A predictive model of disease progression of red-pepper anthracnose
1988
Kim, C.H. | Park, K.S. (Rural Development Administration, Suwon (Korea R.). Agricultural Sciences Institute)
A model to forecast disease progress of red-pepper anthracnose after initial occurrence was written based on key climatic variable in three years field experiments. Anthracnose incidence, ambient air temperature, relative humidity (RH) and rainfall were monitored continuously for weather factor or 3-10 day intervals for disease incidence from early July to early September. Logistic disease proportion (LDP) of anthracnose regressed to cumulative portion of temperature (CPT) over 25C in daily maximum temperature, cumulative RH portion (CRH) over 80 % in daily average RH and cumulative frequency of rainfall (CFR) to select prediction variables. CRH and CFR predicted LDP with R2 of 0.8512 and 0.7564, respectively. Poor prediction was achieved from the equation between in [x/(1-x)] and CPT, where x is disease proportion. Any combinations of above two or three variables failed to improve prediction accuracy appreciably because of existence of intercorrelation, particularly between CRH and CFR. Since CRH was more significant for disease prediction, model was written using CRH as x = exp(b1 CRH + b0) [1 + exp(b1 CRH + b0)]** (-1) where b1 = 0.045 and b0 = - 7.54.: Hence, disease proportion could be directly estimated based on relative humidity
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