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基于牧场的奶牛日粮中康奈尔净碳水化合物和蛋白质体系的评估与应用

Evaluation and application of the Cornell Net Carbohydrate and Protein System for dairy cows fed diets based on pasture.

作者信息

Kolver E S, Muller L D, Barry M C, Penno J W

机构信息

Department of Dairy and Animal Science, Pennsylvania State University, University Park 16802, USA.

出版信息

J Dairy Sci. 1998 Jul;81(7):2029-39. doi: 10.3168/jds.S0022-0302(98)75777-7.

Abstract

This study evaluated the Cornell Net Carbohydrate and Protein System for dairy cows consuming diets based on pasture, assessed the sensitivity of the model to critical inputs, and demonstrated application opportunities. Data were obtained from four grazing experiments and four indoor pasture feeding experiments (25 dietary treatments) involving dairy cows in New Zealand and the US. The model provided a reasonably good estimate of changes in body condition score (r2 = 0.78; slope not significantly different from 1), estimated energy balance (r2 = 0.76; slope not significantly different from 1), blood urea N (r2 = 0.94; underprediction bias of 0.5%), microbial N flow (r2 = 0.88; slope not significantly different from 1), and milk production. The model underpredicted dry matter intake (r2 = 0.80; 13% bias) and overpredicted ruminal pH (r2 = 0.47; 1.7% bias). Predicted milk production was especially sensitive to changes in pasture lignin content, effective fiber, rate of fiber digestion, and amino acid composition of ruminal microbes. Milk production was first-limited by the supply of metabolizable energy when only high quality pasture was fed, but specific amino acids limited milk production when more than 20% of the diet consisted of a grain supplement. These results indicate that the Cornell Net Carbohydrate and Protein System can be used for dairy cows in a grazing system to make realistic predictions of performance.

摘要

本研究评估了康奈尔净碳水化合物与蛋白质系统在以牧场为基础日粮的奶牛中的应用情况,评估了该模型对关键输入参数的敏感性,并展示了其应用机会。数据来自新西兰和美国的四项放牧试验以及四项室内牧场饲养试验(25种日粮处理),涉及奶牛。该模型对体况评分的变化提供了较为合理的估计(r2 = 0.78;斜率与1无显著差异),对能量平衡的估计(r2 = 0.76;斜率与1无显著差异)、血尿素氮(r2 = 0.94;预测偏差为0.5%)、微生物氮流量(r2 = 0.88;斜率与1无显著差异)以及产奶量均有较好表现。该模型对干物质采食量预测偏低(r2 = 0.80;偏差为13%),对瘤胃pH预测偏高(r2 = 0.47;偏差为1.7%)。预测的产奶量对牧场木质素含量、有效纤维、纤维消化率以及瘤胃微生物氨基酸组成的变化尤为敏感。仅饲喂优质牧草时,产奶量首先受代谢能供应的限制,但当日粮中超过20%由谷物补充料组成时,特定氨基酸会限制产奶量。这些结果表明,康奈尔净碳水化合物与蛋白质系统可用于放牧系统中的奶牛,以对其生产性能做出实际预测。

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