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Optimized microwave assisted extraction (MAE) of alkaloids and polyphenols from Berberis roots using multiple-component analysis
Berberis, one of the major sources of berberine and polyphenols, is widely accepted genus for its medicinal properties. The inclusion of these phytochemicals in different health formulations has widened its scope in pharmaceuticals and nutraceuticals. In the present study, multi-component analysis (...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6976575/ https://www.ncbi.nlm.nih.gov/pubmed/31969583 http://dx.doi.org/10.1038/s41598-020-57585-8 |
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author | Belwal, Tarun Pandey, Aseesh Bhatt, Indra D. Rawal, Ranbeer S. |
author_facet | Belwal, Tarun Pandey, Aseesh Bhatt, Indra D. Rawal, Ranbeer S. |
author_sort | Belwal, Tarun |
collection | PubMed |
description | Berberis, one of the major sources of berberine and polyphenols, is widely accepted genus for its medicinal properties. The inclusion of these phytochemicals in different health formulations has widened its scope in pharmaceuticals and nutraceuticals. In the present study, multi-component analysis (MCA) has been used to extract these nutraceutical compounds from Berberis jaeschkeana roots under microwave-assisted extraction (MAE) conditions. To determine the optimum extraction condition, different factors, including, microwave power, sample to solvent ratio, irradiation time, solvent pH and solvent concentration were tested under 42 experiments. The MCA includes, Plackett-Burmen and Central Composite Design and analyzes model fitness, regression coefficient (β), analysis of variance (ANOVA) and 3D response curve. The results showed significant model fitness and involvement of linear, quadratic and interactive effect of different factors. Under optimized MAE condition, [i.e. 1 g of sample extracted through 70 mL of a solution (100% methanol pH 2.0), provided microwave power of 598 W for 2 min of irradiation time], the berberine and palmatine contents were recorded as 46.38 mg g(−1) and 20.54 mg g(−1) respectively. Under optimized condition, the yield of alkaloids were found closer to the models’ predicted value. Similarly, total phenolic content and antioxidant activities were also found closer to the models’ predicted value. To test the suitability of the optimized MAE condition for other species i.e., Berberis asiatica, extraction of alkaloids and polyphenolics was conducted and recorded higher yield to the previous records. Moreover, under optimum extraction condition, six and seven polyphenolic compounds from B. jaeschkeana and B. asiatica were quantified respectively. The proposed MAE optimization design using MCA contributes towards faster and greener extraction of alkaloids and polyphenolics with higher yield. Moreover these greener approaches could sustainably utilize species during extract preparation and harnessing its nutraceutical and pharmaceutical potential. This study design could also be replicated on other valuable species or compounds for effective extraction of nutraceutical components and sustainable utilization of natural products. |
format | Online Article Text |
id | pubmed-6976575 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69765752020-01-29 Optimized microwave assisted extraction (MAE) of alkaloids and polyphenols from Berberis roots using multiple-component analysis Belwal, Tarun Pandey, Aseesh Bhatt, Indra D. Rawal, Ranbeer S. Sci Rep Article Berberis, one of the major sources of berberine and polyphenols, is widely accepted genus for its medicinal properties. The inclusion of these phytochemicals in different health formulations has widened its scope in pharmaceuticals and nutraceuticals. In the present study, multi-component analysis (MCA) has been used to extract these nutraceutical compounds from Berberis jaeschkeana roots under microwave-assisted extraction (MAE) conditions. To determine the optimum extraction condition, different factors, including, microwave power, sample to solvent ratio, irradiation time, solvent pH and solvent concentration were tested under 42 experiments. The MCA includes, Plackett-Burmen and Central Composite Design and analyzes model fitness, regression coefficient (β), analysis of variance (ANOVA) and 3D response curve. The results showed significant model fitness and involvement of linear, quadratic and interactive effect of different factors. Under optimized MAE condition, [i.e. 1 g of sample extracted through 70 mL of a solution (100% methanol pH 2.0), provided microwave power of 598 W for 2 min of irradiation time], the berberine and palmatine contents were recorded as 46.38 mg g(−1) and 20.54 mg g(−1) respectively. Under optimized condition, the yield of alkaloids were found closer to the models’ predicted value. Similarly, total phenolic content and antioxidant activities were also found closer to the models’ predicted value. To test the suitability of the optimized MAE condition for other species i.e., Berberis asiatica, extraction of alkaloids and polyphenolics was conducted and recorded higher yield to the previous records. Moreover, under optimum extraction condition, six and seven polyphenolic compounds from B. jaeschkeana and B. asiatica were quantified respectively. The proposed MAE optimization design using MCA contributes towards faster and greener extraction of alkaloids and polyphenolics with higher yield. Moreover these greener approaches could sustainably utilize species during extract preparation and harnessing its nutraceutical and pharmaceutical potential. This study design could also be replicated on other valuable species or compounds for effective extraction of nutraceutical components and sustainable utilization of natural products. Nature Publishing Group UK 2020-01-22 /pmc/articles/PMC6976575/ /pubmed/31969583 http://dx.doi.org/10.1038/s41598-020-57585-8 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Belwal, Tarun Pandey, Aseesh Bhatt, Indra D. Rawal, Ranbeer S. Optimized microwave assisted extraction (MAE) of alkaloids and polyphenols from Berberis roots using multiple-component analysis |
title | Optimized microwave assisted extraction (MAE) of alkaloids and polyphenols from Berberis roots using multiple-component analysis |
title_full | Optimized microwave assisted extraction (MAE) of alkaloids and polyphenols from Berberis roots using multiple-component analysis |
title_fullStr | Optimized microwave assisted extraction (MAE) of alkaloids and polyphenols from Berberis roots using multiple-component analysis |
title_full_unstemmed | Optimized microwave assisted extraction (MAE) of alkaloids and polyphenols from Berberis roots using multiple-component analysis |
title_short | Optimized microwave assisted extraction (MAE) of alkaloids and polyphenols from Berberis roots using multiple-component analysis |
title_sort | optimized microwave assisted extraction (mae) of alkaloids and polyphenols from berberis roots using multiple-component analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6976575/ https://www.ncbi.nlm.nih.gov/pubmed/31969583 http://dx.doi.org/10.1038/s41598-020-57585-8 |
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