畜牧兽医学报2012，Vol.43Issue(3)：368-375,8.
3种不同方法对肉牛胴体性状预测能力的比较研究
Comparison of Three Methods to Predict Carcass Traits in Bovine
摘要
Abstract
To search for a method to predict accurately carcass traits in bovine, in this study, DPS and SAS software were used to compare the methods of partial least squares regression, GM(1, N) gray system and BP neural network, in order to observe their accuracy in predicting carcass traits in bovine. Seven preslaughter growth traits including body height, body length, chest circumference, abdominal circumference, cannon bone circumference, live weight and average daily gain were used to predict the carcass weight and meat weight. The results showed that the partial least squares regression gave the highest accuracy, while the average relative errors of GM(1,N) gray system and BP neural network were lower. In this study, the three predicted results were combined and their mean value were calculated as the predictive values, which would greatlyimprove the accuracy of prediction. The results would provide some scientific references to beefproduction.关键词
偏最小二乘回归/GM(1,N)灰色系统/BP神经网络/预测/胴体性状Key words
PLSR/ GM(1,N) gray system/ BP neural network/ prediction/ carcass traits分类
农业科技引用本文复制引用
张立敏,高会江,许尚忠,李俊雅,张猛,周正奎,刘喜冬,陈翠,陈晓杰,李姣,袁峥嵘,高雪..3种不同方法对肉牛胴体性状预测能力的比较研究[J].畜牧兽医学报,2012,43(3):368-375,8.基金项目
农业部专项(Nycytx-38) （Nycytx-38）
国家自然基金(30871774) （30871774）
转基因生物新品种培育重大专项(2009ZX08007-005B) （2009ZX08007-005B）
“十一五”转基因重大专项(2008ZX08007-2) （2008ZX08007-2）
“十二五”科技支撑计划课题(2011BAD28B04) （2011BAD28B04）
中国农业科学院基本科研业务费专项资金课题(2010jC-2) （2010jC-2）
