Estimation of Pork Carcass Composition By On-Line Carcass Evaluation Parameters
碩士 === 國立宜蘭大學 === 動物科技學系碩士班 === 100 === To predict lean content of pork carcass accurately and objectively, relative measurements of carcass traits were used in multiple linear regression analysis for lean estimation. Two hundred and twenty-two LYD cross-bred hogs, with average live weight 112.1±13....
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2013
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| Online Access: | http://ndltd.ncl.edu.tw/handle/04933311917571538626 |
| Summary: | 碩士 === 國立宜蘭大學 === 動物科技學系碩士班 === 100 === To predict lean content of pork carcass accurately and objectively, relative measurements of carcass traits were used in multiple linear regression analysis for lean estimation. Two hundred and twenty-two LYD cross-bred hogs, with average live weight 112.1±13.4kg, were slaughtered and dissected in a commercial packing plant. Carcass length and backfat thickness were recorded on the slaughter line. Loin eye areas of the 10th and last ribs were recorded on cutting line. Carcasses were dissected into lean, fat and bone. The chilled carcass weight was significantly correlated with lean weight of hog carcass (r=0.705; P<0.001). The average backfat thickness was positively related to carcass lean weight (r=0.146; P<0.05) but negatively related to carcass lean weight percentage (r=-0.442; P<0.001). Regression analysis of the pig for lean estimation with carcass traits showed higher coefficient of determination (R2=0.564) and lower coefficient of variation (CV=10.786%) with an equation using chilled carcass weight and loin eye area and backfat thickness of last rib as estimator. Regression analysis of the barrow carcass lean weight estimation with carcass traits showed higher coefficient of determination (R2=0.598) and lower coefficient of variation (CV=10.920%) with an equation using carcass weight and loin eye area and backfat thickness of last rib as estimator. Regression analysis of the gilt carcass lean estimation with carcass traits showed higher coefficient of determination (R2=0.549) and lower coefficient of variation (CV=10.512%) with an equation using carcass weight and loin eye area and backfat thickness of last rib as variables.
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