Optimisation of the controlled atmosphere storage and shelf life of Lilium longiflorum

Main Article Content

Peng Deng
Kailong Li
Wuyin Chen
Jianping Dai
Ang Chen
Lebin Yin

Keywords

Lilium longiflorum, comprehensive evaluation, back propagation neural network, genetic algorithm, controlled atmosphere storage

Abstract

To prolong the storage period of fresh Lilium longiflorum, maintain its quality during storage, and optimise the controlled atmosphere (CA) storage parameters. In a single-factor experiment, the temperature, humidity, and O2 and CO2 concentrations were considered as primary factors affecting the CA storage of L. longiflorum. Then, a comprehensive score was optimised using a back propagation neural network combined with empirical data. Finally, experimental verification was undertaken. The optimal concentrations of O2 and CO2 were 4.5% and 3.8%, respectively. A storage temperature of 4.2°C and a relative humidity of 90% were ideal. Under these conditions, the comprehensive evaluation score for L. longiflorum was 0.8424 (P > 0.05), consistent with the predicted value of 0.8372. Compared to ordinary cold storage, the storage period of L. longiflorum under these CA storage conditions was effectively prolonged. This provided an experimental basis for the CA storage of L. longiflorum.

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