Department of Plant Pathology, The Ohio State University, Ohio Agricultural Research and Development Center, Wooster 44691
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Accepted for publication 23 March 2006.
A total of 126 field studies reporting deoxynivalenol (DON; ppm) content of harvested wheat grain and Fusarium head blight index (IND; field or plot-level disease severity) were analyzed to determine the overall mean regression slope and intercept for the relationship between DON and IND, and the influence of study-specific variables on the slope and intercept. A separate linear regression analysis was performed to determine the slope and intercept for each study followed by a meta-analysis of the regression coefficients from all studies. Between-study variances were significantly (P < 0.05) greater than 0, indicating substantial variation in the relationship between the variables. Regression slopes and intercepts were between -0.27 and 1.48 ppm per unit IND and -10.55 to 32.75 ppm, respectively. The overall mean regression slope and intercept, 0.22 ppm per unit IND and 2.94 ppm, respectively, were significantly different from zero (P < 0.001), and the width of the 95% confidence interval was 0.07 ppm per unit IND for slope and 1.44 ppm for intercept. Both slope and intercept were significantly affected by wheat type (P < 0.05); the overall mean intercept was significantly higher in studies conducted using winter wheat cultivars than in studies conducted using spring wheat cultivars, whereas the overall mean slope was significantly higher in studies conducted using spring wheat cultivars than in winter wheat cultivars. Study location had a significant effect on the intercept (P < 0.05), with studies from U.S. winter wheat-growing region having the highest overall mean intercept followed by studies from Canadian wheat-growing regions and U.S. spring wheat-growing regions. The study-wide magnitude of DON and IND had significant effects on one or both of the regression coefficients, resulting in considerable reduction in between-study variances. This indicates that, at least indirectly, environment affected the relationship between DON and IND.
bivariate mixed-effects models,
bivariate random-effects models,
© 2006 The American Phytopathological Society