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. 2024 Sep 14;10(18):e37919.
doi: 10.1016/j.heliyon.2024.e37919. eCollection 2024 Sep 30.

Hyperspectral reflectance imaging for visualizing reducing sugar content, moisture, and hollow rate in red ginseng

Xueyuan Bai  1 , Yuting You  1 , Hairui Wang  1 , Daqing Zhao  1 , Jiawen Wang  1 , Wei Zhang  1
Affiliations

Hyperspectral reflectance imaging for visualizing reducing sugar content, moisture, and hollow rate in red ginseng

Xueyuan Bai et al. Heliyon. .

Abstract

Red ginseng (RG) has been traditionally valued in Northeast Asia for its health-enhancing properties. Recent advancements in hyperspectral imaging (HSI) offer a non-destructive, efficient, and reliable method to assess critical quality indicators of RG, such as reducing sugar content (RSC), water content (WC), and hollow rate (HR). This study developed predictive models using HSI technology to monitor these quality indicators over the spectral range of 400-1700 nm. Image features were enhanced using Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF), followed by classification through Spectral Angle Mapping (SAM). The best-performing model for RSC achieved an R2 value of 0.6198 and a root mean square error (RMSE) of 0.013. For WC, the optimal model obtained an R2 value of 0.6555 and an RMSE of 0.014. The spatial distribution of RSC, WC, and HR was effectively visualized, demonstrating the potential of HSI for on-site quality control of RG. This study provides a foundation for real-time, non-invasive monitoring of RG quality, addressing industry needs for rapid and reliable assessment methods.

Keywords: Hyperspectral imaging; Non-destructive analysis; Principal component analysis; Quality assessment; Red ginseng; Spectral angle mapping; Traditional Chinese medicine; Visualization.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
Microscopic CT imaging of red ginseng hollow under different angles of view. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2
Fig. 2
PCA (A) and MNF (B) contrast-enhanced images (red circles represent the relevant alone features), changes in different measured components at different steaming time points (C). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3
Fig. 3
Average spectra of RG in VIS-NIR (A) and SWIR (B) range; wavelength selection based on different preprocessed methods VIS-NIR-PCA (C), SWIR-PCA (D), VIS-NIR-MNF (E) and SWIR-MNF (F).
Fig. 4
Fig. 4
Correlation coefficient between PCA band ratio and RG components.
Fig. 5
Fig. 5
Scatter plots of predicted/measured values of WC (A) and RSC (B), visualization of HR (C), WC (D) and RSC (E).
See this image and copyright information in PMC

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