Computer Assisted Rapid Non-Destructive Method For Evaluation Of Meat Freshness

In this study a technique was developed to predict the meat freshness decay by employing a nondestructive visible imaging method and a computer assisted analysis. The technique uses Opto-magnetic imaging spectroscopy and machine learning algorithms for detecting of freshness during storage. The opto-magnetic spectra of meat samples were acquired at 0, 12 and 24 hours of refrigerated storage using specially developed imaging system and computer image processing algorithm. The obtained spectra were related to the storage time of the samples, and several machine learning classification algorithms were tested. The best prediction results of freshness for chicken and beef was achieved using lazy IB1 classifier with the accuracy of 97.47% for chicken, and 98.23% for beef. Since the method is concerned with detecting changes in the state of water in tissues, the freshness decay period was estimated based on changes in meat hydration properties.