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Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology
Yurong Zhang1,2,3, Wenliang Wu1,2,3, Xianqing Zhou1,2,3
1School of Food and Strategic Reserves, Henan University of Technology, Zhengzhou 450001, China.
Molecules (Basel, Switzerland)
|March 27, 2025
Summary
Hyperspectral imaging offers a rapid, non-destructive method to assess soybean storage quality by predicting crude fatty acid values. This technology accurately monitors soybean degradation, ensuring better food processing and consumption.
Area of Science:
- Agricultural Science
- Food Science
- Spectroscopy
Background:
- Soybean storage quality is vital for processing and consumption.
- Objective, rapid, and non-destructive quality assessment methods are needed.
- Crude fatty acid value is a key indicator of soybean storage quality.
Purpose of the Study:
- To evaluate hyperspectral imaging for non-destructive soybean storage quality assessment.
- To develop predictive models for crude fatty acid values.
- To visualize the dynamic distribution of crude fatty acid values.
Main Methods:
- Accelerated aging of three soybean types to analyze crude fatty acid value trends.
- Hyperspectral imaging data acquisition and preprocessing (1ST, 2ND, MSC, SNV).
- Feature variable extraction (VISSA, CARS, SPA) and model development (PLSR, SVM, ELM).
Main Results:
- Crude fatty acid values positively correlated with storage time, indicating quality degradation.
- The 1ST-VISSA-SVM model achieved R² of 0.9888 and RMSE of 0.1857 for predicting crude fatty acid values.
- Successful visualization of dynamic chemical information related to soybean quality.
Conclusions:
- Hyperspectral imaging is a capable technology for non-destructive and rapid detection of soybean storage quality.
- The developed model accurately predicts crude fatty acid values, reflecting storage quality.
- This approach supports objective quality control in soybean processing and trade.
