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Discrimination of wild Paris based on near infrared spectroscopy and high performance liquid chromatography combined with multivariate analysis

Zhao, Yanli ; Zhang, Ji ; Yuan, Tianjun ; Shen, Tao ; Li, Wei ; Yang, Shihua ; Hou, Ying ; Wang, Yuanzhong ; Jin, Hang Motta, Andrea

PloS one, 2014-02, Vol.9 (2), p.e89100-e89100 [Periódico revisado por pares]

United States: Public Library of Science

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Título:
Discrimination of wild Paris based on near infrared spectroscopy and high performance liquid chromatography combined with multivariate analysis
Autor: Zhao, Yanli ; Zhang, Ji ; Yuan, Tianjun ; Shen, Tao ; Li, Wei ; Yang, Shihua ; Hou, Ying ; Wang, Yuanzhong ; Jin, Hang
Motta, Andrea
Assuntos: Analysis ; Biology ; Chemistry ; China ; Chinese medicine ; Chromatography ; Chromatography, High Pressure Liquid - methods ; Climate change ; Data collection ; Diosgenin - analogs & derivatives ; Diosgenin - analysis ; Diosgenin - chemistry ; Discriminant analysis ; Feasibility studies ; Flavonoids ; Food ; Fourier transforms ; Geographical distribution ; Geography ; Herbal medicine ; High performance liquid chromatography ; Identification ; Infrared analysis ; Infrared spectroscopy ; Liquid chromatography ; Magnoliopsida - chemistry ; Mathematical models ; Methods ; Models, Biological ; Molecular Structure ; Morphology ; Multivariate Analysis ; Near infrared radiation ; Near infrared spectroscopy ; Origins ; Pharmaceuticals ; Quality control ; Saponins ; Saponins - analysis ; Saponins - chemistry ; Scanning ; Species ; Species Specificity ; Spectroscopy ; Spectroscopy, Near-Infrared - methods ; Statistical analysis ; Statistical methods ; Tobacco ; Yttrium
É parte de: PloS one, 2014-02, Vol.9 (2), p.e89100-e89100
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Conceived and designed the experiments: YZ TY YW HJ. Performed the experiments: JZ TY TS WL. Analyzed the data: YZ TY SY YH. Contributed reagents/materials/analysis tools: SY YH YW HJ. Wrote the paper: YZ TY YW HJ.
Competing Interests: Although some authors are employed by a commercial company (Yunnan Reascend Tobacco Technology (Group) Co., Ltd.), this does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.
Descrição: Different geographical origins and species of Paris obtained from southwestern China were discriminated by near infrared (NIR) spectroscopy and high performance liquid chromatography (HPLC) combined with multivariate analysis. The NIR parameter settings were scanning (64 times), resolution (4 cm(-1)), scanning range (10,000 cm(-1)∼4000 cm(-1)) and parallel collection (3 times). NIR spectrum was optimized by TQ 8.6 software, and the ranges 7455∼6852 cm(-1) and 5973∼4007 cm(-1) were selected according to the spectrum standard deviation. The contents of polyphyllin I, polyphyllin II, polyphyllin VI, and polyphyllin VII and total steroid saponins were detected by HPLC. The contents of chemical components data matrix and spectrum data matrix were integrated and analyzed by partial least squares discriminant analysis (PLS-DA). From the PLS-DA model of NIR spectrum, Paris samples were separated into three groups according to the different geographical origins. The R(2)X and Q(2)Y described accumulative contribution rates were 99.50% and 94.03% of the total variance, respectively. The PLS-DA model according to 12 species of Paris described 99.62% of the variation in X and predicted 95.23% in Y. The results of the contents of chemical components described differences among collections quantitatively. A multivariate statistical model of PLS-DA showed geographical origins of Paris had a much greater influence on Paris compared with species. NIR and HPLC combined with multivariate analysis could discriminate different geographical origins and different species. The quality of Paris showed regional dependence.
Editor: United States: Public Library of Science
Idioma: Inglês

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Discrimination of wild Paris based on near infrared spectroscopy and high performance liquid chromatography combined with multivariate analysis

Zhao, Yanli ; Zhang, Ji ; Yuan, Tianjun ; Shen, Tao ; Li, Wei ; Yang, Shihua ; Hou, Ying ; Wang, Yuanzhong ; Jin, Hang Motta, Andrea

United States: Public Library of Science

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