Application of Machine Learning in Fruit and Vegetable Quality Inspection and Control
Machine Learning(ML)has shown its superiority and great potential in the field of food quality control and prediction,and is increasingly applied in the fruit and vegetable processing industry to improve the scientificity and simplicity of fruit and vegetable quality management,evaluation,and prediction.This article summarizes the basic principles and categories of ML,and lists common ML methods including K-nearest neighbor clustering algorithm,support vector machine,random forest,and convolutional neural network.It discusses the application of ML in fruit and vegetable structural damage detection,quality control,variety classification,and safety inspection,aiming to provide a reference for the application of ML in the field of fruit and vegetable quality detection and management.
machine learningfruit and vegetable testingquality managementquality and safetyvariety classification
NETL
NSTL
万方数据
