刊名:Chemometrics and Intelligent Laboratory Systems
出版年:2009
出版时间:15 August 2009
年:2009
卷:98
期:1
页码:31-37
全文大小:512 K
文摘
Lean meat percentage (LMP) is an important carcass quality parameter. The aim of this work is to obtain a calibration equation for the Computed Tomography (CT) scans with the Partial Least Square Regression (PLS) technique in order to predict the LMP of the carcass and the different cuts and to study and compare two different methodologies of the selection of the variables (Variable Importance for Projection — VIP- and Stepwise) to be included in the prediction equation. The error of prediction with cross-validation (RMSEPCV) of the LMP obtained with PLS and selection based on VIP value was 0.82 % and for stepwise selection it was 0.83 % . The prediction of the LMP scanning only the ham had a RMSEPCV of 0.97 % and if the ham and the loin were scanned the RMSEPCV was 0.90 % . Results indicate that for CT data both VIP and stepwise selection are good methods. Moreover the scanning of only the ham allowed us to obtain a good prediction of the LMP of the whole carcass.