ArticleScientific reports2018
Application of variable selection in the origin discrimination of Wolfiporia cocos (F.A. Wolf) Ryvarden & Gilb. based on near infrared spectroscopy.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Trends in digital detection for the quality and safety of herbs using infrared and Raman spectroscopy.Frontiers in plant science · 2023Review
- Geographic Origin Discrimination of Millet Using Vis-NIR Spectroscopy Combined with Machine Learning Techniques.Foods (Basel, Switzerland) · 2021Article
- Comparison of Geographical Traceability of Wild and CultivatedJournal of analytical methods in chemistry · 2021Article
- Application of Visible/Infrared Spectroscopy and Hyperspectral Imaging With Machine Learning Techniques for Identifying Food Varieties and Geographical Origins.Frontiers in nutrition · 2021Review
- Novel NIR modeling design and assignment in process quality control of Honeysuckle flower by QbD.Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy · 2020Article
- Phytochemistry and Pharmacological Activities ofFrontiers in pharmacology · 2020Review
- Geographical Authentication ofMolecules (Basel, Switzerland) · 2019Article
- Differentiation and comparison of Wolfiporia cocos raw materials based on multi-spectral information fusion and chemometric methods.Scientific reports · 2018Article
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4 authors.
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Abstract
Dried sclerotium of Wolfiporia cocos (F.A. Wolf) Ryvarden & Gilb. is a traditional Chinese medicine. Its chemical components showed difference among geographical origins, which made it difficult to keep therapeutic potency consistent. The identification of the geographical origin of W. cocos is the fundamental prerequisite for its worldwide recognition and acceptance. Four variable selection methods were employed for near infrared spectroscopy (NIR) variable selection and the characteristic variables were screened for the establishment of Fisher function models in further identification of the origin of W. cocos from Yunnan, China. For the obvious differences between poriae cutis (fu-ling-pi in Chinese, or FLP) and the inner part (bai-fu-ling in Chinese, or BFL) of the sclerotia of W. cocos in the pattern space of principal component analysis (PCA), we established discriminant models for FLP and BFL separately. Through variable selection, the models were significant improved and also the models were simplified by using only a small part of the variables. The characteristic variables were screened (13 for BFL and 10 for FLP) to build Fisher discriminant function models and the validation results showed the models were reliable and effective. Additionally, the characteristic variables were interpreted.
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