Diversity analysis of maize inbred lines using DIVA-GIS under temperate ecologies
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Abstract
The vagaries of Climate Change variability need to be addressed and as climatic conditions change at particular experimental sites and maize producing regions, mega-environment assignments will need to be reassessed to guide breeders to appropriate new germplasm and target environments . The development of improved germplasm to meet the needs of future generations in light of climate change and population growth is of the upmost importance . Evaluation of the inbred lines from diverse ecosystems would be effective for production of lines with resilience towards climate variability. Hence, with this objective diverse set of inbred lines sourced from all over India were characterized and were evaluated with DIVA-GIS for diversity analysis of maize inbred lines. Grid maps generated for these maize inbred lines for eleven quantitative traits indicated that these lines can be sourced from North and South India. High Shannon diversity index with maximum range of 2.17-3.0, 2.25-3.0, 2.36-3.0, 2.4-4.0, 2.0-3.0, and 2.2-3.0 were recorded for the traits viz; plant height, ear height, grain weight, grain yield, kernel row and protein content respectively indicating the high response of these traits to ecosystem. However, inbred lines were found to be diverse for all the traits except for ears plant-1 (EPP) and they have been sourced from Northern and Southern parts of India while for EPP recorded less diversity index range of 0.4-1.0 indicating source from South India. Interestingly, less diverse inbred lines for all the eleven quantitative traits have been sourced from Indogangetic plains as indicated in diversity grid maps. Maximum diversity indices were recorded for anthesis silking interval (ASI), days to silking, days to tasseling, which are in the range of 0.97-2.0, 1.528-2.0, 1.516-2.0 and 1.528-
2.0 respectively. Hence, DIVA-GIS enabled identification of diverse sources from varied ecosystems which can be used for developing improved lines/ cultivars with greater resilience towards climate change.
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Diversity, DIVA-GIS, Grid maps, Maize, Shannon diversity index
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