The Research of Prediction of Lean Yield with CSB Image-Meater and Pork Carcass Grading System
|School||Nanjing Agricultural College|
|Course||Of Food Science|
|Keywords||Image-Meater carcass Lean meat Forecast Grading standards|
With CSB-Image-Meater, prediction equation for lean yield of pork carcass in part of China and pork carcass grading system were studied in the paper. There are three main parts:(1) The verification of the choice of the choice of measurement spot; (2) The research of prediction equation of lean yield with CSB Image-Meater; (3) The research of pork carcass grading system.(1) Via correlation analysis of each characteristic of 436 carcasses from Zhengjiang, Hubei, Shangdong, Shanxi, Sichuan province, which are selected at random in a commercial abattoir, the result shows that carcass lean yield is most relevant in thinnest fat above the middle gluteal muscle (F), correlation coefficient is -0.9132 3 and correlation coefficient of vertical distance between the edge of middle gluteal muscle and spinal cord(R) is 0.584 80. Then putting F and R values into original equation of the device, analyzing the predicting value and actual value with statistical test, we got the result that t=0.241,P=0.233 6>0.05, it means there is no significant difference between predicting value and the actual value. From the above information we can see the choice of measurement spot (F and R) is credible and reasonable.(2) In order to predict lean yield of pork carcasses in China accurately, to achieve grading on line and higher price with better quality,436 carcasses were selected in this research, which were classed three types according to lean yield and somatotype. Actual lean yield, carcass weight without cooling, F and R were measured. The prediction equations were established by linear stepwise regression. The result shows:Carcass weight without cooling and measured lean yield were lower compared with other countries abroad. The prediction equations for different types were accurate, which meet the request of EEC(R>0.8, RSD<2.5%). And the extents of accuracy were higher than the prediction equation without considering different types, but difference was inconspicuous. Consequently, the prediction equation of lean yield without considering different types, sex and form (y=61.264-0.583 x1+0.173 x2. x1 is thinnest fat above the middle gluteal muscle, x2 is vertical distance between the edge of middle gluteal muscle and spinal cord, R2=0.87, RSD=2.31%)was the best prediction equation for CSB Image-Meater, it was because that the prediction equations for different types could not be applied in slaughter plants and classification by men would bring error, The result of validation showed that the difference between predicting lean yield and measured lean yield was not distinct, the accuracy of prediction equation was fine.(3) Carcass weight without cooling of 23342 and lean yield of 1224 were measured and distributing statistic was done. According to these two important data combined with the actual situation of production and consumer behavior in China, we can got a system of 8 grading or 9 grading of lean yield by multi-factor grading method or lean yield grading method. These two systems have each advantage and disadvantages and they can compensate each other really well.