Postharvest preservation efficacy and optimization strategies of fresh cut flowers: a meta-analysis and machine learning approach

Abstract

Cut flowers are favored globally for their ornamental value, but their commercial value is limited by their short vase life, which depends closely on the postharvest preservation technology of cut flowers. Currently, complex types of preservatives and a variety of preservation methods have been used, but there is a lack of summary and comparison of them. In this study, 45 publications were synthesized and analyzed through meta-analysis and machine learning. The meta-analysis results showed that: (i) pulse treatments demonstrated superior vase life extension over conventional vase solution treatments by acutely enhancing antioxidant enzyme activity and suppressing ethylene biosynthesis, but their transient nature necessitated subsequent vase solution treatment maintenance for optimal floral appearance. (ii) As unique preservatives, nanomaterials had advantages in water balance and antimicrobial protection, which required synergistic integration with other preservatives to further enhance antioxidant capacity and supply nutrient. (iii) Plant species specificity needed to be taken into account when choosing the preservative types for vase solution treatment. The model prediction results of machine learning revealed that identical preservatives exhibited distinct differences when applied as pulse treatments versus vase solution treatments, indicating pulse treatment could amplify the preservation effect of preservatives. Based on the above results, an optimized implementation protocol was proposed: initial pulse treatment with nanomaterials, then species-specific preservatives addressed as supplement vase solutions treatment. Our verification experiments further validated that the optimized preservation protocol was effective in cut roses (Rosa hybrida L. cv. Carola). The findings provided mechanistic guidance for optimizing preservative combinations, and a theoretical foundation and direction for future research.

Acknowledgements

This project was supported by the National Natural Science Foundation of China (grant No. 31901184) and Doctor Foundation of Tianjin Normal University (grant No. 52XB1914). The authors wish to express their appreciation to the reviewers for their comments and suggestions.

Data availability

All the data underlying this article are available within the article and its online supplementary material.

Conflict of interest statement

The authors declare no conflict of interest.

Supplementary data

Supplementary data is available at Horticulture Research online.

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