Supervised Machine Learning Approach for Pork Meat Freshness Identification.

Lumogdang CF, Wata MG, Loyola SS, et al. Supervised Machine Learning Approach for Pork Meat Freshness Identification. ICBRA '19: Proceedings of the 6th International Conference on Bioinformatics Research and Applications. 2020;1-6. https://doi.org/10.1145/3383783.3383784.

This study developed a machine learning system to classify pork meat freshness using image processing and gas sensors. Data were collected from pork loin samples inspected by a city veterinarian, with images taken and electronic sensors measuring ammonia and hydrogen sulfide levels. The k-Nearest Neighbor (k-NN) algorithm classified the meat as fresh, half-fresh, or adulterated. The system achieved a high accuracy rate of 93.33% based on functionality testing and statistical analysis using a confusion matrix.