1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China；
2. Beijing Laboratory of Food Quality and Safety, Beijing 100083, China
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.
2013, Vol. 27 
