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Characterizing the Potato Growing Regions in India Using Meteorological Parameters

Currently, the multi-location testing of advanced hybrids in India is carried out at 25 centers under the All India Co-ordinated Research Project on Potato (AICRP-P), which is spread across the country. These centres have been chosen to represent different potato growing regions based on soil and ag...

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Autores principales: Bhardwaj, Vinay, Rawat, Shashi, Tiwari, Jagesh, Sood, Salej, Dua, Vijay Kumar, Singh, Baljeet, Lal, Mehi, Mangal, Vikas, Govindakrishnan, PM
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605082/
https://www.ncbi.nlm.nih.gov/pubmed/36295054
http://dx.doi.org/10.3390/life12101619
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author Bhardwaj, Vinay
Rawat, Shashi
Tiwari, Jagesh
Sood, Salej
Dua, Vijay Kumar
Singh, Baljeet
Lal, Mehi
Mangal, Vikas
Govindakrishnan, PM
author_facet Bhardwaj, Vinay
Rawat, Shashi
Tiwari, Jagesh
Sood, Salej
Dua, Vijay Kumar
Singh, Baljeet
Lal, Mehi
Mangal, Vikas
Govindakrishnan, PM
author_sort Bhardwaj, Vinay
collection PubMed
description Currently, the multi-location testing of advanced hybrids in India is carried out at 25 centers under the All India Co-ordinated Research Project on Potato (AICRP-P), which is spread across the country. These centres have been chosen to represent different potato growing regions based on soil and agronomic features. However, the reliable deployment of the newly bred varieties in different regions requires a scientific delineation of potato growing zones with homogenous climates. The present study was undertaken to develop homogenous zones in the Indian sub-continent based on the environmental parameters of the potato growing season. A total of 1253 locations were identified across the country as having a plausible potato growing season of at least 70 days with suitable thermal limits. Six variables including five meteorological parameters including Physiological days (P days), Growing degree days (GDD), Mean daily temperature, Mean night temperature and Mean daily incident solar radiation, together with altitude as the sixth variable, were used for Agglomerative Hierarchical Clustering (AHC) and the Principal Component Analysis by Multidimensional Scaling (MDS) technique to derive identical classes. The thematic map of the classes was overlaid on potato growing districts of India using ArcGIS 9.1 software. The study clearly depicted that the clustering technique can effectively delineate the target population of environments (TPE) for potato genotypes performing well at different testing environments in India. The study also identifies target locations for future focus on breeding strategies, especially the high night temperature class having a large expanse in India. This is also vital in view of the impending climate change situation.
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spelling pubmed-96050822022-10-27 Characterizing the Potato Growing Regions in India Using Meteorological Parameters Bhardwaj, Vinay Rawat, Shashi Tiwari, Jagesh Sood, Salej Dua, Vijay Kumar Singh, Baljeet Lal, Mehi Mangal, Vikas Govindakrishnan, PM Life (Basel) Article Currently, the multi-location testing of advanced hybrids in India is carried out at 25 centers under the All India Co-ordinated Research Project on Potato (AICRP-P), which is spread across the country. These centres have been chosen to represent different potato growing regions based on soil and agronomic features. However, the reliable deployment of the newly bred varieties in different regions requires a scientific delineation of potato growing zones with homogenous climates. The present study was undertaken to develop homogenous zones in the Indian sub-continent based on the environmental parameters of the potato growing season. A total of 1253 locations were identified across the country as having a plausible potato growing season of at least 70 days with suitable thermal limits. Six variables including five meteorological parameters including Physiological days (P days), Growing degree days (GDD), Mean daily temperature, Mean night temperature and Mean daily incident solar radiation, together with altitude as the sixth variable, were used for Agglomerative Hierarchical Clustering (AHC) and the Principal Component Analysis by Multidimensional Scaling (MDS) technique to derive identical classes. The thematic map of the classes was overlaid on potato growing districts of India using ArcGIS 9.1 software. The study clearly depicted that the clustering technique can effectively delineate the target population of environments (TPE) for potato genotypes performing well at different testing environments in India. The study also identifies target locations for future focus on breeding strategies, especially the high night temperature class having a large expanse in India. This is also vital in view of the impending climate change situation. MDPI 2022-10-17 /pmc/articles/PMC9605082/ /pubmed/36295054 http://dx.doi.org/10.3390/life12101619 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bhardwaj, Vinay
Rawat, Shashi
Tiwari, Jagesh
Sood, Salej
Dua, Vijay Kumar
Singh, Baljeet
Lal, Mehi
Mangal, Vikas
Govindakrishnan, PM
Characterizing the Potato Growing Regions in India Using Meteorological Parameters
title Characterizing the Potato Growing Regions in India Using Meteorological Parameters
title_full Characterizing the Potato Growing Regions in India Using Meteorological Parameters
title_fullStr Characterizing the Potato Growing Regions in India Using Meteorological Parameters
title_full_unstemmed Characterizing the Potato Growing Regions in India Using Meteorological Parameters
title_short Characterizing the Potato Growing Regions in India Using Meteorological Parameters
title_sort characterizing the potato growing regions in india using meteorological parameters
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605082/
https://www.ncbi.nlm.nih.gov/pubmed/36295054
http://dx.doi.org/10.3390/life12101619
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