Prediction of BCS number by using digital images of carcass cross sections obtained from high-resolution photographic equipment
2006
Takahashi, K.(Obihiro Univ. of Agriculture and Veterinary Medicine, Hokkaido (Japan)) | Hori, T. | Nami, M. | Honma, T. | Kotaka, H. | Kuchida, K.
The purpose of this study was to examine a new method of predicting the BCS number by using digital images of carcass cross-sections obtained from high-resolution photographic equipment. Six types of digital images (JPEG and TIFF images along the outline of the rib eye, and JPEG and TIFF images for the rectangular area of the rib eye, and those JPEG images adjusted with the variation of luminance) of the cross section were taken for 46 Japanese Black steers using the new equipment. Average values of R (Red), G (Green), B (Blue) and the luminance for the whole rib eye, the muscle and the marbling area (total of 108 variables) were calculated. A multiple regression analysis was performed by the REG procedure in SAS to predict the BCS number. BCS numbers evaluated by graders were used as a dependent variable, and traits obtained by the image analysis were used as independent variables which were limited to 5. Images with adjusted luminance and extracted along the outline of the rib eye had the highest determination coefficient (R(2)=0.783). Ninety five point seven percent of the BCS numbers evaluated by graders were correctly predicted using BCS numbers by the image analysis, suggesting that it is possible to predict BCS numbers with high accuracy.
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