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Relationships of Environmental and Cultural Factors with Severity of Gray Leaf Spot in Maize

Gray leaf spot of maize caused by Cercospora zeae-maydis is a major foliar disease in the United States and other parts of the world. Efficient management of gray leaf spot is hindered by a lack of quantitative information regarding environmental and cultural influences on disease severity. We collected environmental, cultural, and disease severity data in southern Iowa at 13 locations in 1998 and 11 locations in 1999. The independent variables that we considered included temperature, relative humidity, leaf wetness, percent maize residue cover, distance to nearest maize residue, planting date, and previous crop. A time-duration value (TDV) variable was created to represent cumulative hours of favorable temperature (22 ≤ T ≤ 30°C) and relative humidity (≥95%). Disease severity was assessed at 2-week intervals on three to eight maize genotypes differing in gray leaf spot resistance and maturity at each location. Environmental, cultural, and disease data were summarized for four different periods during the growing season and analyzed by stepwise multiple linear regression in order to determine which variables significantly contributed to gray leaf spot severity at the dough or dent growth stages of maize. In 1998, genotype resistance, planting date, distance to nearest maize residue, wetness duration, and TDV had significant effects on disease severity. R² values were similar among the four periods. The best-fitting model for the 1998 data had an R² of 0.65. With 1998 and 1999 data combined, results were similar except that percent maize residue cover was significant rather than distance to nearest maize residue. The best-fitting model had an R² of 0.55. The 2-year model utilizing only the weather variables from emergence to 2 weeks before silking had an R² value of 0.43. Strong linear relationships existed between gray leaf spot severity and genotype resistance, maize surface residue, planting date, and TDV. These results can serve as a foundation for the development of a prediction model for gray leaf spot severity on maize.