Facility tomato picking system based on shelf life prediction and fruit maturity discrimination

Abstract

In order to ensure the best taste and maturity of the picked tomatoes during the market, this paper designed a facility tomato picking system based on shelf life prediction and fruit maturity discrimination. Use the deep learning method to predict the shelf life of tomatoes and distinguish the ripeness of tomato fruits, and calculate the best picking time of tomatoes through the shelf life and fruit ripeness. The use of this system avoids the uncertainty of empirical judgment of picking time, improves economic benefits, and is of great significance to the development of intelligent fruit and vegetable picking.