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Effect of Weather Variables on Strawberry Leather Rot Epidemics. K. M. Reynolds, Former postdoctoral research associate, Department of Plant Pathology, The Ohio State University (OSU), Ohio Agricultural Research and Development Center (OARDC), Wooster 44691, Current address: Forest Sciences Laboratory, USDA Forest Service, Anchorage, AK 99501; L. V. Madden, and M. A. Ellis. Associate professors, respectively, Department of Plant Pathology, The Ohio State University (OSU), Ohio Agricultural Research and Development Center (OARDC), Wooster 44691. Phytopathology 78:822-827. Accepted for publication 7 January 1988. Copyright 1988 The American Phytopathological Society. DOI: 10.1094/Phyto-78-822.

Epidemic development of strawberry leather rot, caused by Phytophthora cactorum, which is spread by rain splash dispersal, was monitored in six field plots in 1986 and eight in 1987. Each plot was 2 m long and three rows wide. In 1986, straw mulch was removed from the interior aisles in three plots (nonstraw plots) and left on the two exterior aisles, and no straw was removed from the remaining three plots (straw plots). In 1987, straw was removed from the interior aisles of six of the eight plots. Plots were infested in mid-May with strawberry fruit on which P. cactorum was sporulating. Assessments of incidence of cyme infection (i.e., proportion of tagged cymes with one or more infected fruit) on each side of each aisle were made 5 days after each rain event on the nonstraw plots, whereas assessments in the straw plots were only made on the last assessment date in both years. By early June 1986, cyme infection was >60% in all but two of the interior aisles and < 10% in both of the exterior aisles in the nonstraw plots and the straw plots. Incidence of cyme infection in 1987 in the straw and nonstraw was similar to that observed in the respective plot types in 1986. Regression analyses were used to examine the relationship between change in logit of cyme infection incidence, rainfall, and either selected weather variables or indices derived from the selected weather variables. Both the weather variables and the indices were calculated for the sporulation period immediately preceding a rain event and for the infection period immediately following a rain event. Stepwise regressions using the weather variables always yielded predictive models that differed significantly between years, whereas regressions using indices for sporulation, infection, and dispersal yielded a common model for the 2 yr.

Additional keywords: disease prediction, Fragaria ananassa, quantitative epidemiology.