Modelling virus- and host-limitation in vectored plant disease epidemics

Models of plant virus epidemics have received less attention than those caused by fungal pathogens. Intuitively, the fact that virus diseases are systemic means that the individual diseased plant can be considered as the population unit which simplifies modelling. However, the fact that a vector is required in the vast majority of cases for virus transmission, means that explicit consideration must be taken of the vector, or, the involvement of the vector in the transmission process must be considered implicitly. In the latter case it is also important that within-plant processes, such as virus multiplication and systemic movement, are taken into account. In this paper we propose an approach based on the linking of transmission at the population level with virus multiplication within plants. The resulting models are parameter-sparse and hence simplistic. However, the range of model outcomes is representative of field observations relating to the apparent limitation of epidemic development in populations of healthy susceptible plants. We propose that epidemic development can be constrained by virus limitation in the early stages of an epidemic when the availability of healthy susceptible hosts is not limiting. There is an inverse relationship between levels of transmission in the population and the mean virus titre/infected plant. In the case of competition between viruses, both virus and host limitation are likely to be important in determining whether one virus can displace another or whether both viruses can co-exist in a plant population. Lotka-Volterra type equations are derived to describe density-dependent competition between two viruses multiplying within plants, embedded within a population level epidemiological model. Explicit expressions determining displacement or co-existence of the viruses are obtained. Unlike the classical Lotka-Volterra competition equations, the co-existence requirement for the competition coefficients to be both less than 1 can be relaxed.

Multiple treatment meta-analysis of products evaluated for control of fire blight in the eastern United States

The aim of this analysis was to estimate the effect sizes and consistency of products evaluated for fire blight control in the eastern United States over the last decade. Because only 3% of the 69 studies published from 2000 to 2008 explicitly presented a measure of within-study variability, a method for estimating the least significant difference (LSD) and, hence the sampling variance, for studies with at least two significant mean separations in the presented mean multiple comparisons was developed. Lin's concordance analysis indicated that the estimated LSD was an accurate predictor of the actual LSD based on 35 studies in a calibration evaluation (ρ(c) = 0.997). Separate multi-treatment random-effects meta-analyses were performed for three control categories: antibiotics, biological control, and plant defense-activating products and mean log response ratios relative to the nontreated controls ([Formula: see text]) were computed for each treatment and then back-transformed to obtain the mean percent disease control. None of the products evaluated performed as well as streptomycin, the standard product for fire blight control, for which the mean disease control was 68.6%. As a group, experimental antibiotics provided the best fire blight control with mean effect sizes ranging from 59.7 to 61.7%. Among the biological controls, the best control was noted for treatments combining the antibiotic streptomycin with a product based on Pantoea agglomerans (55.0% mean disease reduction) or Bacillus subtilis (53.9%). Mean disease control was 31.9, 25.7, and 22.6%, respectively, for products based on B. subtilis, Pantoea agglomerans, and Pseudomonas fluorescens without an antibiotic, suggesting that the higher efficacy of the combination treatments was due to the antibiotic. Among the plant defense-activating products, prohexadione calcium had the highest and most consistent effect size (50.7% control), while other products provided modest mean disease control of between 6.1 and 25.8%. Percent control values were significantly moderated by study location and cultivar used in the study, and were smaller, but more variable, when products were tested under high disease intensity compared with low disease intensity. Results indicate that wide-scale use of biological control and plant defense-activating products in the eastern United States is likely to remain low.

Meta-analysis for evidence synthesis in plant pathology: an overview

Meta-analysis is the analysis of the results of multiple studies, which is typically performed in order to synthesize evidence from many possible sources in a formal probabilistic manner. In a simple sense, the outcome of each study becomes a single observation in the meta-analysis of all available studies. The methodology was developed originally in the social sciences by Smith, Glass, Rosenthal, Hunter, and Schmidt, based on earlier pioneering contributions in statistics by Fisher, Pearson, Yates, and Cochran, but this approach to research synthesis has now been embraced within many scientific disciplines. However, only a handful of articles have been published in plant pathology and related fields utilizing meta-analysis. After reviewing basic concepts and approaches, methods for estimating parameters and interpreting results are shown. The advantages of meta-analysis are presented in terms of prediction and risk analysis, and the high statistical power that can be achieved for detecting significant effects of treatments or significant relationships between variables. Based on power considerations, the fallacy of naïve counting of P values in a narrative review is demonstrated. Although there are many advantages to meta-analysis, results can be biased if the analysis is based on a nonrepresentative sample of study outcomes. Therefore, novel approaches for characterizing the upper bound on the bias are discussed, in order to show the robustness of meta-analysis to possible violation of assumptions.

An Assessment of Mixed-Modeling Approaches for Characterizing Profiles of Time-Varying Response and Predictor Variables

A general statistical modeling approach was tested for characterizing the relationship between pathogen inoculum density (or other biological response variables) and environmental variables when the data are collected as temporal profiles of observations within multiple locations or years. The approach, based on the use of linear mixed models, simultaneously accounts for serial correlations of the observations within each time profile, the random effects of location–year (or other grouping factors), and the cross-correlation of the environmental variables, and is appropriate when the environmental effects on the response variable or its transformation (Y) are distributed over several times (e.g., days). Stability and precision of parameter estimates for environmental effects over multiple time lags were achieved through the use of polynomial constraints within a likelihood-based full mixed-model fit; from the parameter estimates, marginal effects of environmental variables and weights for individual time lags were determined. The mixed model was directly expanded, through the incorporation of smoothing functions, to potentially account for possible longer-term trends in the temporal profiles unrelated to the environmental variables being considered. The new approach described here (with or without a smoothing function) generalizes a previously used—and computationally less demanding—two-stage (composite) approach. In the previous approach, constrained parameter estimates and associated weights were first determined without consideration of serial correlation, cross-correlation of environmental variables, and the random effects of location–year; then, a mixed-model fit was accomplished using the fixed time-lag weights derived in the first step. Using data for inoculum density of Gibberella zeae on wheat spikes from 27 location–years, similar results were achieved with the full mixed model and the two-stage approaches, in terms of both the calculated parameters and predictions of Y. With the use of smoothing functions, the precision of the predictions was improved but the general conclusions regarding environmental effects on Y were not affected. Thus, in the particular example data set, previously derived conclusions regarding environmental effects on inoculum density were robust in terms of the statistical methodology used in analysis; most researchers will find the two-stage approach much easier to implement for the analysis of multiple profiles of time-varying observations.

Relationship between yearly fluctuations in Fusarium head blight intensity and environmental variables: a window-pane analysis

Window-pane methodology was used to determine the length and starting time of temporal windows where environmental variables were associated with annual fluctuations of Fusarium head blight (FHB) intensity in wheat. Initial analysis involved FHB intensity observations for Ohio (44 years), with additional analyses for Indiana (36 years), Kansas (28 years), and North Dakota (23 years). Selected window lengths of 10 to 280 days were evaluated, with starting times from approximate crop maturity back to the approximate time of planting. Associations were quantified with Spearman rank correlation coefficients. Significance for a given variable (for any window starting time in a collection of starting times) was declared using the Simes' multiplicity adjustment; at individual time windows, significant correlations were declared when the individual (unadjusted) P values were <0.005. In all states, moisture- or wetness-related variables (e.g., daily average relative humidity [RH] and total daily precipitation) were found to be positively correlated with FHB intensity for multiple window lengths and starting times; however, the highest correlations were primarily for shorter-length windows (especially 15 and 30 days) at similar starting times during the final 60 days of the growing season, particularly near the time of anthesis. This period encompasses spore production, dispersal, and fungal colonization of wheat spikes. There was no evidence of significant correlations between FHB and temperature-only variables for any time window; however, variables that combined aspects of moisture or wetness with temperature (e.g., duration of temperature between 15 and 30 degrees C and RH > or = 80%) were positively correlated with FHB intensity. Results confirm that the intensity of FHB in a region depends, at least in part, on environmental conditions during relatively short, critical time periods for epidemic development.

Meta-analysis of the effects of triazole-based fungicides on wheat yield and test weight as influenced by Fusarium head blight intensity

ABSTRACT Multivariate random-effects meta-analyses were conducted on 12 years of data from 14 U.S. states to determine the mean yield and test-weight responses of wheat to treatment with propiconazole, prothioconazole, tebuconazole, metconazole, and prothioconazole+tebuconazole. All fungicides led to a significant increase in mean yield and test weight relative to the check (D; P < 0.001). Metconazole resulted in the highest overall yield increase, with a D of 450 kg/ha, followed by prothioconazole+ tebuconazole (444.5 kg/ha), prothioconazole (419.1 kg/ha), tebuconazole (272.6 kg/ha), and propiconazole (199.6 kg/ha). Metconazole, prothioconazole+tebuconazole, and prothioconazole also resulted in the highest increases in test weight, with D values of 17.4 to 19.4 kg/m(3), respectively. On a relative scale, the best three fungicides resulted in an overall 13.8 to 15.0% increase in yield but only a 2.5 to 2.8% increase in test weight. Except for prothioconazole+tebuconazole, wheat type significantly affected the yield response to treatment; depending on the fungicide, D was 110.0 to 163.7 kg/ha higher in spring than in soft-red winter wheat. Fusarium head blight (FHB) disease index (field or plot-level severity) in the untreated check plots, a measure of the risk of disease development in a study, had a significant effect on the yield response to treatment, in that D increased with increasing FHB index. The probability was estimated that fungicide treatment in a randomly selected study will result in a positive yield increase (p(+)) and increases of at least 250 and 500 kg/ha (p(250) and p(500), respectively). For the three most effective fungicide treatments (metconazole, prothioconazole+tebuconazole, and prothioconazole) at the higher selected FHB index, p(+) was very large (e.g., >/=0.99 for both wheat types) but p(500) was considerably lower (e.g., 0.78 to 0.92 for spring and 0.54 to 0.68 for soft-red winter wheat); at the lower FHB index, p(500) for the same three fungicides was 0.34 to 0.36 for spring and only 0.09 to 0.23 for soft-red winter wheat.

Assessing heterogeneity in the relationship between wheat yield and Fusarium head blight intensity using random-coefficient mixed models

Seventy-seven studies reporting Fusarium head blight disease index (Y; mean percentage of diseased spikelets per spike) and wheat yield (W; MT/ha) were analyzed to determine the relationship between W and Y, and to assess the degree of variation for the relationship among studies. A linear random-coefficient model-comprising a population-average intercept and slope, a random residual term, and random effects of study on the intercept and slope (best linear unbiased predictors; BLUPs)-was successfully fitted to the data using maximum likelihood. From the predicted random effects, study-specific intercepts and slopes were obtained, and both population-average and subject-specific predictions of yield were determined. The estimated population-average intercept (expected yield when disease symptoms were not present) was 4.10 MT/ha, and the population-average slope was 0.038 MT/ha per unit increase of disease index. Wheat class had a significant effect on the intercept but not on the slope, with soft-red winter wheat having, on average, 0.85 MT/ha higher yield than spring wheat. Based on the estimates of the among-study variances, there was high variation in the effects of study on the intercept, but substantially lower variation in the effects of study on the slope. Thus, although one cannot predict with accuracy the actual wheat yield in a field or plot based on disease index using population-average results, one can predict with accuracy the decline in yield at a given level of disease index using the population-average slope. Through the modeling results, predicted relative yield (as a percentage of yield when disease is not present) can be determined, as well as predicted disease index at which a prespecified level of yield (or yield loss) is expected to occur. The predicted reduction in yield on a percentage scale was greater for spring than for soft-red winter wheat, on average, because of the lower estimated intercept in absolute units for spring wheat.

Efficacy of triazole-based fungicides for fusarium head blight and deoxynivalenol control in wheat: a multivariate meta-analysis

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.

Variation in Disease Incidence of Phomopsis Cane and Leaf Spot of Grape in Commercial Vineyards in Ohio

A statewide survey for incidence of Phomopsis cane and leaf spot of grape (caused by Phomopsis viticola) was conducted during the 2002 to 2004 growing seasons. Over the 3 years, disease was observed in all surveyed vineyards, and mean disease incidence for leaves and internodes was 42 and 50%, respectively. A hierarchical linear mixed model was used to evaluate effects of region, farm within region, vineyard within farm, sampling site (i.e., vine) within vineyard, and shoot (i.e., cane) within vine on disease incidence. Region of the state did not have a significant effect on incidence but there was significant variation at all other levels of the hierarchy (P < 0.05); the greatest variation was at the lowest scale (shoots within vines). The potential effects of weather and management practices on disease risk at the vineyard scale were determined by using nonparametric correlation and binary logistic analyses after first classifying mean incidence per vineyard as being below or above 20% (D20 = 0,1) and 40% (D40 = 0,1). Overall results indicated that variables for predicted number of moderate infection events (DM; based on ambient temperature and hours when either there was measured rainfall or relative humidity above 90%), the extent of fungicide application (C) during early- and mid-May (M1 and M2, respectively), and the use of a dormant-period application of fungicide (DOR) were the key factors in predicting disease risk (for either D20 or D40). Accuracy (percentage of high and low disease vineyards correctly predicted) and area under the receiver operating characteristic curve (an overall measure of the accuracy of a model) for a generic model combining these predictor variables were 74 and 0.84, respectively, for D40 and 87 and 0.97, respectively, for D20. Models based on management practices were as accurate as those that incorporated weather variables. Although the degree of control of this disease is inadequate in Ohio, based on the survey results for incidence, the results from the risk-model analysis showed that improved management might be obtained by applying fungicide early during the growing season.

The basic reproduction number of plant pathogens: matrix approaches to complex dynamics

The basic reproduction number, R0, is defined as the total number of infections arising from one newly infected individual introduced into a healthy (disease-free) host population. R0 is widely used in ecology and animal and human epidemiology, but has received far less attention in the plant pathology literature. Although the calculation of R0 in simple systems is straightforward, the calculation in complex situations is challenging. A very generic framework exists in the mathematical and biomathematical literature, which is difficult to interpret and apply in specific cases. In this paper we describe a special case of this general framework involving the use of matrix population models. Leading by example, we explain the existing mathematical literature on this subject in such a way that plant pathologists can apply the method for a wide range of pathosystems.

Baseline and Differential Sensitivity to Two QoI Fungicides Among Isolates of Phytophthora cactorum That Cause Leather Rot and Crown Rot on Strawberry

Sensitivities of 89 isolates of Phytophthora cactorum, the causal agent of crown rot and leather rot on strawberry plants, from seven states (Florida, Maine, North Carolina, Ohio, Oregon, South Carolina, and New York) to the QoI fungicide azoxystrobin were determined based on mycelium growth and zoospore germination. Radial growth of mycelia on lima bean agar amended with azoxystrobin at 0.001, 0.01, 0.1, 1.0, 10, and 30 μg/ml and salicylhydroxamic acid (SHAM) at 100 μg/ml was measured after 6 days. Effect on zoospore germination was evaluated in aqueous solutions of azoxystrobin at 0.005, 0.01, 0.05, 0.1, 0.5, and 1.0 μg/ml in 96-well microtiter plates by counting germinated and nongerminated zoospores after 4 h at room temperature. SHAM was not used to evaluate zoospore sensitivity. The effective dose to reduce mycelium growth by 50% (ED₅₀) ranged from 0.16 to 12.52 μg/ml for leather rot isolates and 0.10 to 15 μg/ml for crown rot isolates. The Kolmogorov-Smirnov test showed significant differences (P < 0.001) between the two distributions. Zoospores were much more sensitive to azoxystrobin than were mycelia. Differences between sensitivity distributions for zoospores from leather rot and crown rot isolates were significant at P = 0.05. Estimated ED₅₀ values ranged from 0.01 to 0.24 μg/ml with a median of 0.04 μg/ml. Experiments with pyraclostrobin, another QoI fungicide, demonstrated that both mycelia and zoospores of P. cactorum were more sensitive to pyraclostrobin than to azoxystrobin. Sensitivities to azoxystrobin and pyraclostrobin were moderately but significantly correlated (r = 0.60, P = 0.0001).

A Distributed Lag Analysis of the Relationship Between Gibberella zeae Inoculum Density on Wheat Spikes and Weather Variables

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.

Consideration of Nonparametric Approaches for Assessing Genotype-by-Environment (G × E) Interaction with Disease Severity Data

Determination of host genotype-by-environment (G × E) interaction is needed to assess the stability of cultivar traits such as plant disease resistance and to reveal differences in aggressiveness or virulence of pathogen strains among locations. Here we explored the use of rank-based methodology to quantify the concordance (or discordance) of disease responses of host genotypes across environments, based on the Kendall coefficient of concordance (W) and ancillary test statistics, in order to determine the extent to which environment affected rankings of genotypes. An analysis of four data sets for disease severity of gray leaf spot of maize (with genotypes planted in as many as 11 locations in a given year) revealed highly significant concordance (P ≤ 0.001) overall, indicating that genotypes varied little in within-environment rankings. This suggests that the G × E interaction was small or nonexistent (in terms of rankings). A novel rank-based method by Piepho was evaluated to further elucidate the interaction (if any) through a test for variance homogeneity. The Piepho test statistic was not significant (P > 0.25) for any of the gray leaf spot data sets, confirming the stability of genotypes across environments for this pathosystem; however, analysis of published data sets for other pathosystems indicated significant results. The relationship shown by Hühn, Lotito, and Piepho between the ratio of genotype and residual variances of the original data and the rank-based W statistic was evaluated using Monte Carlo simulations. A more general functional relationship was developed that is applicable over a wide range of number of genotypes and environments in the analyzed studies. This confirms previously shown linkages between rankings of genotypes within environments and variability in the original (unranked) data, thus permitting ease of interpretation of parametric and nonparametric results.

Pre- and Post-Infection Activity of Azoxystrobin, Pyraclostrobin, Mefenoxam, and Phosphite Against Leather Rot of Strawberry, Caused by Phytophthora cactorum

Pre- and post-infection activity of azoxystrobin, pyraclostrobin, mefenoxam, and phosphite against leather rot of strawberry, caused by Phytophthora cactorum, was determined under greenhouse conditions. Strawberry plants (cv. Honeoye) were grown in pots, and attached fruit at the green-to-white stage of development were used in evaluations. Plants and fruit were sprayed to runoff with the above-mentioned fungicides either before (protectant) or after (curative) inoculation with a zoospore suspension (10⁵ zoospores/ml) of P. cactorum. Inoculated plants with fruit were placed in a mist chamber for 12 h to ensure infection. Fungicides were applied at either 2, 4, or 7 days before inoculation or 13, 24, 36, or 48 h after inoculation. Incidence (proportion of diseased fruit) was recorded 6 days after inoculation. Azoxystrobin and pyraclostrobin provided protectant activity for up to 7 days before inoculation, but only slight curative activity when applied 13 h after inoculation. Phosphite and mefenoxam also provided protection for up to 7 days, as well as curative activity of at least 36 h. There were no significant differences in protectant activity among the QoI fungicides azoxystrobin and pyraclostrobin, phosphite and mefenoxam.

Systemic Modulation of Gene Expression in Tomato by Trichoderma hamatum 382

ABSTRACT A light sphagnum peat mix inoculated with Trichoderma hamatum 382 consistently provided a significant (P = 0.05) degree of protection against bacterial spot of tomato and its pathogen Xanthomonas euvesicatoria 110c compared with the control peat mix, even though this biocontrol agent did not colonize aboveground plant parts. To gain insight into the mechanism by which T. hamatum 382 induced resistance in tomato, high-density oligonucleotide microarrays were used to determine its effect on the expression pattern of 15,925 genes in leaves just before they were inoculated with the pathogen. T. hamatum 382 consistently modulated the expression of genes in tomato leaves. We identified 45 genes to be differentially expressed across the replicated treatments, and 41 of these genes could be assigned to at least one of seven functional categories. T. hamatum 382-induced genes have functions associated with biotic or abiotic stress, as well as RNA, DNA, and protein metabolism. Four extensin and extensin-like proteins were induced. However, besides pathogenesis-related protein 5, the main markers of systemic acquired resistance were not significantly induced. This work showed that T. hamatum 382 actively induces systemic changes in plant physiology and disease resistance through systemic modulation of the expression of stress and metabolism genes.

A quantitative review of tebuconazole effect on fusarium head blight and deoxynivalenol content in wheat

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 (</=2% for IND and <1 ppm for DON). C(IND) was 25% higher in studies with mean IND between 2 and 15% than in studies with mean IND </= 2%, whereas C(DON) was 28.8% higher in studies with mean DON between 1 and 10 ppm than in studies with mean DON < 1 ppm. The between-study variance was significantly greater than 0 (P < 0.01), indicating considerable (unexplained) variability in percent control.

Meta-analysis of regression coefficients for the relationship between fusarium head blight and deoxynivalenol content of wheat

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.

Effects of Application of Fungicide During the Dormant Period on Phomopsis Cane and Leaf Spot of Grape Disease Intensity and Inoculum Production

Efficacy of application of the fungicides calcium polysulfide or fixed copper during the dormant period on control of Phomopsis cane and leaf spot of grape (Vitis spp.), caused by Phomopsis viticola, was examined under field conditions during the 2003 and 2004 growing seasons in Ohio. Dormant-period fungicide applications were made either in the fall (after leaf drop and periderm tissue formation on the first-year canes, mid-November), or spring (at bud-swell, mid-April), or both. Disease incidence and severity on leaves and internodes were examined. In addition, effects of dormant-period application on sporulation of P. viticola were determined by examining the number of conidia in rain-splashed water in the spring and formation of mature pycnidia on cane sections in the winter. Fall-and-spring and spring applications of calcium poly-sulfide provided 12 to 88% reduction in disease intensity (incidence or severity), whereas calendar-based protectant mancozeb applications reduced overall disease intensity by 47 to 100%. Fixed-copper applications did not provide a consistent reduction of the disease. Fall applications of dormant-period fungicide provided little or no effect by itself. There was a significantly lower number of conidia observed in collected splashed rain water from vines treated with fall-and-spring applications of calcium polysulfide than in rain water from nonsprayed vines. Fall-and-spring and spring applications of calcium polysulfide provided a significant reduction in the number of mature pycnidia formed on incubated cane sections compared with the nonsprayed control (5 versus 10 pycnidia/cm²), whereas fixed copper did not provide a significant reduction.

Evaluation of a Disease Warning System for Phomopsis Cane and Leaf Spot of Grape: A Field Study

A field evaluation of a warning system for Phomopsis cane and leaf spot of grape (Vitis spp.), caused by Phomopsis viticola, was conducted in Ohio over 3 years (2002 to 2004) by applying fungicides and fungicide-adjuvant combinations based on predicted infection events. Three different criteria for risk-light, moderate, and high-were evaluated with the warning system. The warning system is based on measured weather conditions (temperature and wetness duration following rain) and a model for risk of leaf and internode infection. Vines were sprayed with fungicides based on either the warning system or a calendar-based 7-day protectant program, from 2.5-cm shoot growth (Eichhorn-Lorenz [E-L] stage 7) to the end of the broom (E-L stage 27). Fungicides were tested with or without an adjuvant (JMS Stylet-Oil or Regulaid). In the controls, the mean percentage of leaves and internodes with infections ranged from 36 to 100%, the number of lesions per leaf ranged from 1 to 28, and percentage of internodes covered by lesions ranged from 1 to 12%. Both the calendar-based protectant treatment (based on use of mancozeb) and the warning system treatment based on spraying in response to light or moderate predicted infection events (especially with mancozeb + Regulaid) resulted in significantly less disease incidence and severity compared with the controls. The mean percent control (relative difference in disease between a treatment and the control) was higher for the protectant schedule (˜55% and ˜80% for incidence and severity, respectively, based on application of mancozeb) than for the warning system (˜36% and ˜60% for incidence and severity, respectively, based on application of mancozeb + Regulaid), but there were two to three times more fungicide applications with the protectant schedule than with the warning system.

An assessment model for rating high-threat crop pathogens

ABSTRACT Natural, accidental, and deliberate introductions of nonindigenous crop pathogens have become increasingly recognized as threats to the U.S. economy. Given the large number of pathogens that could be introduced, development of rapid detection methods and control strategies for every potential agent would be extremely difficult and costly. Thus, to ensure the most effective direction of resources a list of high-threat pathogens is needed. We address development of a pathogen threat assessment model based on the analytic hierarchy process (AHP) that can be applied world-wide, using the United States as an illustrative example. Previously, the AHP has been shown to work well for strategic planning and risk assessment. Using the collective knowledge of subject matter expert panels incorporated into commercial decision-making software, 17 biological and economic criteria were determined and given weights for assessing the threat of accidental or deliberately introduced pathogens. The rating model can be applied by experts on particular crops to develop threat lists, especially those of high priority, based on the current knowledge of individual diseases.

Role of Temperature and Moisture in the Production and Maturation of Gibberella zeae Perithecia

Fusarium graminearum (teleomorph Gibberella zeae) is the most common pathogen of Fusarium head blight (FHB) in North America. Ascospores released from the perithecia of G. zeae are a major source of inoculum for FHB. The influence of temperature and moisture on perithecial production and development was evaluated by monitoring autoclaved inoculated cornstalk sections in controlled environments. Perithecial development was assessed at all combinations of five temperatures (12, 16, 20, 24, and 28°C) and four moisture levels with means (range) -0.45 (-0.18, -1.16), -1.30 (-0.81, -1.68), -2.36 (-1.34, -3.53) and -4.02 (-2.39, -5.88) MPa. Moisture levels of -0.45 and -1.30 MPa and temperatures from 16 to 24°C promoted perithecial production and development. Temperatures of 12 and 28°C and moisture levels of -2.36 and -4.02 MPa either slowed or limited perithecial production and development. The water potential of -1.30 MPa had mature perithecia after 10 days at 20°C, but not until after 15 days for 24°C. In contrast, few perithecia achieved maturity and produced ascospores at lower moisture levels (-2.36 and -4.02 MPa) and low (12°C) and high (28°C) temperatures. In the future, it may be possible to use the information gathered in these experiments to improve the accuracy of FHB forecasting systems.

Systemic Resistance Induced by Trichoderma spp.: Interactions Between the Host, the Pathogen, the Biocontrol Agent, and Soil Organic Matter Quality

ABSTRACT Several factors affect the ability of Trichoderma spp. to provide systemic disease control. This paper focuses on the role of the substrate in which plants are grown, resistance of the host to disease, and the ability of introduced Trichoderma inoculum to spread under commercial conditions. Several reports reveal that foliar disease control provided by Trichoderma spp. is more effective on plants grown in compost-amended media compared with in lower-in-microbial-carrying-capacity sphagnum peat media. In Rhododendron spp., host resistance affects control of Phytophthora dieback provided by Trichoderma spp. For example, T. hamatum 382 (T382) significantly (P = 0.05) suppressed the disease on susceptible cv. Roseum Elegans while plant vigor was increased. The disease was not suppressed, however, on highly susceptible cvs. Aglo and PJM Elite even though the vigor of these plants was increased. Using a strain-specific polymerase chain reaction assay under commercial conditions, it was demonstrated that introduced inoculum of T382 did not spread frequently from inoculated to control compost-amended media. Other Trichoderma isolates typically are abundant in control media within days after potting unless inoculated with a specific Trichoderma isolate. Thus, the low population of isolates that can induce systemic resistance in composting and potting mix environments may explain why most compost-amended substrates do not naturally suppress foliar diseases.

Suppression of Botrytis Blight of Begonia by Trichoderma hamatum 382 in Peat and Compost-Amended Potting Mixes

Inoculation of an industry standard light sphagnum peat potting mix with Trichoderma hamatum 382 (T382) significantly (P = 0.05) reduced the severity of Botrytis blight, caused by Botrytis cinerea, on begonia plants grown in a greenhouse. In data combined from three experiments, the degree of control provided by T382 did not differ significantly (P = 0.05) from that provided by weekly topical sprays with chlorothalonil. In addition, T382 significantly (P = 0.05) increased shoot dry weight and salability of flowering plants. Incorporation of composted cow manure (5%, vol/vol) into the light peat mix also significantly (P = 0.05) decreased blight severity while shoot dry weight and salability were increased. Blight severity on plants in this compost mix did not differ significantly (P = 0.05) from that on those in the light peat mix inoculated with T382. Finally, T382 and chlorothalonil did not significantly (P = 0.05) affect blight severity, shoot dry weight, or salability of plants grown in the compost mix. Spatial separation was maintained in begonias between the biocontrol agent T382 and the pathogen. It was concluded, therefore, that the decrease in disease severity provided by inoculation of the peat mix with T382 most likely was due to systemic resistance induced in begonia against Botrytis blight. The suppressive effect of the compost mix against Botrytis blight was unusual because composts typically do not provide such effects unless inoculated with a biocontrol agent capable of inducing systemic resistance in plants to disease.

Relationship between visual estimates of fusarium head blight intensity and deoxynivalenol accumulation in harvested wheat grain: a meta-analysis

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.