Application of artificial intelligence methods for bovine gender prediction

Authors : Ali ÖZTÜRK, Novruz ALLAHVERDI, Fatih SADAY

Pages : 54-62

Doi:10.31127/tuje.807019

View : 14 | Download : 11

Publication Date : 2022-01-30

Article Type : Research Paper

Abstract :This study investigates determining the gender of calves using some artificial intelligence insert ignore into journalissuearticles values(AI); techniques. Gender identification is important in animal breeding, focusing on the desired outcome and planning. The data used to determine the gender of calves were the speed, magnitude, and density of the bull`s semen. The analysis of the related studies showed that there was not a study on gender prediction of bovine with the application of AI methods. In this study, fuzzy logic insert ignore into journalissuearticles values(FL);, artificial neural networks insert ignore into journalissuearticles values(ANN);, support vector machines insert ignore into journalissuearticles values(SVM);, and random forests insert ignore into journalissuearticles values(RF); were used. The efficiency of these approaches was verified by statistical analysis parameters such as accuracy, specificity, sensitivity insert ignore into journalissuearticles values(recall);, precision, and F-score. The FL, ANN, SVM, and RF models had 84%, 96%, 97%, 99% accuracy, 93.75%, 96.88%, 100%, 100% sensitivity, 66.66%, 94.44%, 92.31%, 97.30% specificity, 83.33%, 96.88%, 95.31%, 98.44% precision results, respectively. Application of these AI techniques for prediction bovine gender proves that these methods may be used by semen breeders as supporting information tools. In particular, it was observed that the RF method yielded the highest accuracy results.   
Keywords : Bovine gender prediction, Fuzzy logic, Artificial neural networks, Support vector machines, Random forests