A Comprehensive Review on Quality Prediction of Fruits and Vegetables using Feature Extraction and Machine Learning Techniques

The quality estimation of fruits and vegetables plays a vital role in the field of agriculture. This paper reviews the latest improvements in estimating the quality of fruits and vegetables as well as grading them using machine learning techniques. As fruits and vegetables have high nutritional value, their sales are on high demand. The prime importance is given to the supply of toxin-free, premium quality products to the end-users. Quality of a fruits and vegetables highly affected by detecting the defects on them. Keeping the spoiled foods along with good food may contaminate the whole collection. Features of interest are needed for proper identification of food product. After extracting and refining features of interest, the images can be trained to error free categorization. This paper presents an elaborated description of various feature extraction and machine learning techniques to identify and grade different kinds of fruits and vegetables. This research study has reviewed many articles to sort out the problems in estimating the quality and classifying them according to the need. The results of this review show that incorporating image processing and computer vision techniques with machine learning techniques surpasses the traditional methods.