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An Apple Powdery Mildew Model Based on Plant Growth, Primary Inoculum, and Fungicide Concentration. N. Lalancette, Graduate research assistant, Department of Plant Pathology, The Pennsylvania State University, Fruit Research Laboratory, Biglerville 17307, Present address: postdoctoral research associate, Department of Plant Pathology, The Ohio State University, Ohio Agricultural Research and Development Center, Wooster 44691; K. D. Hickey, professor, Department of Plant Pathology, The Pennsylvania State University, Fruit Research Laboratory, Biglerville 17307. Phytopathology 76:1176-1182. Accepted for publication 30 January 1986. Copyright 1986 The American Phytopathological Society. DOI: 10.1094/Phyto-76-1176.

In 1981, 1982, and 1983 Rome Beauty apple trees with different amounts of primary mildew were sprayed with various concentrations of the fungicide bitertanol. The number of leaves and proportion of infected leaves per shoot were determined periodically throughout each growing season. Plant growth and disease progress curves were then constructed for each treatment combination of primary mildew and bitertanol concentration. Trees with higher levels of primary mildew were observed to have greater rates of disease progression and higher carrying capacities for disease. Conversely, those trees receiving higher fungicide concentrations had lower rates and carrying capacities. When disease incidence was modeled as a function of shoot growth, the best fit was obtained by substituting a linear function of primary mildew and fungicide concentration for the disease carrying-capacity parameter. Because disease was dependent on the production of young tissue, the end of the epidemics occurred when plant growth approached its carrying capacity. Under these circumstances, the model was reduced from four to three parameters: The final amount of disease was expressed as a function of primary mildew and fungicide concentration. Thus, given estimates of the amount of primary mildew, the concentration of fungicide necessary to manage secondary mildew at a desired level can be predicted. Although this model provides a method for optimizing fungicide use, additional factors need to be considered to augment its accuracy and capability.