Using Machine Learning Approaches for Food Quality Detection

Food quality detection is an important method for ensuring food safety. Efficient methods can improve the efficiency of circulation and reduce storage labor costs. Traditional use instrumentation, testing reagents, or manual labor. These take a long time to detect, are time-consuming labor-intensive, require professionals operate. Fruit, as high-value that provides essential nutrition human beings, susceptible spoilage during packaging, transportation, sales, so freshness safety assurance fruit hot difficult area current research. Therefore, freshness, this paper proposes efficient nondestructive way detect by using machine learning algorithm convolutional neural network (CNN). This shows networks have good performance in identifying fruits through extensive experimental results discusses overfitting based on results.