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.
Diversity, DIVA-GIS, Grid maps, Maize, Shannon diversity index
Babu, A.V., Kamala, N., Sivaraj, N., Sunil, N., Pandravada, S. R., Vanaja, M. and Varaprasad, K.S. (2010). DIVAGIS approaches for diversity assessment of pod characteristics in black gram (Vigna mungo L. Hepper). Current Sci., 98(5): 616-619.
Cairns, J.E., Sonder, K., Zaidi, P.H., Verhulst, P.N., Mahuku, G., Babu, R., Nair, S.K., Das, B., Govaerts, B., Vinayan, M.T., Rashid, Z., Noor, J.J., Devi, P., Vicente, F. san, and Prasanna, B.M. (2012). Maize production in a changing climate: Impacts, adaptation, and mitigation strategies. Advances in Agronomy 114: 1-65.
Cairns, J.E., Hellin, J., Sonder, K., Araus, J.L., MacRobert, J.F., Thierfelder, C., and Prasanna, B.M. (2013). Adapting maize production to climate change in sub-Saharan Africa. Food Security 5(3): 345â€“360.
Easterling, W., Aggarwal, P., Batima, P., Brander, K., Erda, L., Howden, M., Kirilenko, A., Morton, J., Soussana, J.F., Schmidhuber, J. and Tubiello, F. (2007). Food Fibre and Forest Products. In Climate Change 2007: Impacts, Adaptation and Vulnerability (Oarry, M.L., Canziani, O.F., Palutikof, J.P., Van der Lindin, P.J., and Hanson, C.E. Eds.). pp 273â€313, Cambridge University Press, Cambridge, UK.
Hijmans, R.J., Garret, K.A., Huaman, Z., Zhang, D.P., Schreuder, M. and Bonierbale. (2000). Assessing the geographic representatives of genebank collections:the case of Bolivian wild potatoes. Conservation Biology 14: 1755-1765.
Hijmans, R.J, Guarino, Cruz, M. and Rojas, E. (2001). Computer tools for spatial analysis of plant genetic resources data. Plant Genetic Resources Newsletter 127: 15-19.
Hallauer, A.R., Russell, W.A. and Lamkey, K.R. (1988). Corn Breeding. In: Corn and Corn Improvement, 3rd edn. Agron Monogr 18, ASA-CSSA-SSSA, Madison, Wisconsin, USA. pp. 469-564.
Hijmans, Robert, J., Mirjam, J., John, B., Bamberg, and David, M.S. (2003). Frost tolerance in wild potato species: Assessing the predictivity of taxonomic, geographic, and ecological factors. Euphytica 130: 47-59.
Howden, S.M., Soussana, J.F., Tubiello, F.N., Chhetri, N., Dunlop, M., and Meinke, H. (2007). Adapting agriculture to climate change. Proceedings of the National Academy of Sciences 104(50): 19691-19696.
Jambrovic, A., Simic, D., Leden, T., Zdunic, Z. and Brkic, I. (2008). Genetic diversity among maize (Zea mays L.) inbred lines in Eastern Croatia. Periodicum Biologorum 110 (3): 251-255.
Jones, P.G., Beebe, S.E., Tohme, J. and Galway, N.W. (1997). The use of geographical information systems in biodiversity exploration and conservation. Biodiversity and Conservation 6: 947-958.
Kamala, V., Gupta, A.J., Sivaraj, N., Pandravada, S.R., Sunil, N., Varaprasad, K.S and Lawande, K.E. (2011). Diversity analysis of onion germplasm collections from north Telangana region of Andhra Pradesh. Indian J. Plant Genet. Resour. 24(2): 163-171.
Li, Y., Du, J., Wang, T., Shi, Y., Song, Y. and Jia, J. (2002). Genetic diversity and relationships among Chinese maize inbred lines revealed by SSR markers. Maydica 47: 93-101.
Liu, K., Goodman, M., Muse, S., Smith, J.S., Buckler, Ed. and Doebley, J. (2003). Genetic structure and diversity among maize inbred lines as inferred from DNA microsatellites. Genetics 165: 2117-2128.
Prasanna, B.M. (2012). Diversity in global maize germplasm: Characterization and utilization. Journal of Biosciences 37(5): 843-855.
Sivaraj, N., Sunil, N., Pandravada, S.R., Kamala, V., Vinod, K., Rao, B.V.S.K, Prasad, R.B.N. and Varaprasad, K.S. (2009). DIVA-GIS approaches for diversity assessment of fatty acid composition in linseed (Linum usitatissimum L.) germplasm collections from peninsular India. Journal of Oilseeds Research. 26: 13-15.
Sivaraj, N., Sunil, N., Pandravada, S.R., Kamala, V., Rao, B.V.S.K., Prasad, R.B.N., Nayar, E.R., Joseph, John, K., Abraham, Z. and Varaprasad, K.S. (2010). Fatty acid composition in seeds of Jack bean [Canavalia ensiformis (L.) DC] and Sword bean [Canavalia gladiata Jacq.) DC] germplasm from South India: A DIVA-GIS analysis. Seed Technology 32(1): 46-53.
Sivaraj, N., Sunil, N., Pandravada, S.R., Kamala, V., Vinod, K, Babu, A., Rao, B.V.S.K., Prasad, R.B.N. and Varaprasad, K.S. (2012). Variability in linseed (Linum usitatissimum) germplasm collections from peninsular India with special reference to seed traits and fatty acid composition. Indian Journal of Agricultural Sciences 82 (2): 102-105.
Sunil, N., Sivaraj, N., Pandravada, S.R., Kamala, V., Raghuram, R.P. and Varaprasad, K.S. (2008). Genetic and geographical divergence in horsegram germplasm from Andhra Pradesh, India. Plant Genetic Resources: Characterization and Utilization 7(1): 84-87.
Sunil, N., Sivaraj, N., Anitha, K., Babu, A., Vinod, K.E., Sudhir, M., Vanaja and Varaprasad, K.S. (2009). Analysis of diversity and distribution of Jatropha curcas L. germplasm using Geographic Information System (DIVA-GIS). Genetic Resources and Crop Evolution 56: 115-119.
Tao, F. and Zhang, Z. (2010). Adaptation of maize production to climate change in North China Plain: Quantify the relative contributions of adaptation options. European Journal of Agronomy 33(2): 103-116.
Tao, F. and Zhang, Z. (2011). Impacts of climate change as a function of global mean temperature: maize productivity and water use in China. Climate Change 105(3/5): 409-432.
Varaprasad, K.S, Sivaraj, N., Mohd, I. and Pareek, S.K. (2007). GIS mapping of selected medicinal plants diversity in the Southeast Coastal Zone for effective collection and conservation. In: Advances in Medicinal Plants (eds. K. Janardhan Reddy, Bir Bahadur, B. Bhadraiah and MLN Rao). Universities Press (India) Private Ltd. pp.69-78.
Varaprasad, K.S., Sivaraj, N., Pandravada, S.R., Kamala, V. and Sunil, N. (2008). GIS mapping of Agrobiodiversity in Andhra Pradesh. Proceedings of Andhra Pradesh Akademi of Sciences. Special Issue on Plant wealth of Andhra Pradesh. pp: 24-33.
Yadav, V.K. and Singh, I.S. (2010). Comparative evaluation of maize inbred lines (Zea mays L.) according to DUS testing using morphological, physiological and molecular markers. Agricultural Sciences 1(3): 131-142.
This work is licensed under Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) © Author (s)