Trouw Nutrition Research and Development, PO Box 299, 3800 AG, Amersfoort, the Netherlands.
Trouw Nutrition Research and Development, PO Box 299, 3800 AG, Amersfoort, the Netherlands.
J Dairy Sci. 2020 Dec;103(12):11268-11284. doi: 10.3168/jds.2020-18286. Epub 2020 Oct 1.
Net energy and protein systems (hereafter called feed evaluation systems) offer the possibility to formulate rations by matching feed values (e.g., net energy and metabolizable protein) with animal requirements. The accuracy and precision of this approach relies heavily on the quantification of various animal digestive and metabolic responses to dietary changes. Therefore, the aims of the current study were, first, to evaluate the predicted responses to dietary changes of total-tract digestibility (including organic matter, crude protein, and neutral detergent fiber) and nitrogen (N) flows at the duodenum (including microbial N and undigested feed N together with endogenous N) against measurements from published studies by 2 different feed evaluation systems. These feed evaluation systems were the recently updated Institut National de la Recherche Agronomique (INRA, 2018) and the older, yet widely used, National Research Council (NRC, 2001) system. The second objective was to estimate the accuracy and precision of predicting milk yield responses based on values of net energy (NE) and metabolizable protein (MP) supply predicted by the 2 feed evaluation systems. For this, published studies, with experimentally induced changes in either NE or MP content, were used to calibrate the relationship of NE and MP supply, with milk component yields. Based on the slope, root mean square prediction error, and concordance correlation coefficient (CCC), the results obtained show that total nonammonia nitrogen flow at the duodenum was predicted with similar accuracy and precision, but considerably better prediction was achieved when the INRA model was used to predict organic matter and neutral detergent fiber digestibility responses. The average NE and MP content predicted by both models was similar, but NE and MP content of individual diets differed substantially between both models as indicated by determination coefficients of 0.45 (NE content) and 0.50 (MP content). Despite these differences, this work shows that when response equations are calibrated with NE and MP values either from the INRA model or from the NRC model, the accuracy and precision (slope, root mean square prediction error, and CCC) of the predicted milk component yields responses is similar between the models. The lowest accuracy and precision were observed for milk fat yield response, with CCC values in the range of 0.37 to 0.40, compared with milk lactose and protein yields responses for which CCC values were in the range of 0.75 to 0.81.
净能和蛋白质体系（以下简称饲料评估体系）提供了一种通过匹配饲料值（如净能和可代谢蛋白）与动物需求来制定日粮的可能性。这种方法的准确性和精密度在很大程度上依赖于对动物对日粮变化的各种消化和代谢反应的量化。因此，本研究的目的首先是评估两个不同饲料评估系统对总肠道消化率（包括有机物、粗蛋白和中性洗涤纤维）和十二指肠氮（包括微生物氮和未消化饲料氮以及内源性氮）变化的预测反应，以对比来自已发表研究的测量结果。这两个饲料评估系统是最近更新的法国国家农业研究院（INRA，2018 年）和较旧但广泛使用的美国国家研究委员会（NRC，2001 年）系统。第二个目标是估计基于净能（NE）和可代谢蛋白（MP）供应预测值预测产奶量反应的准确性和精密度，这两个饲料评估系统进行预测。为此，使用了实验性改变 NE 或 MP 含量的已发表研究，以校准 NE 和 MP 供应与乳成分产量之间的关系。基于斜率、均方根预测误差和一致性相关系数（CCC），结果表明，十二指肠非氨氮流量的预测具有相似的准确性和精密度，但使用 INRA 模型预测有机物和中性洗涤纤维消化率反应时，预测效果要好得多。两个模型预测的平均 NE 和 MP 含量相似，但两个模型之间的个别日粮的 NE 和 MP 含量差异很大，决定系数分别为 0.45（NE 含量）和 0.50（MP 含量）。尽管存在这些差异，但这项工作表明，当用 INRA 模型或 NRC 模型的 NE 和 MP 值校准响应方程时，两种模型预测的乳成分产量响应的准确性和精密度（斜率、均方根预测误差和 CCC）相似。对于乳脂产量响应，观察到最低的准确性和精密度，CCC 值在 0.37 到 0.40 之间，而对于乳乳糖和蛋白质产量响应，CCC 值在 0.75 到 0.81 之间。
