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A Model to Estimate Disease on Cereal Leaves at Different Positions from Whole Plant Severity Data. K. V. Subbarao, Department of Plant Pathology, University of California, Berkeley, Kearney Agricultural Center, 9240 S. Riverbend Ave., Parlier 93648; X. B. Yang(2), and J. P. Snow(3). (2)Department of Plant Pathology, University of Arkansas, 217 Plant Sciences Building, Fayetteville 72701; (3)Department of Plant Pathology and Crop Physiology, Louisiana Agricultural Experiment Station, Louisiana State University Agricultural Center, Baton Rouge 70803. Phytopathology 82:184-190. Accepted for publication 26 September 1991. Copyright 1992 The American Phytopathological Society. DOI: 10.1094/Phyto-82-184.

A model to estimate wheat leaf rust severity at different positions from the tiller/whole plant rust severity values and disease progress curves was developed. Development of leaf rust on the ith leaf was expressed as dxit/dt = rXt(1 xit) or, in an integrated form, xit = 1 exp[rXt (t ti)], where xit is the rust severity on the ith leaf at time t, r is the tiller/plant apparent infection rate, Xt is the tiller/plant rust severity observed at time t, and ti is the time of the ith leaf emergence. Leaf rust severity data were collected on individual leaves on 10 randomly selected tillers in sequentially inoculated plots and in plots of naturally occurring epidemics of wheat cultivar McNair 1003 during the 198687 and 198788 wheat-growing seasons. These data were used to study the relationship between rust on leaves at different positions and mean rust severity per tiller/plant, as well as to evaluate the performance of the above model. The equation predicted leaf rust severity on individual leaves from the whole plant rust severity, and the predicted severities correlated very well with the observed severity (r = 0.850.99). The severity of leaf rust on flag (F) and F-1 leaves was lower than on F-2 and F-3 leaves. The slopes between any two successive points on the disease progress curves for individual leaves were significantly different from each other, indicating the influence of the amount of inoculum available for different leaf layers and the time of leaf emergence.

Additional keywords: Crop model, model coupling, Puccinia recondita f. sp. tritici, quantitative epidemiology, simulation.