动物营养学报2018，Vol.30Issue(5)：1748-1759,12.DOI:10.3969/j.issn.1006-267x.2018.05.017
化学计量学模型预测中国泌乳奶牛瘤胃挥发性脂肪酸组成的精度分析
Accuracy Analysis of Prediction of Ruminal Volatile Fatty Acid Profiles in Chinese Lactating Dairy Cows by Stoichiometry Models
摘要
Abstract
This study was conducted to evaluate the accuracy of models to predict ruminal volatile fatty acids (VFA)profiles in Chinese lactating dairy cows, and to analyze factors that affect the accuracy of the models. Three classical models of ruminal VFA stoichiometry were selected, which were MUR model, DIJ model and BAN model. The VFA data was selected from 18 articles of Chinese scientists,including 14 SCI articles,3 ar-ticles from Chinese Core Journals and 1 unpublished manuscript, and data included diet, body weight, dry matter intake,feed additives,VFA proportions. Mean squared prediction error(MSPE)and consistent correla-tion coefficient(CCC)methods were employed to evaluate the prediction accuracy of MUR model,DIJ model and BAN model. The results showed as follow:BAN model had the highest prediction accuracy of acetate pro-portion(R2=0.140; P=0.007, RMSPE=6.8%), with overall bias being 47.8%. Propionate, butyrate and other acids proportions could not be predicted by the above three models. In conclusion,BAN model has high-est prediction accuracy to predict acetate molar proportion among the three models,but the prediction accuracy is still low with the error mainly coming from the overall bias, and it is necessary to make use of more data to establish a VFA stoichiometry prediction model suitable for Chinese national conditions.关键词
挥发性脂肪酸/模型/预测误差均方/一致性相关系数/泌乳奶牛Key words
volatile fatty acid/model/prediction error mean square/consistency correlation coefficient/lac-tating dairy cow分类
农业科技引用本文复制引用
毛宏祥,任傲,王敏,高凤仙,张秀敏,马致远,谭支良..化学计量学模型预测中国泌乳奶牛瘤胃挥发性脂肪酸组成的精度分析[J].动物营养学报,2018,30(5):1748-1759,12.基金项目
国家自然科学基金项目(31561143009,31472133) （31561143009,31472133）
国家科技计划项目(2016YFD0500504) （2016YFD0500504）
现代农业(奶牛)产业技术体系建设专项资金(CARS-36) （奶牛）
中国科学院青年促进会项目(2016327) （2016327）
