动物营养学报 >

2018 , Vol. 30 >Issue 5: 1748 - 1759

DOI: https://doi.org/10.3969/j.issn.1006-267x.2018.05.017

反刍动物营养 Ruminant nutrition

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

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  • 1. 中国科学院亚热带农业生态研究所, 长沙 410125;
    2. 湖南农业大学动物科学技术学院, 长沙 410128;
    3. 湖南畜禽安全生产协同创新中心, 长沙 410128
毛宏祥(1991-),男,湖北襄阳人,硕士研究生,从事反刍家畜营养研究。E-mail:HongXiangmao@126.com

收稿日期: 2017-11-01

  网络出版日期: 2018-05-06

基金资助

国家自然科学基金项目（31561143009，31472133）；国家科技计划项目（2016YFD0500504）；现代农业（奶牛）产业技术体系建设专项资金（CARS-36）；中国科学院青年促进会项目（2016327）

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Accuracy Analysis of Prediction of Ruminal Volatile Fatty Acid Profiles in Chinese Lactating Dairy Cows by Stoichiometry Models

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  • 1. Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China;
    2. College of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China;
    3. Hunan Collaborative Innovation Center of Animal Production Safety, Changsha 410128, China

Received date: 2017-11-01

  Online published: 2018-05-06

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摘要

本研究旨在评估化学计量学模型预测中国泌乳奶牛瘤胃挥发性脂肪酸（VFA）组成的精度，分析影响模型预测精度的原因。本研究选择了3个经典的奶牛瘤胃VFA模型，分别为MUR模型、DIJ模型和BAN模型。试验数据来自我国主要科研团队的18篇论文，包括14篇SCI、3篇中文核心期刊和1篇未见刊的英文文章，论文数据含动物饲粮、体重、干物质采食量、饲料添加剂、VFA各组分比例。采用预测误差均方（MSPE）和一致性相关系数（CCC）2种分析方法对3个经典的奶牛瘤胃VFA模型的估算精度进行评估分析。结果表明：BAN模型乙酸比例估算精度最高（决定系数=0.140，P=0.007），预测误差均方根为6.8%，误差主要来自整体偏差的偏离（47.8%）。3个模型无法预测丙酸、丁酸、其他酸比例。总之，BAN模型预测乙酸比例的精度是3个模型中最高的，但预测精度仍然偏低，误差来源于整体偏差的偏离，迫切需要利用更多数据建立适合我国国情的VFA化学计量学预测模型。

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

本文引用格式

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 . DOI: 10.3969/j.issn.1006-267x.2018.05.017

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selected from 18 articles of Chinese scientists, including 14 SCI articles, 3 articles from Chinese Core Journals and 1 unpublished manuscript, and data included diet, body weight, dry matter intake, feed additives, VFA proportions.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 correlation 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 proportion (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 highest 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.

Key words： volatile fatty acid; model; prediction error mean square; consistency correlation coefficient; lactating dairy cow

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