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

Author

Listed:
  • K. Viswanath

    (ICAR–Indian Agricultural Research Institute
    RARS, ANGRAU)

  • P. Sinha

    (ICAR–Indian Agricultural Research Institute)

  • S. Naresh Kumar

    (ICAR–Indian Agricultural Research Institute)

  • Taru Sharma

    (ICAR–Indian Agricultural Research Institute)

  • Shalini Saxena

    (ICAR–Indian Agricultural Research Institute)

  • Shweta Panjwani

    (ICAR–Indian Agricultural Research Institute)

  • H. Pathak

    (ICAR–Indian Agricultural Research Institute)

  • Shalu Mishra Shukla

    (ICAR–Indian Agricultural Research Institute)

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.

Suggested Citation

  • K. Viswanath & P. Sinha & S. Naresh Kumar & Taru Sharma & Shalini Saxena & Shweta Panjwani & H. Pathak & Shalu Mishra Shukla, 2017. "Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario," Climatic Change, Springer, vol. 142(1), pages 155-167, May.
  • Handle: RePEc:spr:climat:v:142:y:2017:i:1:d:10.1007_s10584-017-1942-z
    DOI: 10.1007/s10584-017-1942-z
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    References listed on IDEAS

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    1. Aggarwal, P.K. & Banerjee, B. & Daryaei, M.G. & Bhatia, A. & Bala, A. & Rani, S. & Chander, S. & Pathak, H. & Kalra, N., 2006. "InfoCrop: A dynamic simulation model for the assessment of crop yields, losses due to pests, and environmental impact of agro-ecosystems in tropical environments. II. Performance of the model," Agricultural Systems, Elsevier, vol. 89(1), pages 47-67, July.
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    5. Aggarwal, P.K. & Kalra, N. & Chander, S. & Pathak, H., 2006. "InfoCrop: A dynamic simulation model for the assessment of crop yields, losses due to pests, and environmental impact of agro-ecosystems in tropical environments. I. Model description," Agricultural Systems, Elsevier, vol. 89(1), pages 1-25, July.
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    Cited by:

    1. Kyoung-Tae Lee & Hye-Won Jeon & Sook-Young Park & Jaepil Cho & Kwang-Hyung Kim, 2022. "Comparison of projected rice blast epidemics in the Korean Peninsula between the CMIP5 and CMIP6 scenarios," Climatic Change, Springer, vol. 173(1), pages 1-20, July.
    2. Maria Lodovica Gullino & Ramon Albajes & Ibrahim Al-Jboory & Francislene Angelotti & Subrata Chakraborty & Karen A. Garrett & Brett Phillip Hurley & Peter Juroszek & Ralf Lopian & Khaled Makkouk & Xub, 2022. "Climate Change and Pathways Used by Pests as Challenges to Plant Health in Agriculture and Forestry," Sustainability, MDPI, vol. 14(19), pages 1-22, September.
    3. Wang, Hui & Mongiano, Gabriele & Fanchini, Davide & Titone, Patrizia & Tamborini, Luigi & Bregaglio, Simone, 2021. "Varietal susceptibility overcomes climate change effects on the future trends of rice blast disease in Northern Italy," Agricultural Systems, Elsevier, vol. 193(C).

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