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Zhang H, Pan Y, Liu X, Chen Y, Gong X, Zhu J, Yan J, Zhang H. Recognition of the rhizome of red ginseng based on spectral-image dual-scale digital information combined with intelligent algorithms. Spectrochim Acta A Mol Biomol Spectrosc 2023; 297:122742. [PMID: 37098315 DOI: 10.1016/j.saa.2023.122742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 04/08/2023] [Accepted: 04/11/2023] [Indexed: 05/14/2023]
Abstract
Red ginseng is a widely used and extensively researched food and medicinal product with high nutritional value, derived from steamed fresh ginseng. The components in various parts of red ginseng differ significantly, resulting in distinct pharmacological activities and efficacies. This study proposed to establish a hyperspectral imaging technology combined with intelligent algorithms for the recognition of different parts of red ginseng based on the dual-scale of spectrum and image information. Firstly, the spectral information was processed by the best combination of first derivative as pre-processing method and partial least squares discriminant analysis (PLS-DA) as classification model. The recognition accuracy of the rhizome and the main root of red ginseng is 96.79% and 95.94% respectively. Then, the image information was processed by the You Only Look Once version 5 small (YOLO v5s) model. The best parameter combination is epoch = 30, learning rate = 0.01, and activation function is leaky ReLU. In the red ginseng dataset, the highest accuracy, recall and mean Average Precision at IoU (Intersection over Union) threshold 0.5 (mAP@0.5) were 99.01%, 98.51% and 99.07% respectively. The application of spectrum-image dual-scale digital information combined with intelligent algorithms in the recognition of red ginseng is successful, which provides a positive significance for the online and on-site quality control and authenticity identification of crude drugs or fruits.
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Affiliation(s)
- HongXu Zhang
- College of Pharmaceutical Science, Zhejiang University of Technology, No. 18, Chaowang Road, Hangzhou 310014, China
| | - YiXia Pan
- College of Pharmaceutical Science, Zhejiang University of Technology, No. 18, Chaowang Road, Hangzhou 310014, China
| | - XiaoYi Liu
- College of Pharmaceutical Science, Zhejiang University of Technology, No. 18, Chaowang Road, Hangzhou 310014, China
| | - Yuan Chen
- College of Pharmaceutical Science, Zhejiang University of Technology, No. 18, Chaowang Road, Hangzhou 310014, China
| | - XingChu Gong
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - JieQiang Zhu
- College of Pharmaceutical Science, Zhejiang University of Technology, No. 18, Chaowang Road, Hangzhou 310014, China
| | - JiZhong Yan
- College of Pharmaceutical Science, Zhejiang University of Technology, No. 18, Chaowang Road, Hangzhou 310014, China.
| | - Hui Zhang
- College of Pharmaceutical Science, Zhejiang University of Technology, No. 18, Chaowang Road, Hangzhou 310014, China.
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Shi T, Chen Y, Liu Y, Wu G. Visible and near-infrared reflectance spectroscopy-an alternative for monitoring soil contamination by heavy metals. J Hazard Mater 2014; 265:166-176. [PMID: 24361494 DOI: 10.1016/j.jhazmat.2013.11.059] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2013] [Revised: 11/28/2013] [Accepted: 11/29/2013] [Indexed: 06/03/2023]
Abstract
Soil contamination by heavy metals is an increasingly important problem worldwide. Quick and reliable access to heavy metal concentration data is crucial for soil monitoring and remediation. Visible and near-infrared reflectance spectroscopy, which is known as a noninvasive, cost-effective, and environmentally friendly technique, has potential for the simultaneous estimation of the various heavy metal concentrations in soil. Moreover, it provides a valid alternative method for the estimation of heavy metal concentrations over large areas and long periods of time. This paper reviews the state of the art and presents the mechanisms, data, and methods for the estimation of heavy metal concentrations by the use of visible and near-infrared reflectance spectroscopy. The challenges facing the application of hyperspectral images in mapping soil contamination over large areas are also discussed.
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Affiliation(s)
- Tiezhu Shi
- School of Resource and Environmental Science & Key Laboratory of Geographic Information System of the Ministry of Education, Wuhan University, 430079 Wuhan, China
| | - Yiyun Chen
- School of Resource and Environmental Science & Key Laboratory of Geographic Information System of the Ministry of Education, Wuhan University, 430079 Wuhan, China
| | - Yaolin Liu
- School of Resource and Environmental Science & Key Laboratory of Geographic Information System of the Ministry of Education, Wuhan University, 430079 Wuhan, China
| | - Guofeng Wu
- Key Laboratory for Geo-Environment Monitoring of Coastal Zone, National Administration of Surveying, Mapping and GeoInformation & Shenzhen Key Laboratory of Spatial Smart Sensing and Services & College of Life Sciences, Shenzhen University, 518060 Shenzhen, China; School of Resource and Environmental Science & Key Laboratory of Geographic Information System of the Ministry of Education, Wuhan University, 430079 Wuhan, China.
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