Cargando…

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...

Descripción completa

Detalles Bibliográficos
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
Descripción
Sumario: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.