Journal of Northern Agriculture ›› 2023, Vol. 51 ›› Issue (5): 103-113.doi: 10.12190/j.issn.2096-1197.2023.05.11

• Agricultural information technology • Previous Articles     Next Articles

Construction and optimization of BP neural network mango maturity discrimination model based on genetic algorithm

FANG Xinru, XING Jingxuan, Suolangcuo , JIANG Yiping   

  1. Nanjing Agricultural University,Nanjing 210000,China
  • Received:2023-08-29 Online:2023-10-20 Published:2024-01-04

Abstract:

【Objective】To construct and optimize BP neural network mango maturity discrimination model based on genetic algorithm.【Methods】Using Xiaotai Mango as the experimental material,the firmness and sugar content of mangoes with different maturity levels were measured,and RGB images captured. The correlation between mango maturity and mango firmness,sugar content,and image feature variables(RGBHSV components) were analyzed. BP neural network mango maturity discrimination model was constructed and optimized using optimal network weights and thresholds obtained by genetic algorithm.【Results】With the increase of mango maturity,sugar content showed clear increasing trend,while firmness showed decreasing trend. Image feature variables (RGBHS components) had significant differences (P<0.05) at different maturity stages. The BP neural network mango maturity discrimination model optimized by genetic algorithm had an classification accuracy of 96.3%.【Conclusion】The BP neural network mango maturity discrimination model optimized by genetic algorithm could accurately identify mangoes with different maturity levels.

Key words: Mango, Maturity, Genetic algorithm, BP neural network, Discrimination model

CLC Number: 

  • TP391.41