An Enhanced Framework for Categorization of Fruits Based on Ripeness using Ensemble PSO Model

Ripeness-based categorization is a vital function after the harvest of fruits to balance ripening treatment. Ripeness level significant factor determining quality and lifetime fruits. Various attributes are used identify ripeness level, which manual method categorizing based on skin colour predominantly used. This prone error at many times. paper implements an Ensemble Particle Swarm Optimization (EnPSO) algorithm categorize level. The comparison reveals that proposed EnPSO outperforms state-of-the-art algorithms for same problem. Categorization done using decision tree, provides up 98% classification accuracy.