A Simulation Model for Assessing Soybean Rust Epidemics

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Abstract
A soybean rust (causal agent Phakopsora pachyrhizt) simulation model was developed for assessing disease epidemics as a part of pest risk analysis. Equations describing environmental effects on disease components were developed by re‐analyzing previous data with a view toward a systems approach. The infection rate was predicted well using dew period and temperature after inoculation as independent variables (R2=0.88, P < 0.0001). The exponential models which used physiological day as an independent variable explained 98% of the variations of latent period and senescence of disease lesions. The simulation model was validated with data from 72 sequential planting experiments during 1980 and 1981 in Taiwan. Time of onset for these epidemics varied from 25—60 days and 50—80 days after planting soybean cultivars TK 5 and G 8587, respectively. The epidemic periods were 75—95 for TK 5 and 100—120 days for G 8587. Variation of epidemics was accurately predicted by the simulator. Predicted disease curves fit well the observed disease curves for the recognized cropping seasons, spring‐ and autumn‐seeded crops. For G 8587, which is very sensitive to photoperiod, the data from spring and autumn gave a better fit compared with data from pre‐summer planting. The model underestimated disease epidemics during the winter, probably because the plant growth model failed to reflect the photoperiod rection of soybean. The simulation model was validated with data from other experiments conducted in three cropping seasons in 1979 and 1980. Determination coefficients of the regression between observed and predicted disease severity were significant.