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A high-throughput baiting and identification process identified more than 7,000 isolates of Pythium from 88 locations in Ohio. Isolates were identified using direct-colony polymerase chain reaction followed by single-strand conformational polymorphism, and communities were assembled using the Jaccard similarity coefficient and cluster analysis. Both univariate and multivariate statistics were used to evaluate differences in soil properties between communities, and canonical discriminant analysis (CDA) was used to assess the strength of the association of soil variables within communities from 83 of the locations. In all, 21 species of Pythium were identified but only 6 were recovered from >40% of the locations. Five communities were formed using the cluster analysis, and significant differences were observed in disease incidence, as well as soil pH, calcium, magnesium, and cation exchange capacity between communities. Stepwise multiple discriminant analysis and CDA identified pH, calcium, magnesium, and field capacity as contributing the most to the separation of the five Pythium communities. There was a strong association between abiotic soil components and the structure of Pythium communities, as well as diversity of Pythium spp. collected from agronomic production fields in Ohio.

The effects of propiconazole, prothioconazole, tebuconazole, metconazole, and prothioconazole+tebuconazole (as a tank mix or a formulated premix) on the control of Fusarium head blight index (IND; field or plot-level disease severity) and deoxynivalenol (DON) in wheat were determined. A multivariate random-effects meta-analytical model was fitted to the log-transformed treatment means from over 100 uniform fungicide studies across 11 years and 14 states, and the mean log ratio (relative to the untreated check or tebuconazole mean) was determined as the overall effect size for quantifying fungicide efficacy. Mean log ratios were then transformed to estimate mean percent reduction in IND and DON relative to the untreated check (percent control: C(IND) and C(DON)) and relative to tebuconazole. All fungicides led to a significant reduction in IND and DON (P < 0.001), although there was substantial between-study variability. Prothioconazole+tebuconazole was the most effective fungicide for IND, with a C(IND) of 52%, followed by metconazole (50%), prothioconazole (48%), tebuconazole (40%), and propiconazole (32%). For DON, metconazole was the most effective treatment, with a [Formula: see text](DON) of 45%; prothioconazole+tebuconazole and prothioconazole showed similar efficacy, with C(DON) values of 42 and 43%, respectively; tebuconazole and propiconazole were the least effective, with C(DON) values of 23 and 12%, respectively. All fungicides, with the exception of propiconazole, were significantly more effective than tebuconazole for control of both IND and DON (P < 0.001). Relative to tebuconazole, prothioconazole, metconazole, and tebuconzole+prothioconzole reduced disease index a further 14 to 20% and DON a further 25 to 29%. In general, fungicide efficacy was significantly higher for spring wheat than for soft winter wheat studies; depending on the fungicide, the difference in percent control between spring and soft winter wheat was 5 to 20% for C(IND) and 7 to 16% for C(DON). Based on the mean log ratios and between-study variances, the probability that IND or DON in a treated plot from a randomly selected study was lower than that in the check by a fixed margin was determined, which confirmed the superior efficacy of prothioconazole, metconazole, and tebuconzole+prothioconzole for Fusarium head blight disease and toxin control.

ABSTRACT In an effort to characterize the association between weather variables and inoculum of Gibberella zeae in wheat canopies, spikes were sampled and assayed for pathogen propagules from plots established in Indiana, North Dakota, Ohio, Pennsylvania, South Dakota, and Manitoba between 1999 and 2005. Inoculum abundance was quantified as the daily number of colony forming units per spike (CFU/spike). A total of 49 individual weather variables for 24-h periods were generated from measurements of ambient weather data. Polynomial distributed lag regression analysis, followed by linear mixed model analysis, was used to (i) identify weather variables significantly related to log-transformed CFU/spike (the response variable; Y), (ii) determine the time window (i.e., lag length) over which each weather variable affected Y, (iii) determine the form of the relationship between each weather variable and Y (defined in terms of the polynomial degree for the relationship between the parameter weights for the weather variables and the time lag involved), and (iv) account for location-specific effects and random effects of years within locations on the response variable. Both location and year within location affected the magnitude of Y, but there was no consistent trend in Y over time. Y on each day was significantly and simultaneously related to weather variables on the day of sampling and on the 8 days prior to sampling (giving a 9-day time window). The structural relationship corresponded to polynomial degrees of 0, 1, or 2, generally showing a smooth change in the parameter weights and time lag. Moisture- (e.g., relative humidity-) related variables had the strongest relationship with Y, but air temperature- and rainfall-related variables also significantly affected Y. The overall marginal effect of each weather variable on Y was positive. Thus, local weather conditions can be utilized to improve estimates of spore density on wheat spikes around the time of flowering.

ABSTRACT A meta-analysis of the effect of tebuconazole (e.g., Folicur 3.6F) on Fusarium head blight and deoxynivalenol (DON) content of wheat grain was performed using data collected from uniform fungicide trials (UFTs) conducted at multiple locations across U.S. wheat-growing regions. Response ratios (mean disease and DON levels from tebuconazole-treated plots, divided by mean disease and DON levels from untreated check plots) were calculated for each of 139 studies for tebuconazole effect on Fusarium head blight index (IND; field or plot-level disease severity, i.e., mean proportion of diseased spikelets per spike) and 101 studies for tebuconazole effect on DON contamination of harvested grain. A random-effects meta-analysis was performed on the log-transformed ratios, and the estimated mean log ratios were transformed to estimate the mean (expected) percent control for IND ( C(IND) ) and DON ( C(DON)). A mixed effects meta-analysis was then done to determine the effects of wheat type (spring versus winter wheat) and disease and DON levels in the controls on the log ratios. Tebuconazole was more effective at limiting IND than DON, with C(IND) and C(DON) values of 40.3 and 21.6%, respectively. The efficacy of tebuconazole as determined by the impact on both IND and DON was greater in spring wheat than in winter wheat (P < 0.01), with a 13.2% higher C(IND) and a 12.4% higher C(DON) in spring wheat than in winter wheat. In general, C(IND) and C(DON) were both at their lowest values (and not significantly different from 0) when mean IND and DON in the controls, respectively, were low (

ABSTRACT 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.

ABSTRACT The association between Fusarium head blight (FHB) intensity and deoxynivalenol (DON) accumulation in harvested grain is not fully understood. A quantitative review of research findings was performed to determine if there was a consistent and significant relationship between measures of Fusarium head blight intensity and DON in harvested wheat grain. Results from published and unpublished studies reporting correlations between DON and Fusarium head blight "index" (IND; field or plot-level disease severity), incidence (INC), diseased-head severity (DHS), and Fusarium-damaged kernels (FDK) were analyzed using meta-analysis to determine the overall magnitude, significance, and precision of these associations. A total of 163 studies was analyzed, with estimated correlation coefficients (r) between -0.58 and 0.99. More than 65% of all r values were >0.50, whereas less that 7% were <0. The overall mean correlation coefficients for all relationships between DON and disease intensity were significantly different from zero (P < 0.001). Based on the analysis of Fisher-transformed r values ( z(r) values), FDK had the strongest relationship with DON, with a mean r of 0.73, followed by IND (r = 0.62), DHS (r = 0.53), and INC (r = 0.52). The mean difference between pairs of transformed z(r) values (z(d) ) was significantly different from zero for all pairwise comparisons, except the comparison between INC and DHS. Transformed correlations were significantly affected by wheat type (spring versus winter wheat), study type (fungicide versus genotype trials), and study location (U.S. spring- and winter-wheat-growing regions, and other wheat-growing regions). The strongest correlations were observed in studies with spring wheat cultivars, in fungicide trials, and in studies conducted in U.S. spring-wheat-growing regions. There were minor effects of magnitude of disease intensity (and indirectly, environment) on the transformed correlations.

ABSTRACT To determine the relationship between incidence (I; proportion of diseased spikes) and severity (S; mean proportion of diseased spikelets per spike) for Fusarium head blight of wheat and to determine if severity could be predicted reliably from incidence data, disease assessments were made visually at multiple sample sites in artificially and naturally inoculated research and production fields between 1999 and 2002. Ten distinct data sets were collected. Mean disease intensity ranged from 0.023 to 0.975 for incidence and from 0.0003 to 0.808 for severity. A model based on complementary log-log transformation of incidence and severity performed well for all data sets, based on calculated coefficients of determination and random residual plots. The I-S relationship was consistent among years and locations, with similar slopes for all data sets. For 7 of the 10 data sets and for the pooled data from all locations and years, the estimated slope from the fit of the model ranged from 1.03 to 1.26. Time of disease assessment affected the relationship between incidence and severity; however, the estimated slopes from each assessment time were also close to 1. Based on the width of the 95% prediction interval, severity was estimated more precisely at lower incidence values than at higher values. The number of sampling units and the index of dispersion of disease incidence had only minor effects on the precision with which S was predicted from I. The estimation of mean S from I would substantially reduce the time required to assess Fusarium head blight in field surveys and treatment comparisons, and the observed relationship between I and S could be used to identify genotypes with some types of disease resistance.

ABSTRACT Rain splash dispersal of Gibberella zeae, causal agent of Fusarium head blight of wheat, was investigated in field studies in Ohio between 2001 and 2003. Samplers placed at 0, 30, and 100 cm above the soil surface were used to collect rain splash in wheat fields with maize residue on the surface and fields with G. zeae-infested maize kernels. Rain splash was collected during separate rain episodes throughout the wheat-growing seasons. Aliquots of splashed rain were transferred to petri dishes containing Komada's selective medium, and G. zeae was identified based on colony and spore morphology. Dispersed spores were measured in CFU/ml. Intensity of splashed rain was highest at 100 cm and ranged from 0.2 to 10.2 mm h(-1), depending on incident rain intensity and sampler height. Spores were recovered from splash samples at all heights in both locations for all sampled rain events. Both macroconidia and ascospores were found based on microscopic examination of random samples of splashed rain. Spore density and spore flux density per rain episode ranged from 0.4 to 40.9 CFU cm(-2) and 0.4 to 84.8 CFU cm(-2) h(-1), respectively. Spore flux density was higher in fields with G. zeae-infested maize kernels than in fields with maize debris, and generally was higher at 0 and 30 cm than at 100 cm at both locations. However, on average, spore flux density was only 30% lower at 100 cm (height of wheat spikes) than at the other heights. The log of spore flux density was linearly related to the log of splashed rain intensity and the log of incident rain intensity. The regression slopes were not significantly affected by year, location, height, and their interactions, but the intercepts were significantly affected by both sampler height and location. Thus, our results show that spores of G. zeae were consistently splash dispersed to spike heights within wheat canopies, and splashed rain intensity and spore flux density could be predicted based on incident rain intensity in order to estimate inoculum dispersal within the wheat canopy.

ABSTRACT Logistic regression models for wheat Fusarium head blight were developed using information collected at 50 location-years, including four states, representing three different U.S. wheat-production regions. Non-parametric correlation analysis and stepwise logistic regression analysis identified combinations of temperature, relative humidity, and rainfall or durations of specified weather conditions, for 7 days prior to anthesis, and 10 days beginning at crop anthesis, as potential predictor variables. Prediction accuracy of developed logistic regression models ranged from 62 to 85%. Models suitable for application as a disease warning system were identified based on model prediction accuracy, sensitivity, specificity, and availability of weather variables at crop anthesis. Four of the identified models correctly classified 84% of the 50 location-years. A fifth model that used only pre-anthesis weather conditions correctly classified 70% of the location-years. The most useful predictor variables were the duration (h) of precipitation 7 days prior to anthesis, duration (h) that temperature was between 15 and 30 degrees C 7 days prior to anthesis, and the duration (h) that temperature was between 15 and 30 degrees C and relative humidity was greater than or equal to 90%. When model performance was evaluated with an independent validation set (n = 9), prediction accuracy was only 6% lower than the accuracy for the original data sets. These results indicate that narrow time periods around crop anthesis can be used to predict Fusarium head blight epidemics.

ABSTRACT Severe epidemics of Fusarium head blight (FHB) caused by Fusarium graminearum, group II (teleomorph: Gibberella zeae) have been occurring on wheat crops in the northcentral United States and southern Canada. Evaluation of resistance to FHB is difficul, because resistance is partial and infection depends upon host plant maturity. Variance component analysis was conducted to determine how best to allocate resources among environments, replications, and subsamples (heads per plot) in FHB screening nurseries. Advanced breeding lines from the Ohio State University wheat-breeding program were evaluated in screening nurseries from 1995 to 1997. Nurseries were artificially inoculated and sprinkler-irrigated to induce FHB epidemics. Over 80% of the variation within an environment resulted from variation associated with subsampling individual heads within plots. The second greatest source of variation was due to genotype by replication interactions. Host plant maturity influenced disease ratings in 1997. The repeatability of genotype means was approximately 50% within environments. The greatest reduction in genotype standard errors was obtained through additional environments, and then replications. Because the cost of an additional environment was estimated at five times the cost of an additional replication, the most cost-effective improvement in precision was obtained through the addition of replications. Advanced breeding lines should be evaluated in at least four replications per environment. Segregating populations will require more replications.