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>
Origin traceability is important for controlling the effect of Chinese medicinal materials and Chinese patent medicines. <i>Paris polyphylla</i> var. <i>yunnanensis</i> is widely distributed and well-known all over the world. In our study, two spectroscopic techniques (Fourie...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-07-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/24/14/2559 |
| _version_ | 1818927170958917632 |
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| author | Yi-Fei Pei Zhi-Tian Zuo Qing-Zhi Zhang Yuan-Zhong Wang |
| author_facet | Yi-Fei Pei Zhi-Tian Zuo Qing-Zhi Zhang Yuan-Zhong Wang |
| author_sort | Yi-Fei Pei |
| collection | DOAJ |
| description | Origin traceability is important for controlling the effect of Chinese medicinal materials and Chinese patent medicines. <i>Paris polyphylla</i> var. <i>yunnanensis</i> 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 <i>P. yunnanensis</i> 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 <i>P. yunnanensis</i>. |
| first_indexed | 2024-12-20T03:08:46Z |
| format | Article |
| id | doaj.art-8151fac4233f4852a6b44b434668750f |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-12-20T03:08:46Z |
| publishDate | 2019-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-8151fac4233f4852a6b44b434668750f2022-12-21T19:55:32ZengMDPI AGMolecules1420-30492019-07-012414255910.3390/molecules24142559molecules24142559Data 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>Yi-Fei Pei0Zhi-Tian Zuo1Qing-Zhi Zhang2Yuan-Zhong Wang3Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, ChinaInstitute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, ChinaCollege of Traditional Chinese Medicine, Yunnan University of Chinese Medicine, Kunming 650500, ChinaInstitute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, ChinaOrigin traceability is important for controlling the effect of Chinese medicinal materials and Chinese patent medicines. <i>Paris polyphylla</i> var. <i>yunnanensis</i> 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 <i>P. yunnanensis</i> 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 <i>P. yunnanensis</i>.https://www.mdpi.com/1420-3049/24/14/2559origin traceabilitydata fusion<i>Paris polyphylla</i> var. <i>yunnanensis</i>Fourier transform mid-infrared spectroscopynear-infrared spectroscopy |
| spellingShingle | Yi-Fei Pei Zhi-Tian Zuo Qing-Zhi Zhang Yuan-Zhong Wang 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> Molecules origin traceability data fusion <i>Paris polyphylla</i> var. <i>yunnanensis</i> Fourier transform mid-infrared spectroscopy near-infrared spectroscopy |
| title | 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> |
| title_full | 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> |
| title_fullStr | 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> |
| title_full_unstemmed | 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> |
| title_short | 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> |
| title_sort | 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 |
| topic | origin traceability data fusion <i>Paris polyphylla</i> var. <i>yunnanensis</i> Fourier transform mid-infrared spectroscopy near-infrared spectroscopy |
| url | https://www.mdpi.com/1420-3049/24/14/2559 |
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