Forecasting model for disease risk period in chickpea x collar rot pathosystem
Keywords:Collar rot, Chickpea, Forecasting model, Soil moisture, Soil temperature
Collar rot caused by Sclerotium rolfsii Sacc. is one of the major biotic constraints of chickpea production worldwide. It is soil-borne fungi having wider host range and infection mainly occurs at the juvenile stage of crop growth resulting crop failure in no time. The pathogen is greatly influenced by soil temperature (ST) and soil moisture (SM) therefore, experiment formulated to develop a suitable forecasting model for its future use in computer simulation of plant disease prognostication by feeding only soil temperature and moisture data. The popular desi type chickpea variety Anuradha sown at different dates to get a range of soil temperature and soil moisture combination and its corresponding effect on disease incidence was recorded under natural epiphytotic conditions. The data obtained were analyzed using binary logistic regression and discriminant analysis to assess disease risk and non-risk period. The model developed was Y'= -73.9 + 1.251 SM + 0.017 ST. The outcome recorded, a unique statistically significant contribution of soil moisture (p value=0.029) on the establishment of the disease whereas, the effect of soil temperature was detected as statistically non-significant. The model developed and the correctness of the model determined to predict the disease severity with 80 % accuracy.
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Copyright (c) 2022 SANJU TAMANG , POLY SAHA
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