Identification of Pork Meat Freshness Using Neural Networks

Pork meat freshness level is a vital factor in determining its quality for consumption. Sensory testing, physical and chemical testing, microbiological testing, and instrument analysis are all examples of traditional detection procedures. The goal of this work is to use image analysis and deep learning to classify pork meat quality. The datasets were provided, and it consists of extracted features from the photos of various pork meats. The parameters are then classified using Neural Network model and Keras Classifier. Pork meat quality can be categorized as fresh, half-fresh and adulterated. After testing and conducting a statistical analysis, the system achieved an overall accuracy of 87.93 %.