肉类研究Issue(2)：1-4,4.
北京地区三元杂交猪胴体的分级优化
Optimization of Carcass Grading of Sanyuan Crossbred Pigs in Beijing
摘要
Abstract
To increase the accuracy of pig carcass grading, computer vision technology, image processing technology and statistical methods were used to modify the established pig carcass grading standard and prediction equations. An absolute error smaller than 4%was obtained from lean percentage predications based on half carcass weight, gluteus medium length and gluteus medium fat thickness. The accuracy of carcass grading obtained using lean meat percentage, gluteus medium fat thickness, mid-body fat thickness and rib 6—7 fat thickness as evaluation parameters was 90%. In conclusion, more reasonable and more accurate carcass grading can be achieved when using fat thickness in different carcass parts and lean percentage as evaluation parameters and making practical modifications to the carcass grades.关键词
猪胴体/计算机视觉/分级标准/瘦肉率/膘厚Key words
pig carcass/computer vision/grading standard/lean meat percentage/fat thickness分类
轻工纺织引用本文复制引用
张丽萍,郑丽敏,任发政,朱虹,田立军,刘银..北京地区三元杂交猪胴体的分级优化[J].肉类研究,2013,(2):1-4,4.基金项目
“十二五”国家科技支撑计划项目(2012BAK17B09 （）
2012BAD28B02) （）
国家生猪产业体系北京市创新团队项目 （）
