Biometric identification provides an important tool for precision livestock farming. This study investigates the effect of weight gain and sheep maturation on recognition performance. Sheep facial identification was implemented using two convolutional neural network (CNN) called Faster R-CNN, and ResNet50V2, equipped with the state-of-art Additive Angular Margin (ArcFace) loss function. The identification model was tested on 47 young sheep at different stages, during a 3-month growth period, when they were between 2 and 5 months old, throughout which the sheep gained approximately 30 kilograms in weight. Results revealed that when the model was trained and tested on images of sheep aged 2 months, the average accuracy of the group was 95.4%, compared with 91.3% when trained on images of sheep aged 2 months but tested on images of sheep aged 5 months.
