Hydrogen Sulfide as a Green Postharvest Preservative: A Meta‐Analysis of Quality Maintenance, Stress Resistance Regulation, and Implications for Artificial Intelligence‑Assisted Chilling Injury Early Warning

ABSTRACT Postharvest losses of fruits and vegetables represent a global concern, as they are susceptible to spoilage and deterioration. In recent years, numerous studies have explored the effects of hydrogen sulfide (H 2 S) treatment on the postharvest preservation of fruits and vegetables. However, due to variations in experimental materials, treatment protocols, and detection parameters, no consensus has yet been reached regarding its efficacy. This study systematically analyzed the overall effects of H 2 S treatment on improving the quality of various fruits and vegetables and enhancing postharvest storability, while also elucidating the underlying mechanisms. A total of 54 articles were included, from which 43 parameters associated with postharvest quality and stress resistance were extracted in strict adherence to the predefined inclusion criteria. The results demonstrated that H 2 S treatment enhanced firmness, total chlorophyll (CC), titratable acid (TA), and ascorbic acid (AsA) in postharvest fruits and vegetables, while significantly reducing chilling injury (CI) incidence, weight loss, respiration rate, and ethylene production. Meanwhile, H 2 S preserved the structural integrity of cell walls and cell membranes, ensuring the stability of cellular energy metabolism. Additionally, H 2 S promoted the accumulation of endogenous H 2 S, non‐enzymatic antioxidants, and enzymatic antioxidants. Furthermore, significant correlations were found between CI and CC, TA, and AsA in postharvest fruits and vegetables. Multiple linear regression analysis also identified ascorbate peroxidase and phenylalanine ammonia‐lyase as key indicators for establishing a stable multivariate model with CI. In conclusion, this systematic review clarifies the efficacy of H 2 S in reducing postharvest loss and preserving produce freshness, and provides new insights for AI‐assisted early warning of CI in fruits and vegetables.