Partial scanning using computed tomography for fat weight prediction in green hams: Scanning protocols and modelling

Prediction of primal cuts by using an automatic ultrasonic device as a new method for estimating a pig-carcass slaughter and commercial value

The objective of the present work was to develop regression equations to estimate the percentage, weight (in g) and lean meat content (in %) of the primal cuts of a pig carcass by using Auto-Fom and to estimate the commercial value of the carcass on the slaughter line in a meat-processing plant. The research was conducted on 168 pig carcasses. From the whole pork carcass, only the most valuable cuts (i.e. belly, ham, loin, neck and shoulder) and also meat content in ham and shoulder were weighed at a 100 g accuracy and the percentage of each cut in carcass was calculated. Loin ‘eye’ height and belly-muscle thickness were also measured. The regression equations for the prediction of the primal-cut weights and their percentages in the pig carcasses were derived using the partial least-square procedure. The developed equations include 70 variables that are standard measurements taken with an Auto-Fom device. These equations have a satisfactory accuracy rate and are useful in estimating the yield of the elements, especially for loin, ham and belly content. Belly-muscle thickness (R2 = 0.98) and the percentage of meat in the ham (R2 = 0.93) can be estimated with a high precision. It was confirmed that the developed equations may be used in the current Auto-Fom software.