Grade prediction of meat quality in Korean Native cattle using neural network

This paper proposed a prediction method of meat quality grade from an ultrasound image of Korean native cattle using neural network. Systematic way of meat quality to prediction of grade in Korean native cattle is one of important technologies of total quality control. An improvement rate is increased by prediction of a meat quality and amount of meat without butchery. Shipping date and feeding schedule are able to control through prediction information on a farm. However, the hitherto subject for biometrics information has not been studied in domestic. So, it proposes prediction method of meat quality using neural network algorithms with the ultrasound image. Experiment results compared with real grades, and total prediction rate of the proposed method have been checked 83.33 percent.