Author
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Pfender, William |
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Submitted to: Phytopathology
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 11/15/2002 Publication Date: 9/30/2003 Citation: Pfender, W.F. Prediction of Stem Rust Infection Favorability, by Means of Degree-Hour Wetness Duration, for Perennial Ryegrass Seed Crops. Phytopathology. v. 93. p. 467-477. Interpretive Summary: A simple mathematical model based on weather conditions was developed for stem rust of perennial ryegrass seed crops. The model describes favorability for infection under the assumption of abundant inoculum availability. Moisture duration and temperature are combined in one factor as 'wet degree-hours' (DH), that is, thermal units > 1.5 C summed only over time intervals when moisture is present. The pathogen, Puccinia graminis subsp. graminicola, requires favorable conditions of temperature and moisture during the night (dark period) and also at the beginning of the morning (light period), and thus both periods are modeled. The model is a form of the Richards equation, with the log- transformed infection severity related to the product of post-sunrise DH and the square root of nighttime DHw. There is a correction factor for reduced favorability if the night wet period is interrupted. The model can be run easily with measurements from automated dataloggers that record temperature and wetness readings at frequent time intervals. This model for infection will be useful, in combination with additional models for inoculum availability and other disease cycle components, in a comprehensive epidemic model for managing stem rust in grass seed crops. Technical Abstract: Stem rust is a very severe disease of grasses that can destroy a crop grown for seed. To better manage the disease, information is needed about how weather conditions affect the amount of infection that can occur. In this paper, a simple mathematical description for the effect of weather on stem rust infection was developed using data from field experiments in which automated weather monitoring equipment was used. The duration of moisture on leaves and the temperature are combined in one factor as 'wet degree-hours'. The pathogen, Puccinia graminis subsp. graminicola, requires favorable conditions of temperature and moisture during the night (dark period) and also at the beginning of the morning (light period), and thus both periods are included in the mathematical model. The model can be run easily with measurements from automated dataloggers that record temperature and wetness readings at frequent time intervals. It accurately predicted the amount of infection, from a standardized spore load, in two growing seasons. This model for infection will be useful, in combination with additional component models for spore availability and other disease cycle components, in a future overall epidemic model for managing stem rust in grass seed crops. |
