VIEW ARTICLE

Ecology and Epidemiology

Analysis of Disease Progress Curves, Gradients, and Incidence-Severity Relationships for Field and Phytotron Bean Rust Epidemics. M. W. Imhoff, Graduate research assistant, U.S. Department of Agriculture, SEA, AR, North Carolina State University, Raleigh 27650; K. J. Leonard(2), and C. E. Main(3). (2)Plant pathologist, U.S. Department of Agriculture, SEA, AR, North Carolina State University, Raleigh 27650; (3)Professor, Department of Plant Pathology, North Carolina State University, Raleigh 27650. Phytopathology 72:72-80. Accepted for publication 5 May 1981. This article is in the public domain and not copyrightable. It may be freely reprinted with customary crediting of the source. The American Phytopathological Society, 1982. DOI: 10.1094/Phyto-72-72.

Six bean rust field epidemics in 1979 and 1980 were monitored for disease severity, disease incidence, hourly temperature, hourly leaf wetness, leaf area per plant, and number of leaves per plant. These epidemics were initiated by artificially inoculating 1.83 × 1.83-m areas at the centers of 44 × 44-m plots of Phaseolus vulgaris ‘Bountiful’ with race 34 of Uromyces phaseoli var. typica. Disease gradient patterns over time were unique to each epidemic and reflected the pattern of the disease progress curves for the central inoculated area. Disease progress curves appeared to depend more on the frequency and length of wetting period than on temperature. Incidence vs severity relationships differed for each epidemic and were too variable within an individual epidemic to be of practical use for estimating disease severity from disease incidence data. Under controlled phytotron conditions, five epidemics under different environmental regimes, initial inoculum levels, and inoculation dates produced similar-shaped disease progress curves that varied in time displacement. Incidence vs severity relationships reflected the rate of the epidemic, the time of disease onset, and the rate of host growth. These field and phytotron epidemics can serve as verification tools for future disease simulator development.