Cargando…

Predicting phytochemical diversity of medicinal and aromatic plants (MAPs) across eco-climatic zones and elevation in Uttarakhand using Generalized Additive Model

The present study uses a systematic approach to explore the phytochemical composition of medicinal plants from Uttarakhand, Western Himalaya. The phytochemical composition of medicinal plants was analyzed based on (i) the presence of different chemical groups and (ii) bioactive compounds. The Genera...

Descripción completa

Detalles Bibliográficos
Autores principales: Tiwari, Deepti, Kewlani, Pushpa, Gaira, Kailash S., Bhatt, Indra D., Sundriyal, R. C., Pande, Veena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10322824/
https://www.ncbi.nlm.nih.gov/pubmed/37407604
http://dx.doi.org/10.1038/s41598-023-37495-1
_version_ 1785068841871605760
author Tiwari, Deepti
Kewlani, Pushpa
Gaira, Kailash S.
Bhatt, Indra D.
Sundriyal, R. C.
Pande, Veena
author_facet Tiwari, Deepti
Kewlani, Pushpa
Gaira, Kailash S.
Bhatt, Indra D.
Sundriyal, R. C.
Pande, Veena
author_sort Tiwari, Deepti
collection PubMed
description The present study uses a systematic approach to explore the phytochemical composition of medicinal plants from Uttarakhand, Western Himalaya. The phytochemical composition of medicinal plants was analyzed based on (i) the presence of different chemical groups and (ii) bioactive compounds. The Generalized Additive Model (GAM) analysis was used to predict the occurrence of chemical groups and active compounds across different eco-climatic zones and the elevation in Uttarakhand. A total of 789 medicinal plants represented by 144 taxonomic families were screened to explore the phytochemical diversity of the medicinal plants of Uttarakhand. These medicinal plant species are signified in different life forms such as herbs (58.86%), shrubs (18.24%), trees (17.48%), ferns (2.38%), and climbers (2.13%). The probability of occurrence of the chemical groups found in tropical, sub-tropical, and warm temperate eco-climatic zones, whereas active compounds have a high Probability towards alpine, sub-alpine, and cool temperate zones. The GAM predicted that the occurrence of species with active compounds was declining significantly (p < 0.01), while total active compounds increased across elevation (1000 m). While the occurrence of species with the chemical group increased, total chemical groups were indicated to decline with increasing elevation from 1000 m (p < 0.000). The current study is overwhelmed to predict the distribution of phytochemicals in different eco-climatic zones and elevations using secondary information, which offers to discover bioactive compounds of the species occurring in the different eco-climatic habitats of the region and setting the priority of conservation concerns. However, the study encourages the various commercial sectors, such as pharmaceutical, nutraceutical, chemical, food, and cosmetics, to utilize unexplored species. In addition, the study suggests that prioritizing eco-climatic zones and elevation based on phytochemical diversity should be a factor of concern in the Himalayan region, especially under the climate change scenario.
format Online
Article
Text
id pubmed-10322824
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-103228242023-07-07 Predicting phytochemical diversity of medicinal and aromatic plants (MAPs) across eco-climatic zones and elevation in Uttarakhand using Generalized Additive Model Tiwari, Deepti Kewlani, Pushpa Gaira, Kailash S. Bhatt, Indra D. Sundriyal, R. C. Pande, Veena Sci Rep Article The present study uses a systematic approach to explore the phytochemical composition of medicinal plants from Uttarakhand, Western Himalaya. The phytochemical composition of medicinal plants was analyzed based on (i) the presence of different chemical groups and (ii) bioactive compounds. The Generalized Additive Model (GAM) analysis was used to predict the occurrence of chemical groups and active compounds across different eco-climatic zones and the elevation in Uttarakhand. A total of 789 medicinal plants represented by 144 taxonomic families were screened to explore the phytochemical diversity of the medicinal plants of Uttarakhand. These medicinal plant species are signified in different life forms such as herbs (58.86%), shrubs (18.24%), trees (17.48%), ferns (2.38%), and climbers (2.13%). The probability of occurrence of the chemical groups found in tropical, sub-tropical, and warm temperate eco-climatic zones, whereas active compounds have a high Probability towards alpine, sub-alpine, and cool temperate zones. The GAM predicted that the occurrence of species with active compounds was declining significantly (p < 0.01), while total active compounds increased across elevation (1000 m). While the occurrence of species with the chemical group increased, total chemical groups were indicated to decline with increasing elevation from 1000 m (p < 0.000). The current study is overwhelmed to predict the distribution of phytochemicals in different eco-climatic zones and elevations using secondary information, which offers to discover bioactive compounds of the species occurring in the different eco-climatic habitats of the region and setting the priority of conservation concerns. However, the study encourages the various commercial sectors, such as pharmaceutical, nutraceutical, chemical, food, and cosmetics, to utilize unexplored species. In addition, the study suggests that prioritizing eco-climatic zones and elevation based on phytochemical diversity should be a factor of concern in the Himalayan region, especially under the climate change scenario. Nature Publishing Group UK 2023-07-05 /pmc/articles/PMC10322824/ /pubmed/37407604 http://dx.doi.org/10.1038/s41598-023-37495-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Tiwari, Deepti
Kewlani, Pushpa
Gaira, Kailash S.
Bhatt, Indra D.
Sundriyal, R. C.
Pande, Veena
Predicting phytochemical diversity of medicinal and aromatic plants (MAPs) across eco-climatic zones and elevation in Uttarakhand using Generalized Additive Model
title Predicting phytochemical diversity of medicinal and aromatic plants (MAPs) across eco-climatic zones and elevation in Uttarakhand using Generalized Additive Model
title_full Predicting phytochemical diversity of medicinal and aromatic plants (MAPs) across eco-climatic zones and elevation in Uttarakhand using Generalized Additive Model
title_fullStr Predicting phytochemical diversity of medicinal and aromatic plants (MAPs) across eco-climatic zones and elevation in Uttarakhand using Generalized Additive Model
title_full_unstemmed Predicting phytochemical diversity of medicinal and aromatic plants (MAPs) across eco-climatic zones and elevation in Uttarakhand using Generalized Additive Model
title_short Predicting phytochemical diversity of medicinal and aromatic plants (MAPs) across eco-climatic zones and elevation in Uttarakhand using Generalized Additive Model
title_sort predicting phytochemical diversity of medicinal and aromatic plants (maps) across eco-climatic zones and elevation in uttarakhand using generalized additive model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10322824/
https://www.ncbi.nlm.nih.gov/pubmed/37407604
http://dx.doi.org/10.1038/s41598-023-37495-1
work_keys_str_mv AT tiwarideepti predictingphytochemicaldiversityofmedicinalandaromaticplantsmapsacrossecoclimaticzonesandelevationinuttarakhandusinggeneralizedadditivemodel
AT kewlanipushpa predictingphytochemicaldiversityofmedicinalandaromaticplantsmapsacrossecoclimaticzonesandelevationinuttarakhandusinggeneralizedadditivemodel
AT gairakailashs predictingphytochemicaldiversityofmedicinalandaromaticplantsmapsacrossecoclimaticzonesandelevationinuttarakhandusinggeneralizedadditivemodel
AT bhattindrad predictingphytochemicaldiversityofmedicinalandaromaticplantsmapsacrossecoclimaticzonesandelevationinuttarakhandusinggeneralizedadditivemodel
AT sundriyalrc predictingphytochemicaldiversityofmedicinalandaromaticplantsmapsacrossecoclimaticzonesandelevationinuttarakhandusinggeneralizedadditivemodel
AT pandeveena predictingphytochemicaldiversityofmedicinalandaromaticplantsmapsacrossecoclimaticzonesandelevationinuttarakhandusinggeneralizedadditivemodel