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Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine
Andrographis paniculata (Burm. F) Nees, has been widely used for upper respiratory tract and several other diseases and general immunity for a historically long time in countries like India, China, Thailand, Japan, and Malaysia. The vegetative productivity and quality with respect to pharmaceutical...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8134700/ https://www.ncbi.nlm.nih.gov/pubmed/34025404 http://dx.doi.org/10.3389/fphar.2021.629833 |
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author | Sing, Dilip Banerjee, Subhadip Jana, Shibu Narayan Mallik, Ranajoy Dastidar, Sudarshana Ghosh Majumdar, Kalyan Bandyopadhyay, Amitabha Bandyopadhyay, Rajib Mukherjee, Pulok K. |
author_facet | Sing, Dilip Banerjee, Subhadip Jana, Shibu Narayan Mallik, Ranajoy Dastidar, Sudarshana Ghosh Majumdar, Kalyan Bandyopadhyay, Amitabha Bandyopadhyay, Rajib Mukherjee, Pulok K. |
author_sort | Sing, Dilip |
collection | PubMed |
description | Andrographis paniculata (Burm. F) Nees, has been widely used for upper respiratory tract and several other diseases and general immunity for a historically long time in countries like India, China, Thailand, Japan, and Malaysia. The vegetative productivity and quality with respect to pharmaceutical properties of Andrographis paniculata varies considerably across production, ecologies, and genotypes. Thus, a field deployable instrument, which can quickly assess the quality of the plant material with minimal processing, would be of great use to the medicinal plant industry by reducing waste, and quality grading and assurance. In this paper, the potential of near infrared reflectance spectroscopy (NIR) was to estimate the major group active molecules, the andrographolides in Andrographis paniculata, from dried leaf samples and leaf methanol extracts and grade the plant samples from different sources. The calibration model was developed first on the NIR spectra obtained from the methanol extracts of the samples as a proof of concept and then the raw ground samples were estimated for gradation. To grade the samples into three classes: good, medium and poor, a model based on a machine learning algorithm - support vector machine (SVM) on NIR spectra was built. The tenfold classification results of the model had an accuracy of 83% using standard normal variate (SNV) preprocessing. |
format | Online Article Text |
id | pubmed-8134700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81347002021-05-21 Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine Sing, Dilip Banerjee, Subhadip Jana, Shibu Narayan Mallik, Ranajoy Dastidar, Sudarshana Ghosh Majumdar, Kalyan Bandyopadhyay, Amitabha Bandyopadhyay, Rajib Mukherjee, Pulok K. Front Pharmacol Pharmacology Andrographis paniculata (Burm. F) Nees, has been widely used for upper respiratory tract and several other diseases and general immunity for a historically long time in countries like India, China, Thailand, Japan, and Malaysia. The vegetative productivity and quality with respect to pharmaceutical properties of Andrographis paniculata varies considerably across production, ecologies, and genotypes. Thus, a field deployable instrument, which can quickly assess the quality of the plant material with minimal processing, would be of great use to the medicinal plant industry by reducing waste, and quality grading and assurance. In this paper, the potential of near infrared reflectance spectroscopy (NIR) was to estimate the major group active molecules, the andrographolides in Andrographis paniculata, from dried leaf samples and leaf methanol extracts and grade the plant samples from different sources. The calibration model was developed first on the NIR spectra obtained from the methanol extracts of the samples as a proof of concept and then the raw ground samples were estimated for gradation. To grade the samples into three classes: good, medium and poor, a model based on a machine learning algorithm - support vector machine (SVM) on NIR spectra was built. The tenfold classification results of the model had an accuracy of 83% using standard normal variate (SNV) preprocessing. Frontiers Media S.A. 2021-05-06 /pmc/articles/PMC8134700/ /pubmed/34025404 http://dx.doi.org/10.3389/fphar.2021.629833 Text en Copyright © 2021 Sing, Banerjee, Jana, Mallik, Dastidar, Majumdar, Bandyopadhyay, Bandyopadhyay and Mukherjee. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Sing, Dilip Banerjee, Subhadip Jana, Shibu Narayan Mallik, Ranajoy Dastidar, Sudarshana Ghosh Majumdar, Kalyan Bandyopadhyay, Amitabha Bandyopadhyay, Rajib Mukherjee, Pulok K. Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine |
title | Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine |
title_full | Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine |
title_fullStr | Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine |
title_full_unstemmed | Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine |
title_short | Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine |
title_sort | estimation of andrographolides and gradation of andrographis paniculata leaves using near infrared spectroscopy together with support vector machine |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8134700/ https://www.ncbi.nlm.nih.gov/pubmed/34025404 http://dx.doi.org/10.3389/fphar.2021.629833 |
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