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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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Autores principales: Sing, Dilip, Banerjee, Subhadip, Jana, Shibu Narayan, Mallik, Ranajoy, Dastidar, Sudarshana Ghosh, Majumdar, Kalyan, Bandyopadhyay, Amitabha, Bandyopadhyay, Rajib, Mukherjee, Pulok K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
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.
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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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