Dataset Information

Data Fusion of Fourier Transform Mid-Infrared (MIR) and Near-Infrared (NIR) Spectroscopies to Identify Geographical Origin of Wild Paris polyphylla var. yunnanensis.

ABSTRACT: Origin traceability is important for controlling the effect of Chinese medicinal materials and Chinese patent medicines. Paris polyphylla var. yunnanensis is widely distributed and well-known all over the world. In our study, two spectroscopic techniques (Fourier transform mid-infrared (FT-MIR) and near-infrared (NIR)) were applied for the geographical origin traceability of 196 wild P. yunnanensis samples combined with low-, mid-, and high-level data fusion strategies. Partial least squares discriminant analysis (PLS-DA) and random forest (RF) were used to establish classification models. Feature variables extraction (principal component analysis-PCA) and important variables selection models (recursive feature elimination and Boruta) were applied for geographical origin traceability, while the classification ability of models with the former model is better than with the latter. FT-MIR spectra are considered to contribute more than NIR spectra. Besides, the result of high-level data fusion based on principal components (PCs) feature variables extraction is satisfactory with an accuracy of 100%. Hence, data fusion of FT-MIR and NIR signals can effectively identify the geographical origin of wild P. yunnanensis.

SUBMITTER: Pei YF

PROVIDER: S-EPMC6680555 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Publications

Data Fusion of Fourier Transform Mid-Infrared (MIR) and Near-Infrared (NIR) Spectroscopies to Identify Geographical Origin of Wild Paris polyphylla var. yunnanensis.

Pei Yi-Fei YF Zuo Zhi-Tian ZT Zhang Qing-Zhi QZ Wang Yuan-Zhong YZ

Molecules (Basel, Switzerland) 20190713 14

Origin traceability is important for controlling the effect of Chinese medicinal materials and Chinese patent medicines. Paris polyphylla var. yunnanensis is widely distributed and well-known all over the world. In our study, two spectroscopic techniques (Fourier transform mid-infrared (FT-MIR) and near-infrared (NIR)) were applied for the geographical origin traceability of 196 wild P. yunnanensis samples combined with low-, mid-, and high-level data fusion strategies. Part ...[more]

PMID: 31337084

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Project description:The root of Paris polyphylla var. yunnanensis, a famous and endangered traditional Chinese herb, has a significant medicinal value. The aim of this study was to analyze the composition and functional characteristics of bacterial endophytes in roots, stems, and leaves of P. polyphylla var. yunnanensis. The 16S rRNA gene sequencing and functional prediction of bacterial endophytes in roots, stems, and leaves of P. polyphylla var. yunnanensis were conducted. The Chao and Shannon indices of the bacteria in roots were significantly higher than those in stems and leaves. The dominant endophyte phyla were Cyanobacteria, Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria. The main genera detected in roots were unclassified Cyanobacteria, Rhizobium, Flavobacterium, and Sphingobium; the main genera in stems were norank_c__Cyanobacteria, Bacillus, and Pseudomonas; the main genera in leaves were norank_c__Cyanobacteria and Rhizobium. The microbiota in roots was particularly enriched in functional categories "extracellular structures" and "cytoskeleton" compared with stems and leaves (p < 0.05). Our study reveals the structural and functional characteristics of the endophytic bacteria in roots, stems, and leaves of P. polyphylla var. yunnanensis, which aids in the scientific understanding of this plant.The root of Paris polyphylla var. yunnanensis, a famous and endangered traditional Chinese herb, has a significant medicinal value. The aim of this study was to analyze the composition and functional characteristics of bacterial endophytes in roots, stems, and leaves of P. polyphylla var. yunnanensis. The 16S rRNA gene sequencing and functional prediction of bacterial endophytes in roots, stems, and leaves of P. polyphylla var. yunnanensis were conducted. The Chao and Shannon indices of the bacteria in roots were significantly higher than those in stems and leaves. The dominant endophyte phyla were Cyanobacteria, Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria. The main genera detected in roots were unclassified Cyanobacteria, Rhizobium, Flavobacterium, and Sphingobium; the main genera in stems were norank_c__Cyanobacteria, Bacillus, and Pseudomonas; the main genera in leaves were norank_c__Cyanobacteria and Rhizobium. The microbiota in roots was particularly enriched in functional categories “extracellular structures” and “cytoskeleton” compared with stems and leaves (p < 0.05). Our study reveals the structural and functional characteristics of the endophytic bacteria in roots, stems, and leaves of P. polyphylla var. yunnanensis, which aids in the scientific understanding of this plant.

Dataset Information

Data Fusion of Fourier Transform Mid-Infrared (MIR) and Near-Infrared (NIR) Spectroscopies to Identify Geographical Origin of Wild Paris polyphylla var. yunnanensis.

Publications

Data Fusion of Fourier Transform Mid-Infrared (MIR) and Near-Infrared (NIR) Spectroscopies to Identify Geographical Origin of Wild <i>Paris</i> <i>polyphylla</i> var. <i>yunnanensis</i>.

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