A Comparative Study on Predicting Food Quality using Machine Learning Techniques

Machine Learning has been established to be a state of the art technology with a high number of successful cases in various research areas. These techniques have been applied widely on food quality evaluation in recent years. This paper reviews the recent developments in the field of estimating food quality and food safety using machine learning techniques. The primary focus is on the supply of defect-free, premium quality products to the consumers which is considered to be major factor for the competitiveness of manufacturing units. This paper provides a brief description of machine learning techniques and then a detailed comparative study of different techniques to grade different kinds of foods. We investigated many articles to resolve the problems in food domain which includes detecting the quality of fruits, vegetables, seafood, meat and dairy products. The results of this survey shows that machine learning techniques outperforms the conventional methods used in the food domain.