Prediction of stem rust infection favorability, by means of degree-hour wetness duration, for perennial ryegrass seed crops

• Published in: Phytopathology 2003-04, Vol.93 (4), p.467-477
• Main Author: Pfender, W.F
• Format: Article
• Language: English
• Subjects: Agronomy. Soil science and plant productions; Biological and medical sciences; climatic factors; disease advisory systems; disease models; diurnal variation; Fundamental and applied biological sciences. Psychology; Fungal plant pathogens; fungal spores; Genetics and breeding of economic plants; infection; inoculum density; Lolium perenne; pathogenicity; Pathology, epidemiology, host-fungus relationships. Damages, economic importance; Pest resistance; Phytopathology. Animal pests. Plant and forest protection; plant pathogenic fungi; Plant pathogens; prediction; Puccinia graminis; relative humidity; rust diseases; seeds; spore germination; temperature; Varietal selection. Specialized plant breeding, plant breeding aims
• ISSN: 0031-949X; 1943-7684
• DOI: 10.1094/PHYTO.2003.93.4.467

A weather-based infection model for stem rust of perennial ryegrass seed crops was developed and tested using data from inoculated bioassay plants in a field environment with monitored weather. The model describes favorability of daily weather as a proportion (0.0 to 1.0) of the maximum possible infection level set by host and inoculum. Moisture duration and temperature are combined in one factor as wet degree-hours (DH(w)) (i.e., degree-hours > 2.0°C summed only over time intervals when) moisture is present). Degree-hours are weighted as a function of temperature, based on observed rates of urediniospore germination. 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 both periods are included in the model. There is a correction factor for reduced favorability if the dark wet period is interrupted. The model is: proportion of maximum infection = 1 - e((-0.0031) x (DHw Index)), where DH(w) Index is the product of interruption-adjusted overnight weighted DH(w) multiplied by morning (first 2 h after sunrise) weighted DH(w). The model can be run easily with measurements from automated dataloggers that record temperature and wetness readings at frequent time intervals. In tests with three independent data sets, the model accounted for 80% of the variance in log(observed infection level) across three orders of magnitude, and the regression lines for predicted and observed values were not significantly different from log(observed) = log(predicted). A simpler version of the model using nonweighted degree hours (>2.0°C) was developed and tested. It performed nearly as well as the weighted-degree-hour model under conditions when temperatures from sunset to 2 h past sunrise were mostly between 4 and 20°C, as is the case during the growing season in the major U.S. production region for cool-season grass seed. The infection model is intended for use in combination with measured or modeled estimates of inoculum level, to derive estimates of daily infection.