Tuesday, 7 March 2017

Keys to Selecting a Prediction Model for Carcass Composition from Computed Tomography Images

Linear, nonlinear and volume measurements obtained from computed tomography (CT) images of live pigs are good predictors of carcass characteristics there are different ways to analyse the goodness of a prediction equation, including the decomposition of the predicted error and the biases and coefficient of determination. 

tomography journal
The present paper compares the goodness of fit of individual prediction equations within three different geno types and the prediction obtained by a global equation for the different geno types at the same time comparison is performed by means of the error decomposition, the standard deviation of the bias and the coefficient of model determination The results showed a good mean square prediction error and a high error due to disturbances (random effects) for most of the predictions