Model Development for the Prediction of Marbling Score of Brangus Beef Fattening Using Logistic Regression

The objective of this article is to develop a model for predicting marbling scores of Brangus beef fattening cattle breed using the Logistic Regression technique. Using 2014-2021 data (8 years) from cow fattening cattle of Kamphaeng Saen Beef Cooperative Ltd. with a total number of1,040 cattle. The data include breeder name, fattening period (months), age of cattle from shedding, tooth wear, live weight when processing, cold carcass weight, and Beef Marbling Score (BMS). Using the percentage split method to test the predictive model. By setting, the size of the training set to 10 to 90 percent with an incremental of 10. It found that the highest accuracy was 59.62%, and the RMSE was 0.34. Due to a lack of main factors such as feed and the season of the cows, enter the beef meat processing. The beef marbling score forecasted by the logistic regression technique can use as a guideline for predicting fat insertion scores, farm management, and selection of cattle breeders.