Andy Mauromoustakos, Professor, University of Arkansas
Shawna L. Weimer, Assistant Professor, University of Arkansas
Stress and lameness negatively affect animals' health, production, and welfare. The following physiological and non-invasive measures of stress and lameness were measured: relative bursa weight, core body temperature, corticosterone (CORT) concentrations in serum and feathers, surface temperatures of the head (eye and beak) and legs (hock, shank, and foot) regions by infrared thermography (IRT), leg blood and oxygen saturation. The JMP Pro 17 Model Screening platform was used to fit several parametric and machine learning models to the binary response variable (Lame=1) of the 258 study birds on the nine health and stress indicators mentioned above. We selected K Fold Cross-validation with K=5 and repeated the process twice (N Trials Folds=10). The best two models were the Neural Boosted (Mean AUC=.985 and misclassification rate of zero in 50 validation birds) and the Generalized Regression Lasso (Mean AUC=.975 and misclassification rate of 1 in 50 validation birds). Both models agreed on predictor effects when using Model Comparison of JMP Pro to compare them further and are found nonsignificant in comparing their AUC.
