外文摘要：The quality prediction of winter jujube during storage is crucial to improve its postharvest value. Postharvest winter jujube was treated with 1 mu L L-1 1-MCP and 5 mu L L-1 O3 respectively. 22 physiological and biochemical indexes were determined at different storage periods, and comprehensive quality measurements were obtained after the data were combined and weighted. Correlation analysis showed that total flavonoids, b* value, c* value, total phenolics, healthy fruit rate had the highest correlation coefficient with the comprehensive quality evaluation value of winter jujube. Single BP and optimized BP (GA-BP and PSO-BP) neural networks of 3 treatments were used to predict the storage quality of winter jujube. The results showed that PSO-BP had the highest prediction accuracy and the overall fitting rate was above 95 %, indicating that the established PSO-BP model could effectively predict the storage quality of winter jujube after harvest.
外文关键词：BP neural network;Winter jujube;1-MCP;Quality prediction;particle swarm optimization (PSO);O3
作者：Zhang, Jingyi;Chen, Cunkun;Wu, Caie;Kou, Xiaohong;Xue, Zhaohui
作者单位：Minist Agr & Rural Affairs;Nanjing Forestry Univ;Tianjin Univ
期刊名称：SCIENTIA HORTICULTURAE
期刊影响因子：0.0
出版年份：2024
出版刊次：331
原文传递申请：江苏省科技资源（工程技术文献）统筹服务平台