirli et al., 2003). Lack of accuracy in prediction of feed intake may result in nutrient underfeeding or overfeeding affecting to animal performance, animal health or dairy farm environmental impact (NRC2001). The 2001 “Nutrient Requirements of Dairy Cattle” recommended a DMI prediction equation based on animal factors that were evaluated with treatment means from experiments published in the Journal of Dairy Science between 1988 and 1998 (NRC2001). The variables used to evaluate DMI prediction are mean square prediction error (MSPE) and relative prediction error (RPE). MSPE accounted as 1/N (A-P)2 that N is number of comparisons, A is actual DMI monitored in farm, and P is predicted DMI in each software. The objective of this investigation was to evaluate the accuracy of National Research Council 2001 and Cornell Pennsylvania Miner softwares in predicting DMI of lactating dairy cows in midlactation.
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- Copyright © The American Society of International Law 2016