Research on the effect of processing methods on ginseng quality and key technologies for improvement

QIAO, Yong-Fei; WANG, Rong-Can; WANG, Xin-Yi; LI, Ya-Li

doi:10.1016/j.cjac.2024.100413

Chinese Journal of Analytical Chemistry

2024

DOI: 10.1016/j.cjac.2024.100413

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Research on the effect of processing methods on ginseng quality and key technologies for improvement

Yong-Fei QIAO,

Rong-Can WANG,

Xin-Yi WANG

et al.

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2024

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Cited by 1 publication

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Infrared Spectroscopy (FT-NIR) and t-Distributed Stochastic Neighbor Embedding (t-SNE) as an Analytical Methodology for Rapid Identification of Tea Adulteration

Gonçalves Lima,

Silveira,

Santana

et al. 2024

Preprint

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Teas and infusions are beverages obtained from plant extracts of flowers, fruits, stems, roots, and other parts of plants, after undergoing a process of selection, cleaning, sanitization, and dehydration. Historically used for medicinal purposes, these beverages are appreciated for their pleasant flavor and aroma, stress reduction, calming and digestive effects, and as an aid in the composition of special diets, in addition to being an excellent option as a social drink at various types of events. It is not uncommon to find commercial tea preparations mixed with leaves and parts of other plants to increase profit and production volume, which constitutes fraud. The aim of this study was to perform FT-NIR spectroscopic characterization of leaves and pieces (petiole and stem) of three types of medicinal plants (Chamomile, Ginseng, and Quebra-pedras) used in the preparation of teas. Three cluster analysis methods were used to evaluate the ability of FT-NIR to identify plant types, with t-SNE presenting the best discriminatory power. The deconvolution of the spectra showed that fifteen vibration bands allow a good characterization of the samples, all with R² greater than 0.99. The presented approach has a great potential for quality control by industry and government agencies.

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Infrared Spectroscopy (FT-NIR) and t-Distributed Stochastic Neighbor Embedding (t-SNE) as an Analytical Methodology for Rapid Identification of Tea Adulteration

Gonçalves Lima,

Silveira,

Santana

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

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Research on the effect of processing methods on ginseng quality and key technologies for improvement

Cited by 1 publication

References 43 publications

Infrared Spectroscopy (FT-NIR) and t-Distributed Stochastic Neighbor Embedding (t-SNE) as an Analytical Methodology for Rapid Identification of Tea Adulteration

Infrared Spectroscopy (FT-NIR) and t-Distributed Stochastic Neighbor Embedding (t-SNE) as an Analytical Methodology for Rapid Identification of Tea Adulteration

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