Nondestructive evaluation of yellowing and senescence in 'Yali' pear using integrated hyperspectral and chlorophyll fluorescence imaging

文献类型： 外文期刊

第一作者： Cheng, Hong

作者： Cheng, Hong;Zhang, Zishen;Feng, Yunxiao;He, Jingang;Wang, Jinxiao;Cheng, Yudou;Guan, Junfeng;Cheng, Hong;Zhang, Zishen;Feng, Yunxiao;He, Jingang;Wang, Jinxiao;Cheng, Yudou;Guan, Junfeng;Zhang, Zishen

作者机构：

关键词： Chlorophyll fluorescence imaging; Hyperspectral imaging; Chlorophyll fluorescence parameters; Yellowing and senescence; Non-destructive determination; 'Yali' pear

期刊名称：FOOD RESEARCH INTERNATIONAL （ 影响因子：8.0； 五年影响因子：8.5 ）

ISSN： 0963-9969

年卷期： 2025 年 209 卷

页码：

收录情况： SCI

摘要： Monitoring the yellowing and senescence of postharvest 'Yali' pear is crucial for quality control during storage. This study integrated chlorophyll fluorescence imaging (CFI) and hyperspectral imaging (HSI) to assess the natural senescence of green 'Yali' pear transitioning from green to yellow under different storage conditions. Results demonstrated that common physicochemical parameters, such as firmness and soluble solids content (SSC), exhibited minimal changes throughout storage. Titratable acidity (TA) content showed slight variations under ambient storage conditions but declined significantly after 105 days of cold storage, stabilizing thereafter. Consequently, these parameters proved ineffective in predicting fruit senescence due to their limited changes over storage time. However, changes in the pear peel color (green to yellow) and chlorophyll degradation (evidenced by decreasing IAD values) effectively reflected the senescence process. Additionally, increased respiration and ethylene production rates further indicated advancing senescence. Among the chlorophyll fluorescence (ChlF) parameters, Fm and Fv/Fm showed a significant decline, correlating strongly with various physicochemical changes, including a*, h0, IAD, as well as respiration and ethylene production rates, thus proving to be reliable indicators of senescence. Notably, HSI was successfully applied to predict ChlF parameters (F0, Fm, and Fv/Fm) based on Partial Least Squares Regression (PLSR) and Least-Squares Support Vector Machine (LSSVM) models, with RPD values exceeding 3.0 for most parameters, indicating high predictive accuracy. In conclusion, the combined use of CFI and HSI offers a robust, non-destructive method for predicting yellowing and senescence in green 'Yali' pear, which provides valuable insights into quality monitoring and postharvest management.

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