An integrated spectroscopic strategy to trace the geographical origins of emblic medicines: Application for the quality assessment of natural medicines
Open accessAbstract
Emblic medicine is a popular natural source in the world due to its outstanding healthcare and therapeutic functions. Our preliminary results indicated that the quality of emblic medicines might have an apparent regional variation. A rapid and effective geographical traceability system has not been designed yet. To trace the geographical origins so that their quality can be controlled, an integrated spectroscopic strategy including spectral pretreatment, outlier diagnosis, feature selection, data fusion, and machine learning algorithm was proposed. A featured data matrix (245 × 220) was successfully generated, and a carefully adjusted RF machine learning algorithm was utilized to develop the geographical traceability model. The results demonstrate that the proposed strategy is effective and can be generalized. Sensitivity (SEN), specificity (SPE) and accuracy (ACC) of 97.65%, 99.85% and 97.63% for the calibrated set, as well as 100.00% predictive efficiency, were obtained using this spectroscopic analysis strategy. Our study has created an integrated analysis process for multiple spectral data, which can achieve a rapid, nondestructive and green quality detection for emblic medicines originating from seventeen geographical origins.
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Geographic indication is a major consideration for the overall quality of turmeric.
“Geographic indication (GI) is a major consideration for the overall quality of this natural medicine [3,16].”
From Rapid metabolic fingerprinting with the aid of chemometric models to identify authenticity of natural medicines: Turmeric, Ocimum, and Withania somnifera study (2023) · cites this paper as [16]
The Introduction says geographical origin affects the quality of natural medicines, and the Results and discussion section finds a significant effect on the quality of emblic products. The paper does not study turmeric, so it supports the general geographic-quality consideration but not its application to turmeric specifically. (LLM, conf=0.86)
Experimental — accuracy not yet measuredFT-NIR metabolic fingerprinting has recently been used to identify the geographic origin of herbal medicines.
“Recently, FT-NIR metabolic fingerprinting has been used to identify the geographic origin of herbal medicines [3,16].”
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- Authors
- Qi, L., Zhong, F., Chen, Y., Mao, S., Yan, Z., & Ma, Y.
- Affiliations
- Chengdu University of Traditional Chinese Medicine (CN)
- Corresponding author
- Yan, Zhuyun
- Ma, Yuntong
- Venue
- Journal of Pharmaceutical Analysis
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 10
- Issue
- 4
- Pages
- 356-364
- ISSN
- 2095-1779 (ISSN-L)
- PMC
- PMC7474118
- OpenAlex
- W2995207171
- Cited by
- 26
- References
- 45
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 10 · 2023: 3 · 2022: 1 · 2021: 1
- FWCI
- 0.28
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Pharmaceutical Analysis (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Standardization and Community for the Collection and Preservation of Important Wild Plant Germplasm Resources (2005DKA21006)
- Topics
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Health Sciences › Medicine › Complementary and alternative medicine › Traditional Chinese Medicine Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
- Keywords
- geographical origin traceability, spectral preprocessing, feature selection, spectral data fusion, random forest classification
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