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Effect of Temperature on Sporulation and Infectivity of Podosphaera macularis on Humulus lupulus

March 2009 , Volume 93 , Number  3
Pages  281 - 286

Amy B. Peetz, Oregon State University, Department of Botany and Plant Pathology, Corvallis, OR 97331; Walter F. Mahaffee, U.S. Department of Agriculture-Agricultural Research Service, Horticultural Crops Research Laboratory, and Oregon State University, Department of Botany and Plant Pathology, Corvallis, OR 97331; David H. Gent, U.S. Department of Agriculture-Agricultural Research Service, Forage Seed and Cereal Research Unit, and Oregon State University, Department of Botany and Plant Pathology, Corvallis, OR 97331



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Accepted for publication 25 November 2008.
ABSTRACT

Hop powdery mildew, caused by Podosphaera macularis, can result in complete crop loss and requires numerous fungicide applications for effective management. To assess the impact of temperature on the production of infective conidia, 10-day-old sporulating colonies were exposed to 18, 30, 33, 36, 39, and 42°C for 6 h, and then incubated at 18°C for 18 h. Conidia were harvested, inoculated onto hop plants, incubated at 18°C for 10 days, and then lesions/cm2 of leaf area was determined. Disease was significantly reduced at temperatures ≥30°C with a nonlinear response in the production of infective conidia (P < 0.0001). Temperature effects on sporulation of P. macularis were examined using a custom impaction conidia sampler in growth chambers programmed at constant temperatures of 5, 10, 15, 20, 25, 30, and 35°C, or 18°C before and after ramping to 18, 22, 26, 30, 34, and 38°C for 6 h. The effect of constant temperature on sporulation was best described by a nonlinear thermodynamic model (P = 0.0001) with maximal production near 25°C. Exposure to fluctuating temperatures produced a curvilinear response in sporulation (P = 0.0122) with maximum production near 25°C. These data indicate that inoculum availability is reduced when ambient temperature exceeds 30°C and that modeling inoculum availability could help further refine current disease forecasting models.



The American Phytopathological Society, 2009