Date of Award
Doctor of Philosophy
Plant Pathology and Microbiology
D. C. McGee
Weather and disease data collected in Iowa during the 1987 and 1988 growing seasons, were used to develop a seed infection model to predict Phomopsis seed decay in soybean seeds. This model incorporates into a regression equation values of pod inoculum levels at R6 growth stage (full pod), the number of consecutive days with rain during growth stages R7 to R8 (physiological maturity) and with the average and maximum daily temperatures for consecutive wet days during that same period. The model was tested for its ability to predict infection levels of Phomopsis seed decay in the harvested seeds above or below 15%, which has been defined as a desirable goal to limit seed infection. The predictive ability of the model was compared to the predicted values obtained with the Iowa pod test predictive method. The selected model has been named CYPOD and has the following equation: % seed infection = 2.806 + 0.267*POD - 0.013*POD*TDIFF + 0.051*POD*MOIST where POD = level of infection with P. longicolla Hobbs on the pods at R6 growth stage: TDIFF = temperature difference between average minimum and average maximum daily temperatures for consecutive wet days during growth stages R7 to R8; MOIST = coded number of consecutive days with precipitation from growth stages R7 to R8;Results from this study clearly indicate that the predictive ability of the Iowa pod test greatly improved when weather data is considered in making the prediction. To use this method, a pod test should be performed during R6 growth stage to determine pod inoculum levels. The weather data to be used in the equation are obtained through short term (1 to 5 days) weather forecasts as reported by weather stations for the area.
Digital Repository @ Iowa State University, http://lib.dr.iastate.edu/
Carmen Martorell Milla
Milla, Carmen Martorell, "A quantitative model for prediction of Phomopsis seed decay of soybeans " (1989). Retrospective Theses and Dissertations. 9157.