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A rapid identification of four medicinal chrysanthemum varieties with near infrared spectroscopy
BACKGROUND: For genuine medicinal material in Chinese herbs; the efficient, rapid, and precise identification is the focus and difficulty in the filed studying Chinese herbal medicines. Chrysanthemum morifolium as herbs has a long planting history in China, culturing high quality ones and different...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159931/ https://www.ncbi.nlm.nih.gov/pubmed/25210325 http://dx.doi.org/10.4103/0973-1296.137378 |
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author | Han, Bangxing Yan, Hui Chen, Cunwu Yao, Houjun Dai, Jun Chen, Naifu |
author_facet | Han, Bangxing Yan, Hui Chen, Cunwu Yao, Houjun Dai, Jun Chen, Naifu |
author_sort | Han, Bangxing |
collection | PubMed |
description | BACKGROUND: For genuine medicinal material in Chinese herbs; the efficient, rapid, and precise identification is the focus and difficulty in the filed studying Chinese herbal medicines. Chrysanthemum morifolium as herbs has a long planting history in China, culturing high quality ones and different varieties. Different chrysanthemum varieties differ in quality, chemical composition, functions, and application. Therefore, chrysanthemum varieties in the market demands precise identification to provide reference for reasonable and correct application as genuine medicinal material. MATERIALS AND METHODS: A total of 244 batches of chrysanthemum samples were randomly divided into calibration set (160 batches) and prediction set (84 batches). The near infrared diffuses reflectance spectra of chrysanthemum varieties were preprocessed by first order derivative (D1) and autoscaling and was built model with partial least squares (PLS). RESULTS: In this study of four chrysanthemum varieties identification, the accuracy rates in calibration sets of Boju, Chuju, Hangju, and Gongju are respectively 100, 100, 98.65, and 96.67%; while the accuracy rates in prediction sets are 100% except for 99.1% of Hangju. CONCLUSION: The research results demonstrate that the qualitative analysis can be conducted by machine learning combined with near infrared spectroscopy (NIR), which provides a new method for rapid and noninvasive identification of chrysanthemum varieties. |
format | Online Article Text |
id | pubmed-4159931 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-41599312014-09-10 A rapid identification of four medicinal chrysanthemum varieties with near infrared spectroscopy Han, Bangxing Yan, Hui Chen, Cunwu Yao, Houjun Dai, Jun Chen, Naifu Pharmacogn Mag Original Article BACKGROUND: For genuine medicinal material in Chinese herbs; the efficient, rapid, and precise identification is the focus and difficulty in the filed studying Chinese herbal medicines. Chrysanthemum morifolium as herbs has a long planting history in China, culturing high quality ones and different varieties. Different chrysanthemum varieties differ in quality, chemical composition, functions, and application. Therefore, chrysanthemum varieties in the market demands precise identification to provide reference for reasonable and correct application as genuine medicinal material. MATERIALS AND METHODS: A total of 244 batches of chrysanthemum samples were randomly divided into calibration set (160 batches) and prediction set (84 batches). The near infrared diffuses reflectance spectra of chrysanthemum varieties were preprocessed by first order derivative (D1) and autoscaling and was built model with partial least squares (PLS). RESULTS: In this study of four chrysanthemum varieties identification, the accuracy rates in calibration sets of Boju, Chuju, Hangju, and Gongju are respectively 100, 100, 98.65, and 96.67%; while the accuracy rates in prediction sets are 100% except for 99.1% of Hangju. CONCLUSION: The research results demonstrate that the qualitative analysis can be conducted by machine learning combined with near infrared spectroscopy (NIR), which provides a new method for rapid and noninvasive identification of chrysanthemum varieties. Medknow Publications & Media Pvt Ltd 2014 /pmc/articles/PMC4159931/ /pubmed/25210325 http://dx.doi.org/10.4103/0973-1296.137378 Text en Copyright: © Pharmacognosy Magazine http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Han, Bangxing Yan, Hui Chen, Cunwu Yao, Houjun Dai, Jun Chen, Naifu A rapid identification of four medicinal chrysanthemum varieties with near infrared spectroscopy |
title | A rapid identification of four medicinal chrysanthemum varieties with near infrared spectroscopy |
title_full | A rapid identification of four medicinal chrysanthemum varieties with near infrared spectroscopy |
title_fullStr | A rapid identification of four medicinal chrysanthemum varieties with near infrared spectroscopy |
title_full_unstemmed | A rapid identification of four medicinal chrysanthemum varieties with near infrared spectroscopy |
title_short | A rapid identification of four medicinal chrysanthemum varieties with near infrared spectroscopy |
title_sort | rapid identification of four medicinal chrysanthemum varieties with near infrared spectroscopy |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159931/ https://www.ncbi.nlm.nih.gov/pubmed/25210325 http://dx.doi.org/10.4103/0973-1296.137378 |
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