Fig. 10

A A two-dimensional Partial Least Square-Discriminant Analysis (PLS-DA) score plot was constructed using three classes of resilience (lower (L) in yellow, medium (M) in light blue as the control group, and higher (H) in grey). The plot represents the distribution of the samples based on the first two components in the model. Each point’s shape changes according to the breed to which the animal belongs. PLS-DA was performed for the four indicators that are lag of 1 day of residual (Lag1), natural logarithm of residual variance (LnVar), area under the curve for periods with the largest consecutive negative errors (MaxArea), and sum of residual’s local minima (SumMin). B Receiver operating characteristic (ROC) analysis was performed to discriminate between the three classes of resilience mentioned above (L,M,H) for the four indicator of resilience mentioned above (Lag1, LnVar, MaxArea, and SumMin). C Confusion matrix depicting the performance of Lag1, LnVar, MaxArea, and SumMin in predicting the resilience classes (L,M,H). The x-axis represents the categories of true values, while the y-axis represents the categories of predicted values