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Related Experiment Video

Updated: Feb 5, 2026

Controlled-release of Chlorine Dioxide in a Perforated Packaging System to Extend the Storage Life and Improve the Safety of Grape Tomatoes
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Logistics Process Safety System of Table Grapes Based on NIR.

Xiao-yu Chen, Xiao-shuan Zhang, Zhi-qiang Zhu

    Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
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    Shelf life prediction for table grapes using near-infrared (NIR) spectroscopy and texture analysis improves logistics safety. This method helps reduce spoilage and loss during transport, ensuring better quality produce.

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    Area of Science:

    • Agricultural Science
    • Food Science
    • Spectroscopy

    Background:

    • Table grape logistics commonly utilize sulfur dioxide (SO2) based fresh-keeping agents.
    • Postharvest texture degradation is a primary factor limiting table grape shelf life.
    • Reducing losses in table grape logistics necessitates improved shelf life prediction.

    Purpose of the Study:

    • To develop a shelf life prediction method for table grapes.
    • To investigate the influence of temperature and sulfur dioxide (SO2) concentrations on grape texture.
    • To design a logistics process safety system based on shelf life prediction.

    Main Methods:

    • Utilized near-infrared (NIR) spectroscopy and texture evolution analysis.
    • Employed SO2 concentration sensors and an automatic compensation mechanism for controlled SO2 levels.
    • Developed a non-destructive testing model using NIR and partial least squares regression (PLSR).
    • Compared NIR data preprocessing techniques: multiplicative scatter correction and S-G derivation.

    Main Results:

    • The NIR-based texture model achieved a coefficient of determination (R²) of 0.93 and RMSE of 1.70.
    • Full cross-validation yielded a prediction accuracy of 0.81 and RMSE of 2.91.
    • Demonstrated the impact of SO2 concentrations and temperature on table grape texture evolution.

    Conclusions:

    • NIR detection combined with quality change modeling and information technology can enhance postharvest fruit and vegetable logistics safety.
    • The developed model provides a reliable method for predicting table grape shelf life.
    • This approach contributes to reducing postharvest losses and improving food supply chain management.