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Vol. 10, Issue 6 (2021)

Insight of rice disease forecasting models

Author(s):
Moin Kabir, Meenakshi Rana and Ankita Roy
Abstract:
Rice endures from several fungal and bacterial diseases in India. A tremendous amount of yield loss takes place due to the attack of pathogens on rice. For secure management relying on the environment and pathogen relation, multiple forecasting models have been developed Seens many years ago, rice diseases rice blast, rice sheath blight, rice leaf spot, EPIBLAST, BLASTL, EPIRICE, BLIGHTASIRRI, some forecasting model build upon calculation from the vertical and horizontal measurement which sustain temperature combination, relative humidity, sclerotia present, and tiller. Other models are calculated on temperature, dew period, meteorological input variables, sporulation, inoculum potential, conidia release, penetration, incubation period, etc. Blast regarding meteorological study progressed at the central rice research institute. Obtained data have shown that the application of fertilizer based on forecasting of disease helps in effecting control of infection. The determining model conceded that 52 studies have been recorded. The best consistent input variable is air temperature, persist by rainfall and relative humidity.
Pages: 1060-1069  |  834 Views  512 Downloads


The Pharma Innovation Journal
How to cite this article:
Moin Kabir, Meenakshi Rana, Ankita Roy. Insight of rice disease forecasting models. Pharma Innovation 2021;10(6):1060-1069.

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