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Title: PSEUDOMONAS SYRINGAE PV. SYRINGAE AND BACTERIAL BROWN SPOT OF SNAP BEAN: A STUDY OF EPIPHYTIC PHYTOPATHOGENIC BACTERIA AND ASSOCIATED DISEASE

Author
item HIRANO, SUSAN - UNIVERSITY OF WISCONSIN
item ROUSE, DOUGLAS - UNIVERSITY OF WISCONSIN
item CLAYTON, MURRAY - UNIVERSITY OF WISCONSIN
item Upper, Christen

Submitted to: Plant Disease
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/13/1995
Publication Date: N/A
Citation: N/A

Interpretive Summary: This manuscript reviews our findings with regard to the epidemiology of bacterial brown spot disease of snap bean, and the ecology of Pseudomonas syringae pv syringae (Pss), the bacterium that causes this disease. Although there is substantial variability in population sizes of Pss among populations of leaves, it is possible to model this variability. By combining the model of variability in population sizes with a model of the likelihood that a particular number of bacteria will cause disease, we found that numbers of Pss on leaves could be used to predict the amount of disease would develop. If numbers of bacteria on leaves determine the amount of disease that will follow, then the factors that determine the amount of bacterial growth on leaves are instrumental in determining the extent of ensuing epidemics. Growth of Pss on snap bean leaves appears to be the dominant processes in establishing population sizes sufficiently large that disease becomes likely. Intense rain triggers the onset of periods of bacterial growth. Thus rain triggered growth of the pathogen is one of the dominant factors in the epidemic of this disease. Properties of the bacteria that provide it the ability to multiply rapidly on bean leaves after intense rain are probably as important as pathogenesis in epidemics of bacterial brown spot disease of snap bean.

Technical Abstract: The role of epiphytic populations of Pseudomonas syringae pv syringae (Pss) in the epidemiology of bacterial brown spot of snap bean is reviewed. Numbers of Pss on different leaves within a bean canopy are highly variable. Bacterial populations on populations of leaves can be modeled with a lognormal. With this distribution, and by representing the probability that a given population size of bacteria will cause disease with the probit, bacterial population sizes can be used to predict the amount of disease that is likely to occur. Spatial variability of bacterial brown spot disease, or of population sizes of Pss can also be modeled. Because disease is quantitatively related to bacterial population sizes, the processes that determine bacterial population sizes are key to the epidemiology of bacterial brownspot disease. The dominant process is growth of bacteria, apparently on healthy leaves. Such growth is very rapid (sometimes 100- to 1000-fold in 24 hours) and appears to be triggere by intense rain. Thus, processes other than pathogenesis may be extremely important in development of epidemics of bacterial brown spot disease.