Vol. 7, Issue 6 (2019)
Rice blast modeling and forecasting
Author(s): Omkar Singh, Jagadeesh Bathula and DK Singh
Abstract: Rice (Oryza sativa) is a major food crop, on which two-third of the world population subsists wholly or partially. Several pests and diseases affect the rice crop round the year. Rice blast is one of the major diseases of rice crop which causes 40-70 percent yield loss. It is caused by a fungal pathogen, Pyricularia oryzae (telemorph, Magnaporthe grisea). Several environmental factors are known to influence sporulation and spore dissemination. Temperature between 19-29 ËšC, particularly in the range of 23-26Ëš C, and more than 16 hr of relative humidity above 90 percent are considered to be highly favorable conditions for blast development. Simulation studies using data from tropical and subtropical areas have shown that temperature changes may bring about years that are blast conducive. Forecasting techniques could be used to identify that which years are conducive and whether fungicide application would be cost-effective or risky under those conditions. Rice farmers in most developing countries demand immediate results once disease problems are encountered. For this reason, fungicides are still the preferred control measures against diseases like blast and to counter this, better forecasting schemes for tropical conditions are solely needed. Several rice blast forecasting models have been developed for the prediction of rice blast disease, out of which computer-based prediction models are most important. EPIBLA, BLASTAM, BLASTL, and EPIBLAST are the computerized forecasting systems which has been developed to simulate the incidence and progress of rice blast in the field. A computer-based simulation model was also developed in Kangra district of Himachal Pradesh in 1999 for the prediction of rice blast. Many of the control practices useful in reducing plant diseases are of limited use to control rice blast. Since blast is present in most rice growing areas, and it has such a wide host range, eradication and crop rotation are of little value. Method and rate of nitrogen application highly influence the disease development. Chemicals such as Probenazole, Tricyclazole, Propiconazole, Azoxystrobin and Isoprothiolane were found to be effective against rice blast disease, forecasted weather products and area wise weather networks are becoming prevalent. The use of predictive models can help growers to manage disease in their crops which will increasingly be a part of an overall IPM program.
Pages: 2788-2799 | 528 Views 314 Downloads
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How to cite this article:
Omkar Singh, Jagadeesh Bathula, DK Singh. Rice blast modeling and forecasting. Int J Chem Stud 2019;7(6):2788-2799.
