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Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario

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Abstract

Assessing disease risk has become an important component in the development of climate change adaptation strategies. Here, the infection ability of leaf blast (Magnaporthe oryzae) was modeled based on the epidemiological parameters of minimum (T min), optimum (T opt), and maximum (T max) temperatures for sporulation and lesion development. An infection ability response curve was used to assess the impact of rising temperature on the disease. The simulated spatial pattern of the infection ability index (IAI) corresponded with observed leaf blast occurrence in Indo-Gangetic plains (IGP). The IAI for leaf blast is projected to increase during the winter season (December–March) in 2020 (2010–2039) and 2050 (2040–2069) climate scenarios due to temperature rise, particularly in lower latitudes. However, during monsoon season (July–October), the IAI is projected to remain unchanged or even reduce across the IGP. The results show that the response curve may be successfully used to assess the impact of climate change on leaf blast in rice. The model could be further extended with a crop model to assess yield loss.

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Acknowledgements

The authors are thankful to the Heads of the Division of Plant Pathology and Centre for Environment Science and Climate Resilient Agriculture, Joint Director (Research) and Director, ICAR–Indian Agricultural Research Institute, New Delhi for providing support. This work is a part of National Innovations on Climate Resilient Agriculture project.

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Correspondence to P. Sinha.

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Viswanath, K., Sinha, P., Naresh Kumar, S. et al. Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario. Climatic Change 142, 155–167 (2017). https://doi.org/10.1007/s10584-017-1942-z

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  • DOI: https://doi.org/10.1007/s10584-017-1942-z

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