MSE FINDR: A Shiny R Application to Estimate Mean Square Error Using Treatment Means and Post-hoc Test Results

Research synthesis methods such as meta-analysis rely primarily on appropriate summary statistics (i.e., means and variance) of a response of interest for implementation to draw general conclusions from a body of research. A commonly encountered problem arises when a measure of variability of a response across a study is not explicitly provided in the summary statistics of primary studies. Typically, these otherwise credible studies, are omitted in research synthesis leading to potential small-study effects and loss of statistical power. We present MSE FINDR, a user-friendly Shiny R application for estimating the mean square error (i.e., within-study residual variance, σ2) for continuous outcomes from ANOVA-type studies, with specific experimental designs and treatment structures (Latin square, completely randomized, randomized complete block, two-way factorial, and split-plot designs). MSE FINDR accomplishes this by using commonly reported information on treatment means, significance level (α), number of replicates and post-hoc mean separation tests (Fisher's LSD, Tukey's HSD, Bonferroni, Šidák and Scheffé). Users upload a CSV file containing the relevant information reported in the study, then specify the experimental design and post-hoc test that was applied in the analysis of the underlying data. MSE FINDR then proceeds to recover σ2, based on user-provided study information. The recovered within-study variance can be downloaded and exported as a CSV file. Simulations of trials with variable number of treatments and treatment effects showed that the MSE FINDR-recovered σ2 was an accurate predictor of the actual ANOVA σ2 for one-way experimental designs when summary statistics (i.e., means, variance and post-hoc results) were available for the single factor. Similarly, σ2 recovered by application accurately predicted the actual σ2 for two-way experimental designs when summary statistics were available for both factors and the sub-plot factor in split-plot designs, irrespective of the post-hoc mean separation test. The MSE FINDR Shiny application, documentation and an accompanying tutorial are hosted at https://garnica.shinyapps.io/MSE_FindR/ and https://github.com/vcgarnica/MSE_FindR/. With this tool, researchers can now easily estimate the within-study variance absent in published reports that nonetheless provide appropriate summary statistics, thus enabling the inclusion of such studies that would have otherwise been excluded in meta-analyses involving estimates of effect sizes based on a continuous response.

A Systematic Review and Quantitative Synthesis of the Efficacy of Quaternary Ammonium Compounds in Disinfesting Nonfungal Plant Pathogens

This quantitative review and systematic analysis of the effectiveness of quaternary ammonium compounds (QACs) in disinfesting nonfungal plant pathogens in agricultural and horticultural cropping systems is a complementary follow-up to a previous study that evaluated the efficacy of QACs against fungal plant pathogens. In the present study, a meta-analysis involving 67 studies was conducted to assess the overall efficacy of QACs against plant pathogenic bacteria, oomycetes, and viruses and to identify factors associated with observed differences in product efficacy. Across all studies, QACs resulted in a significant (P < 0.0001) reduction in either disease intensity or propagule viability with a mean Hedges' g ([Formula: see text]) of 1.75, indicating that overall QAC treatments were moderately effective against nonfungal pathogens. Significant differences in product efficacy were observed between organism types (P = 0.0001), with QAC interventions resulting in higher efficacy (P = 0.0002) against oomycetes ([Formula: see text] = 4.20) than against viruses ([Formula: see text] = 1.42) and bacteria ([Formula: see text] = 1.07), which were not different (P = 0.2689) from each other. As a result, bacterium and virus types were combined into a composite set (BacVir). QAC intervention against BacVir resulted in significant differences in efficacy within categorical moderator subgroups for genus (P = 0.0133), target material (P = 0.0001), and QAC product generation (P = 0.0281). QAC intervention against oomycetes resulted in significant differences in efficacy only for genus (P < 0.0001). For the BacVir composite, five random effect (RE) meta-regression models were significant (P = 0.05), where models with dose and time, dose and genus, time and genus, dose and target, and time and target accounted for 62, 61, 52, 83, and 88%, respectively, of the variance in true effect sizes (R2) associated with [Formula: see text]. For oomycetes, three RE meta-regression models were significant (P = 0.05), where models with dose and time, dose and genus, and time and genus accounted for 64, 86, and 90%, respectively, of R2 associated with [Formula: see text]. These results show that while QACs are moderately effective against nonfungal plant pathogens, the observed variability in their efficacy due to dose of active ingredient and contact time of these products can be influenced by organism type, genus within organism type, the target being treated, and the generation of QAC products.

Effects of Host and Weather Factors on the Growth Rate of Septoria nodorum Blotch Lesions on Winter Wheat

Septoria nodorum blotch (SNB), caused by Parastagonospora nodorum, is a major disease of winter wheat that occurs frequently in the central and southeastern United States. Quantitative resistance to SNB in wheat is determined by various disease resistance components and their interaction with environmental factors. A study was conducted in North Carolina from 2018 to 2020 to characterize SNB lesion size and growth rate and to quantify the effects of temperature and relative humidity on lesion expansion in winter wheat cultivars with different levels of resistance. Disease was initiated in the field by spreading P. nodorum-infected wheat straw in experimental plots. Cohorts (groups of foliar lesions arbitrarily selected and tagged as an observational unit) were sequentially selected and monitored throughout each season. Lesion area was measured at regular intervals, and weather data were collected using in-field data loggers and the nearest weather stations. Final mean lesion area was approximately seven times greater on susceptible than on moderately resistant cultivars, and lesion growth rate was approximately four times higher on susceptible than on moderately resistant cultivars. Across trials and cultivars, temperature had a strong effect of increasing lesion growth rates (P < 0.001), while relative humidity had no significant effect (P = 0.34). Lesion growth rate declined slightly and steadily over the duration of cohort assessment. Our results demonstrate that restricting lesion growth is an important component of SNB resistance in the field and suggest that the ability to limit lesion size may be a useful breeding goal.

Within-Season Shift in Fungicide Sensitivity Profiles of Pseudoperonospora cubensis Populations in Response to Chemical Control

Cucurbit downy mildew, caused by Pseudoperonospora cubensis, is an important disease affecting cucurbits worldwide. Chemical control is an effective method for disease control but P. cubensis has a high risk for developing resistance to fungicides. Alternating fungicides with different modes of action is recommended to avoid an increase of resistant subpopulations. Thus, this study was conducted to establish shifts in the sensitivity profiles of P. cubensis isolates during the growing season, wherein chlorothalonil was applied in alternation with either cymoxanil, fluopicolide, or propamocarb in field experiments conducted from 2018 to 2020 at Rocky Mount, NC and in 2018 and 2020 at Charleston, SC. The sensitivity of baseline isolates sampled early in the season or exposed isolates sampled late in the season to these single-site fungicides was determined using a detached-leaf assay, where tested isolates were classified as sensitive or resistant based on the relative disease severity. Based on the Kruskal-Wallis test, the distribution profile of relative disease severity among baseline and exposed isolates was significantly different where chlorothalonil was alternated with fluopicolide (χ² = 10.82; P = 0.001) but not with cymoxanil (χ² = 1.39; P = 0.238) or propamocarb (χ² = 2.37; P = 0.412). Although there was a directional selection toward resistance for isolates sampled from plots that were treated with fluopicolide or propamocarb alternated with chlorothalonil during a growing season, a significant shift in fungicide sensitivity distribution based on combined data were observed for fluopicolide (χ² = 8.25; P = 0.004) but not propamocarb (χ² = 1.05; P = 0.461). Baseline and exposed isolates sampled from the cymoxanil-treated plots were all resistant to this fungicide and there was no significant shift in their fungicide sensitivity profile during a growing season (χ² = 0.06; P = 1.000). These results indicate that a shift toward reduced sensitivity in P. cubensis can occur during a growing season and the efficacy of fluopicolide is likely to decrease as the frequency of the less sensitive subpopulations increases during a production season. The resultant effect on disease severity and selection of an insensitive subpopulation may accelerate the development of resistance to propamocarb in the southeastern United States.

Evaluation of a Model for Predicting Onset of Septoria nodorum Blotch in Winter Wheat

Prediction models that aid growers in making decisions on timing of fungicide application are important components of integrated management programs for several foliar diseases of wheat. The risk of Septoria nodorum blotch (caused by Parastagonospora nodorum) onset in winter wheat has been reported to be influenced by location, amount of wheat residue in the field, and cumulative daily infection values 2 weeks prior to day of year (DOY) 102. A model previously developed based on these predictor variables was evaluated for its ability to predict disease onset under field conditions. An experiment was conducted at three locations in North Carolina in 2018, 2019, and 2020, where plots were either treated with >20% wheat residue or received no residue treatment. Plots were monitored for disease symptoms, and disease onset was defined to have occurred when mean disease incidence in a plot was 50%. Of the 298 disease cases recorded, disease onset occurred early (i.e., prior to DOY 102) in 257 cases, while onset was late (i.e., on or after DOY 102) in 41 cases. Model accuracy based on correct classification ranged from 0.67 to 0.95, with a mean of 0.87 across the study period. Similarly, sensitivity rates of the model ranged from 0.88 to 1.0 with a mean of 0.98 across all years. However, the model had low specificity, with a mean rate of 0.15 across the study period. Overall, there was no significant difference in the frequency of observed and predicted cases in the study (χ² = 0.50, P = 0.7788, df = 2). Time to disease onset was significantly correlated with grain yield and explained 26% of variation in yield (P < 0.0001). Results indicated that the disease onset model performs well in predicting early disease onset but requires further evaluation and improvement, particularly in the Piedmont, where it over-predicted early onset in 2 successive years.

A Systematic Review and Quantitative Synthesis of the Efficacy of Quaternary Ammonium Disinfestants Against Fungal Plant Pathogens

Quaternary ammonium compounds (QACs) have been used as disinfestants in plant production systems since the late 20th century. In studies on the control of fungal pathogens in agricultural and horticultural crop production systems, the efficacy of QAC disinfestants is variable, ranging from very high to ineffective. A systematic review and meta-analysis were performed to establish and understand how pathogen- and application-related factors influenced product efficacy. The meta-analysis was based on 124 studies involving 14 fungal plant pathogen genera, eight target materials, and four generations of QAC products that contained different mixtures of active ingredients. A significant (P < 0.0001) reduction in either disease intensity or propagule viability resulted following disinfestation using QAC products. Hedges' g standardized mean difference (g̅₊) across the studies was 2.16, indicating that QACs, on average, were highly effective against fungal pathogens. Heterogeneity was significant (P < 0.0001), indicating that effect sizes (g) were not representative of a common mean effect size and supported selection of a random effects model. In all, 78.5% of the observed variance consisted of variance in true effects with a high estimate of between-study variability (τ² = 2.15). For fungal genus, subgroup g̅₊ for genera Pseudonectria and Calonectria was significantly (P < 0.0038) higher than for all other genus subgroups, except Fusarium. For target materials, subgroup g̅₊ for solution, cloth, plant, and metal were significantly (P > 0.0071) higher than for inorganic material or wood. For product generation, subgroup g̅₊ for fifth-generation products was significantly (P > 0.0071) higher than for fourth-, third-, and second-generation products. Dose and time accounted for only 8 and 4%, respectively, of the true variance in effect sizes in the regression model dose, time, and dose-time (P = 0.0004). Genus accounted for 40 and 51% of the true variance in effect sizes in the regression models dose and genus (P = 0.0008) and time and genus (P = 0.0007), respectively. Target material accounted for 18 and 19% of the true variance in effect sizes in the regression models dose and target (P = 0.0001) and time and target (P = 0.0001), respectively. QAC product generation accounted for 24 and 21% of the true variance in effect sizes in the regression models dose and QAC generation (P = 0.0034) and time and QAC generation (P = 0.0189), respectively. These results show that the current recommended rates for dose and contact time are generally expected to result in effective disinfestation for commercial QAC products. However, the efficacy against fungal plant pathogens is likely to be influenced by the fungal genus and target being treated and the generation of the QAC product that is used for disinfestation.

Impact of frequency of application on the long-term efficacy of the biocontrol product Aflasafe in reducing aflatoxin contamination in maize

Aflatoxins, produced by several Aspergillus section Flavi species in various crops, are a significant public health risk and a barrier to trade and development. In sub-Saharan Africa, maize and groundnut are particularly vulnerable to aflatoxin contamination. Aflasafe, a registered aflatoxin biocontrol product, utilizes atoxigenic A. flavus genotypes native to Nigeria to displace aflatoxin producers and mitigate aflatoxin contamination. Aflasafe was evaluated in farmers' fields for 3 years, under various regimens, to quantify carry-over of the biocontrol active ingredient genotypes. Nine maize fields were each treated either continuously for 3 years, the first two successive years, in year 1 and year 3, or once during the first year. For each treated field, a nearby untreated field was monitored. Aflatoxins were quantified in grain at harvest and after simulated poor storage. Biocontrol efficacy and frequencies of the active ingredient genotypes decreased in the absence of annual treatment. Maize treated consecutively for 2 or 3 years had significantly (p < 0.05) less aflatoxin (92% less) in grain at harvest than untreated maize. Maize grain from treated fields subjected to simulated poor storage had significantly less (p < 0.05) aflatoxin than grain from untreated fields, regardless of application regimen. Active ingredients occurred at higher frequencies in soil and grain from treated fields than from untreated fields. The incidence of active ingredients recovered in soil was significantly correlated (r = 0.898; p < 0.001) with the incidence of active ingredients in grain, which in turn was also significantly correlated (r = -0.621, p = 0.02) with aflatoxin concentration. Although there were carry-over effects, caution should be taken when drawing recommendations about discontinuing biocontrol use. Cost-benefit analyses of single season and carry-over influences are needed to optimize use by communities of smallholder farmers in sub-Saharan Africa.

Field Occurrence and Overwintering of Oospores of Pseudoperonospora cubensis in the Southeastern United States

In the United States, the cucurbit downy mildew pathogen, Pseudoperonospora cubensis, has been shown to form oospores under laboratory conditions, but there are no reports on the formation of oospores in naturally infected cucurbit plants in the field. This study investigated the occurrence of oospores in naturally infected leaves from cucurbit fields in North Carolina and South Carolina from 2018 to 2020. Oospore viability and survival was also determined outdoors during the winter in North Carolina during this study period using soil containing leaves infested with oospores. About 5% of 1,658 naturally infected cucumber and cantaloupe leaves sampled during the study had oospores, with a mean density of 585 oospores per cm² of infected leaf tissue. Absolute oospore viability, as assessed using the plasmolysis method, declined linearly (slope = -0.27; P < 0.0001) over the 6-month exposure period from 67.8% in November to 19.3% in May. Other variables being equal, the decrease in oospore viability was significantly affected by soil temperature (b = -0.03 to -0.05; P < 0.0001) and number of rainy days (b = 21.6 to 40.46; P < 0.05), while the effects of soil moisture on oospore viability were less clear. About 20% of the oospores exposed to outdoor conditions at the end the study period were putatively viable and deemed potentially infective. However, these putatively viable oospores failed to germinate or initiate disease when inoculated onto cucumber or cantaloupe leaves. These results indicate that oospores might require some unrecognized stimuli or physiological factors to initiate germination and infection. Nonetheless, viability of oospores at the end of the winter season suggests that once exposed to the right conditions that stimulate germination, these oospores could potentially serve as a primary inoculum source in the southeastern United States where winter temperatures are cold enough to kill cucurbits plants.

Dataset for transcriptomic profiles associated with development of sexual structures in Aspergillus flavus

Information on the transcriptomic changes that occur within sclerotia of Aspergillus flavus during its sexual cycle is very limited and warrants further research. The findings will broaden our knowledge of the biology of A. flavus and can provide valuable insights in the development or deployment of non-toxigenic strains as biocontrol agents against aflatoxigenic strains. This article presents transcriptomic datasets included in our research article entitled, “Development of sexual structures influences metabolomic and transcriptomic profiles in Aspergillus flavus” [1], which utilized transcriptomics to identify possible genes and gene clusters associated with sexual reproduction and fertilization in A. flavus. RNA was extracted from sclerotia of a high fertility cross (Hi-Fert-Mated), a low fertility cross (Lo-Fert-Mated), and unmated strains (Hi-Fert-Unmated and Lo-Fert-Unmated) of A. flavus collected immediately after crossing and at every two weeks until eight weeks of incubation on mixed cereal agar at 30 °C in continuous darkness (n = 4 replicates from each treatment for each time point; 80 total). Raw sequencing reads obtained on an Illumina NovaSeq 6000 were deposited in NCBI's Sequence Read Archive (SRA) repository under BioProject accession number PRJNA789260. Reads were mapped to the A. flavus NRRL 3357 genome (assembly JCVI-afl1-v2.0; GCA_000006275.2) using STAR software. Differential gene expression analyses, functional analyses, and weighted gene co-expression network analysis were performed using DESeq2 R packages. The raw and analyzed data presented in this article could be reused for comparisons with other datasets to obtain transcriptional differences among strains of A. flavus or closely related species. The data can also be used for further investigation of the molecular basis of different processes involved in sexual reproduction and sclerotia fertility in A. flavus.

Temporal Dynamics and Severity of Cucurbit Downy Mildew Epidemics as Affected by Chemical Control and Cucurbit Host Type

Cucurbit downy mildew caused by the oomycete Pseudoperonospora cubensis is an important disease that affects members of Cucurbitaceae family globally. However, temporal dynamics of the disease have not been characterized at the field scale to understand how control strategies influence disease epidemics. Disease severity was assessed visually on cucumber and summer squash treated with weekly alternation of chlorothalonil with cymoxanil, fluopicolide, or propamocarb during the 2018 spring season and 2019 and 2020 fall seasons in North Carolina and the 2018 and 2020 fall seasons in South Carolina. Disease onset was observed around mid-June during the spring season and early September during the fall season, followed by a rapid increase in severity until mid-July in the spring season and late September or mid-October in the fall season, typical of polycyclic epidemics. The Gompertz, logistic, and monomolecular growth models were fitted to disease severity using linear regression and parameter estimates to compare the effects of fungicide treatment and cucurbit host type on disease progress. The Gompertz and logistic models were more appropriate than the monomolecular model in describing temporal dynamics of cucurbit downy mildew, with the Gompertz model providing the best description for 34 of the 44 epidemics examined. Fungicide treatment and host type significantly (P < 0.0001) affected the standardized area under disease progress curve (sAUDPC), final disease severity (Final DS), and weighted mean absolute rates of disease progress (ρ), with these variables, in most cases, being significantly (P < 0.05) lower in fungicide-treated plots than in untreated control plots. Except in a few cases, sAUDPC, Final DS, and ρ were lower in cases where chlorothalonil was alternated with fluopicolide or propamocarb than in cases where chlorothalonil was alternated with cymoxanil or when chlorothalonil was applied alone. These results characterized the temporal progress of cucurbit downy mildew and provided an improved understanding of the dynamics of the disease at the field level. Parameters of disease progress obtained from this study could serve as inputs in simulation studies to assess the efficacy of fungicide alternation in managing fungicide resistance in this pathosystem.

Efficacy of Hypochlorite in Disinfesting Nonfungal Plant Pathogens in Agricultural and Horticultural Plant Production: A Meta-Analysis

Bleach products containing hypochlorite are commonly used as disinfectants to eliminate nonfungal plant pathogens from production surfaces, tools, plant surfaces, irrigation water, and produce dump tanks. Although bleach products are useful, their effectiveness has been reported to vary under specific settings. A meta-analysis was conducted of 86 studies to assess the overall efficacy of hypochlorite against plant pathogenic bacteria, oomycetes, and viruses and to identify factors that explain differences in product efficacy. Hypochlorite resulted in a significant (P < 0.0001) reduction in disease intensity or propagule viability, with a mean Hedges' g standardized difference ([Formula: see text]) of 3.01, indicating that overall, hypochlorite treatments are highly effective. However, heterogeneity in g was significant (P < 0.0001) between studies, wherein 69.8% of the variance observed in g was attributed to true effects. Furthermore, an estimate of between-study variability was moderate (τ² = 1.46). Random effects (REs) metaregression showed limited effects of moderator variables dosage, contact time, targeted material of treatment, and organism type on product efficacy when all organism types were considered together. Because subgroup [Formula: see text] was significantly higher (P = 0.0070) for oomycetes ([Formula: see text] = 3.30) than for bacteria ([Formula: see text] = 2.19), subsequent metaregressions were performed by organism type. For oomycetes, five RE metaregression models, each containing two moderators and their interaction, resulted in significant (P = 0.05) effects, where models with dosage and time, dosage and genus, time and genus, dosage and target, and time and target accounted for ≤50, 71, 57, 48, and 47%, respectively, of the variance in true effect sizes (R²) associated with [Formula: see text]. For viruses, only the RE metaregression model containing time and target and their interaction resulted in significant (P = 0.0435) effects accounting for 38% of the variance in true effect sizes associated with [Formula: see text]. None of the RE metaregression models for bacteria were significant, although they still accounted for ≤28% of the variance in true effect sizes associated with [Formula: see text]. These results show that although the current recommended rates for dosage and contact time for commercial bleach products are generally expected to result in effective disinfestation, the efficacy against nonfungal plant pathogens is expected to be influenced by the organism type and target being treated with hypochlorite.

Need for speed: bacterial effector XopJ2 is associated with increased dispersal velocity of Xanthomonas perforans

Bacterial spot caused by Xanthomonas perforans (Xp) is an economically important disease in tomato. Previous studies have shown that the recently isolated Xp strains have acquired and retained the effector gene, xopJ2, which has been reported to increase fitness of the pathogen in the field. To elucidate the fitness benefit of xopJ2, we quantified the effect of xopJ2 on the dispersal and evolution of Xp populations on tomato. We compared movement of two wild-type Xp strains expressing xopJ2 to their respective xopJ2 mutants when co-inoculated in the field. We developed a binary logistic model to predict the presence of Xp over spatial and temporal dimensions with or without xopJ2. Based on the model, wild-type bacteria were dispersed approximately three times faster than the xopJ2 mutants. In a simulation experiment, the selective advantage due to increased dispersal velocity led to an increase in the frequency of xopJ2 gene in the Xp population and its apparent fixation within 10 to 12 cropping seasons of the tomato crop. Our results show that the presence of a single gene can affect the dispersal of a bacterial pathogen and significantly alter its population dynamics.

Efficacy of Hypochlorite as a Disinfestant Against Fungal Pathogens in Agricultural and Horticultural Plant Production: A Systematic Review and Meta-Analysis

Hypochlorite is often used as a disinfestant of fungal pathogens in a range of agricultural and horticultural settings. However, reports of its effectiveness are variable across studies and it is unclear what factors could potentially influence the reported estimates of its efficacy. A systematic review and meta-analysis was conducted to assess the efficacy of hypochlorite against fungal pathogens and explore factors that may explain the observed heterogeneity in estimates of efficacy. Standardized mean effect size, Hedges' g, was calculated for each of the 109 selected studies, published from 1972 to 2019, that met the criteria defined for the systematic review. A random-effects model was used to estimate the overall mean effect size ([Formula: see text]) and determine the heterogeneity in g among studies. Hypochlorite resulted in a significant (P < 0.001) reduction in either disease intensity or propagule viability with [Formula: see text]= 2.25, suggesting a large overall effect. However, 95% prediction intervals ranged from -0.18 to 4.68, indicating that hypochlorite could be ineffective against some fungi or when targeting some substrate materials. An estimate of the within-study variability, τ², was 1.48 and the proportion of heterogeneity in g among studies due to true effects was 71.5%. Inclusion of categorical moderator variables in the random effects model showed that hypochlorite treatments were significantly (P < 0.0062) more effective when used to disinfest spores in an aqueous solution ([Formula: see text]= 4.58) than when used on plastic ([Formula: see text]= 2.13), plant ([Formula: see text]= 2.13), and wood ([Formula: see text]= 0.79). Similarly, hypochlorite treatments were significantly (P < 0.0083) more effective in disinfesting fungal propagules of Thielaviopsis spp. ([Formula: see text]= 2.51) than those of Verticillium spp. ([Formula: see text]= 1.21). A meta-regression indicated that the effect of dose (β = -3.54; P = 0.0398) and contact time (β = -0.05; P = 0.0001) on [Formula: see text] were highly significant. Further, [Formula: see text]was significantly affected by the dose × time interaction (β = -0.017; P = 0.0269). In the meta-regression models, dose and time explained 0 and 16% of the variance in true effects, respectively. In meta-regression models with a continuous variable of dose or time, a categorical variable of target or genus and their interaction term, genus and target explained an additional 7 to 19% of the variance in true effects. These results show that although the current recommended dose and contact time for commercial bleach products are expected to result in effective disinfestation, the target material and genera of the fungal pathogen of interest will likely influence their efficacy.

"Jumping Jack": Genomic Microsatellites Underscore the Distinctiveness of Closely Related Pseudoperonospora cubensis and Pseudoperonospora humuli and Provide New Insights Into Their Evolutionary Past

Downy mildews caused by obligate biotrophic oomycetes result in severe crop losses worldwide. Among these pathogens, Pseudoperonospora cubensis and P. humuli, two closely related oomycetes, adversely affect cucurbits and hop, respectively. Discordant hypotheses concerning their taxonomic relationships have been proposed based on host-pathogen interactions and specificity evidence and gene sequences of a few individuals, but population genetics evidence supporting these scenarios is missing. Furthermore, nuclear and mitochondrial regions of both pathogens have been analyzed using microsatellites and phylogenetically informative molecular markers, but extensive comparative population genetics research has not been done. Here, we genotyped 138 current and historical herbarium specimens of those two taxa using microsatellites (SSRs). Our goals were to assess genetic diversity and spatial distribution, to infer the evolutionary history of P. cubensis and P. humuli, and to visualize genome-scale organizational relationship between both pathogens. High genetic diversity, modest gene flow, and presence of population structure, particularly in P. cubensis, were observed. When tested for cross-amplification, 20 out of 27 P. cubensis-derived gSSRs cross-amplified DNA of P. humuli individuals, but few amplified DNA of downy mildew pathogens from related genera. Collectively, our analyses provided a definite argument for the hypothesis that both pathogens are distinct species, and suggested further speciation in the P. cubensis complex.

Field Characterization of Partial Resistance to Gray Leaf Spot in Elite Maize Germplasm

Forty-eight inbred lines of maize with varying levels of resistance to gray leaf spot (GLS) were artificially inoculated with Cercospora zeina and evaluated to characterize partial disease resistance in maize under field conditions from 2012 to 2014 across 12 environments in western Kenya. Eight measures of disease epidemic-that is, final percent diseased leaf area (FPDLA), standardized area under the disease progress curve (SAUDPC), weighted mean absolute rate of disease increase (ρ), disease severity scale (CDSG), percent diseased leaf area at the inflection point (PDLA_IP), SAUDPC at the inflection point (SAUDPC_IP), time from inoculation to transition of disease progress from the increasing to the decreasing phase of epidemic increase (T_IP), and latent period (LP)-were examined. Inbred lines significantly (P < 0.05) affected all measures of disease epidemic except ρ. However, the proportion of the variation attributed to the analysis of variance model was most strongly associated with SAUDPC (R² = 89.4%). Inbred lines were also most consistently ranked for disease resistance based on SAUDPC. Although SAUDPC was deemed the most useful variable for quantifying partial resistance in the test genotypes, the proportion of the variation in SAUDPC in each plot was most strongly (R² = 93.9%) explained by disease ratings taken between the VT and R4 stages of plant development. Individual disease ratings at the R4 stage of plant development were nearly as effective as SAUDPC in discerning the differential reaction of test genotypes. Thus, GLS rankings of inbred lines based on disease ratings at these plant developmental stages should be useful in prebreeding nurseries and preliminary evaluation trials involving large germplasm populations.

Characterization of morphological changes within stromata during sexual reproduction in Aspergillus flavus

Aspergillus flavus contaminates agricultural products worldwide with carcinogenic aflatoxins that pose a serious health risk to humans and animals. The fungus survives adverse environmental conditions through production of sclerotia. When fertilized by a compatible conidium of an opposite mating type, a sclerotium transforms into a stroma within which ascocarps, asci, and ascospores are formed. However, the transition from a sclerotium to a stroma during sexual reproduction in A. flavus is not well understood. Early events during the interaction between sexually compatible strains of A. flavus were visualized using conidia of a green fluorescent protein (GFP)-labeled MAT1-1 strain and sclerotia of an mCherry-labeled MAT1-2 strain. Both conidia and sclerotia of transformed strains germinated to produce hyphae within 24 h of incubation. Hyphal growth of these two strains produced what appeared to be a network of interlocking hyphal strands that were observed at the base of the mCherry-labeled sclerotia (i.e., region in contact with agar surface) after 72 h of incubation. At 5 wk following incubation, intracellular green-fluorescent hyphal strands were observed within the stromatal matrix of the mCherry-labeled strain. Scanning electron microscopy of stromata from a high- and low-fertility cross and unmated sclerotia was used to visualize the formation and development of sexual structures within the stromatal and sclerotial matrices, starting at the time of crossing and thereafter every 2 wk until 8 wk of incubation. Morphological differences between sclerotia and stromata became apparent at 4 wk of incubation. Internal hyphae and croziers were detected inside multiple ascocarps that developed within the stromatal matrix of the high-fertility cross but were not detected in the matrix of the low-fertility cross or the unmated sclerotia. At 6 to 8 wk of incubation, hyphal tips produced numerous asci, each containing one to eight ascospores that emerged out of an ascus following the breakdown of the ascus wall. These observations broaden our knowledge of early events during sexual reproduction and suggest that hyphae from the conidium-producing strain may be involved in the early stages of sexual reproduction in A. flavus. When combined with omics data, these findings could be useful in further exploration of the molecular and biochemical mechanisms underlying sexual reproduction in A. flavus.

Biocontrol Strains Differentially Shift the Genetic Structure of Indigenous Soil Populations of Aspergillus flavus

Biocontrol using non-aflatoxigenic strains of Aspergillus flavus has the greatest potential to mitigate aflatoxin contamination in agricultural produce. However, factors that influence the efficacy of biocontrol agents in reducing aflatoxin accumulation under field conditions are not well-understood. Shifts in the genetic structure of indigenous soil populations of A. flavus following application of biocontrol products Afla-Guard and AF36 were investigated to determine how these changes can influence the efficacy of biocontrol strains in reducing aflatoxin contamination. Soil samples were collected from maize fields in Alabama, Georgia, and North Carolina in 2012 and 2013 to determine changes in the population genetic structure of A. flavus in the soil following application of the biocontrol strains. A. flavus L was the most dominant species of Aspergillus section Flavi with a frequency ranging from 61 to 100%, followed by Aspergillus parasiticus that had a frequency of <35%. The frequency of A. flavus L increased, while that of A. parasiticus decreased after application of biocontrol strains. A total of 112 multilocus haplotypes (MLHs) were inferred from 1,282 isolates of A. flavus L using multilocus sequence typing of the trpC, mfs, and AF17 loci. A. flavus individuals belonging to the Afla-Guard MLH in the IB lineage were the most dominant before and after application of biocontrol strains, while individuals of the AF36 MLH in the IC lineage were either recovered in very low frequencies or not recovered at harvest. There were no significant (P > 0.05) differences in the frequency of individuals with MAT1-1 and MAT1-2 for clone-corrected MLH data, an indication of a recombining population resulting from sexual reproduction. Population mean mutation rates were not different across temporal and spatial scales indicating that mutation alone is not a driving force in observed multilocus sequence diversity. Clustering based on principal component analysis identified two distinct evolutionary lineages (IB and IC) across all three states. Additionally, patristic distance analysis revealed phylogenetic incongruency among single locus phylogenies which suggests ongoing genetic exchange and recombination. Levels of aflatoxin accumulation were very low except in North Carolina in 2012, where aflatoxin levels were significantly (P < 0.05) lower in grain from treated compared to untreated plots. Phylogenetic analysis showed that Afla-Guard was more effective than AF36 in shifting the indigenous soil populations of A. flavus toward the non-toxigenic or low aflatoxin producing IB lineage. These results suggest that Afla-Guard, which matches the genetic and ecological structure of indigenous soil populations of A. flavus in Alabama, Georgia, and North Carolina, is likely to be more effective in reducing aflatoxin accumulation and will also persist longer in the soil than AF36 in the southeastern United States.

Cultural and Genetic Approaches to Manage Aflatoxin Contamination: Recent Insights Provide Opportunities for Improved Control

Aspergillus flavus is a morphologically complex species that can produce the group of polyketide derived carcinogenic and mutagenic secondary metabolites, aflatoxins, as well as other secondary metabolites such as cyclopiazonic acid and aflatrem. Aflatoxin causes aflatoxicosis when aflatoxins are ingested through contaminated food and feed. In addition, aflatoxin contamination is a major problem, from both an economic and health aspect, in developing countries, especially Asia and Africa, where cereals and peanuts are important food crops. Earlier measures for control of A. flavus infection and consequent aflatoxin contamination centered on creating unfavorable environments for the pathogen and destroying contaminated products. While development of atoxigenic (nonaflatoxin producing) strains of A. flavus as viable commercial biocontrol agents has marked a unique advance for control of aflatoxin contamination, particularly in Africa, new insights into the biology and sexuality of A. flavus are now providing opportunities to design improved atoxigenic strains for sustainable biological control of aflatoxin. Further, progress in the use of molecular technologies such as incorporation of antifungal genes in the host and host-induced gene silencing, is providing knowledge that could be harnessed to develop germplasm that is resistant to infection by A. flavus and aflatoxin contamination. This review summarizes the substantial progress that has been made to understand the biology of A. flavus and mitigate aflatoxin contamination with emphasis on maize. Concepts developed to date can provide a basis for future research efforts on the sustainable management of aflatoxin contamination.

Resistance to Fluopicolide and Propamocarb and Baseline Sensitivity to Ethaboxam Among Isolates of Pseudoperonospora cubensis From the Eastern United States

Chemical control is currently the most effective method for controlling cucurbit downy mildew (CDM) caused by Pseudoperonospora cubensis. Most commercial cucurbit cultivars, with the exception of a few new cucumber cultivars, lack adequate disease resistance. Fluopicolide and propamocarb were among the most effective fungicides against CDM in the United States between 2006 and 2009. Since then, reduced efficacy of these two fungicides under field conditions was reported starting around 2013 but occurrence of resistance to fluopicolide and propamocarb in field isolates of P. cubensis had not been established. Thirty-one isolates collected from cucurbits in the eastern United States were tested for their sensitivity to fluopicolide and propamocarb using a leaf disc assay. This same set of isolates and four additional isolates (i.e., 35 isolates) were also used to establish the baseline sensitivity of P. cubensis to ethaboxam, an ethylamino-thiazole-carboxamide fungicide, which was recently granted registration to control CDM in the United States. About 65% of the isolates tested were resistant to fluopicolide with at least one resistant isolate being present in samples collected from 12 of the 13 states in the eastern United States. About 74% of the isolates tested were sensitive to propamocarb with at least one resistant isolate being among samples collected from 8 of the 12 states in the study. The frequency of resistance to fluopicolide and propamocarb was high among isolates collected from cucumber, while the frequency was low among isolates collected from other cucurbit host types. All isolates tested were found to be sensitive to ethaboxam and EC₅₀ values ranged from 0.18 to 3.08 mg a.i./liter with a median of 1.55 mg a.i./liter. The ratio of EC₅₀ values for the least sensitive and the most sensitive isolate was 17.1, indicating that P. cubensis isolates were highly sensitive to ethaboxam. The most sensitive isolates to ethaboxam were collected from New York, North Carolina, and Ohio, while the least sensitive isolates were collected from Georgia, Michigan, and New Jersey. These results show that ethaboxam could be a viable addition to fungicide programs used to control CDM in the United States.

Evaluation of a Model for Predicting the Infection Risk of Squash and Cantaloupe by Pseudoperonospora cubensis

Infection risk models of downy mildew of cucumber caused by Pseudoperonospora cubensis were evaluated for their performance in predicting the infection risk of squash and cantaloupe plants under field conditions. Experiments were conducted from 2012 to 2014 in Clayton, NC and Charleston, SC, where disease-free potted plants were exposed to weather conditions during a 24- and 48-h period (hereafter 24- and 48-h models, respectively) within a plot with naturally occurring inoculum. Exposed plants were subsequently placed in a growth chamber where they were monitored for disease symptoms, which was indicative of a successful infection. Disease severity was assessed after 7 days as the proportion of leaf area with disease symptoms. Two predictor variables, day temperature and hours of relative humidity >80% during each exposure were used as inputs to generate model predictions that were compared with observed data. The threshold probability on the receiver operating characteristic (ROC) curve that minimized the overall error rate for the 24-h model was 0.85 for both squash and cantaloupe. The 24-h model was consistently more accurate than the 48-h model in predicting the infection risk for the two hosts. The accuracy of the 24-h model as estimated using area under ROC curve ranged from 0.75 to 0.81, with a correct classification rate ranging from 0.69 to 0.74 across the two hosts. Specificity rates for the model ranged from 0.81 to 0.84, while the sensitivity rates ranged from 0.58 to 0.67. Optimal decisions thresholds (P_OT) developed based on estimates of economic damage and costs of management showed that P_OT was dependent on the probability of disease occurrence, with the benefit of using the 24-h model for making management decisions being greatest at low levels of probability of disease occurrence. This 24-h model, previously developed using cucumber as the host, resulted in accurate estimates of the daily infection risk of squash and cantaloupe and could potentially be useful when incorporated into a decision support tool to guide fungicide applications to manage downy mildew in these other cucurbit host types.

Predicting the risk of cucurbit downy mildew in the eastern United States using an integrated aerobiological model

Cucurbit downy mildew caused by the obligate oomycete, Pseudoperonospora cubensis, is considered one of the most economically important diseases of cucurbits worldwide. In the continental United States, the pathogen overwinters in southern Florida and along the coast of the Gulf of Mexico. Outbreaks of the disease in northern states occur annually via long-distance aerial transport of sporangia from infected source fields. An integrated aerobiological modeling system has been developed to predict the risk of disease occurrence and to facilitate timely use of fungicides for disease management. The forecasting system, which combines information on known inoculum sources, long-distance atmospheric spore transport and spore deposition modules, was tested to determine its accuracy in predicting risk of disease outbreak. Rainwater samples at disease monitoring sites in Alabama, Georgia, Louisiana, New York, North Carolina, Ohio, Pennsylvania and South Carolina were collected weekly from planting to the first appearance of symptoms at the field sites during the 2013, 2014, and 2015 growing seasons. A conventional PCR assay with primers specific to P. cubensis was used to detect the presence of sporangia in rain water samples. Disease forecasts were monitored and recorded for each site after each rain event until initial disease symptoms appeared. The pathogen was detected in 38 of the 187 rainwater samples collected during the study period. The forecasting system correctly predicted the risk of disease outbreak based on the presence of sporangia or appearance of initial disease symptoms with an overall accuracy rate of 66 and 75%, respectively. In addition, the probability that the forecasting system correctly classified the presence or absence of disease was ≥ 73%. The true skill statistic calculated based on the appearance of disease symptoms in cucurbit field plantings ranged from 0.42 to 0.58, indicating that the disease forecasting system had an acceptable to good performance in predicting the risk of cucurbit downy mildew outbreak in the eastern United States.

Epidemiology: Past, Present, and Future Impacts on Understanding Disease Dynamics and Improving Plant Disease Management-A Summary of Focus Issue Articles

Epidemiology has made significant contributions to plant pathology by elucidating the general principles underlying the development of disease epidemics. This has resulted in a greatly improved theoretical and empirical understanding of the dynamics of disease epidemics in time and space, predictions of disease outbreaks or the need for disease control in real-time basis, and tactical and strategic solutions to disease problems. Availability of high-resolution experimental data at multiple temporal and spatial scales has now provided a platform to test and validate theories on the spread of diseases at a wide range of spatial scales ranging from the local to the landscape level. Relatively new approaches in plant disease epidemiology, ranging from network to information theory, coupled with the availability of large-scale datasets and the rapid development of computer technology, are leading to revolutionary thinking about epidemics that can result in considerable improvement of strategic and tactical decision making in the control and management of plant diseases. Methods that were previously restricted to topics such as population biology or evolution are now being employed in epidemiology to enable a better understanding of the forces that drive the development of plant disease epidemics in space and time. This Focus Issue of Phytopathology features research articles that address broad themes in epidemiology including social and political consequences of disease epidemics, decision theory and support, pathogen dispersal and disease spread, disease assessment and pathogen biology and disease resistance. It is important to emphasize that these articles are just a sample of the types of research projects that are relevant to epidemiology. Below, we provide a succinct summary of the articles that are published in this Focus Issue .

Resurgence of cucurbit downy mildew in the United States: Insights from comparative genomic analysis of Pseudoperonospora cubensis

Pseudoperonospora cubensis, the causal agent of cucurbit downy mildew (CDM), is known to exhibit host specialization. The virulence of different isolates of the pathogen can be classified into pathotypes based on their compatibility with a differential set composed of specific cucurbit host types. However, the genetic basis of host specialization within P. cubensis is not yet known. Total genomic DNA extracted from nine isolates of P. cubensis collected from 2008 to 2013 from diverse cucurbit host types (Cucumis sativus, C. melo var. reticulatus, Cucurbita maxima, C. moschata, C. pepo, and Citrullus lanatus) in the United States were subjected to whole-genome sequencing. Comparative analysis of these nine genomes confirmed the presence of two distinct evolutionary lineages (lineages I and II) of P. cubensis. Many fixed polymorphisms separated lineage I comprising isolates from Cucurbita pepo, C. moschata, and Citrullus lanatus from lineage II comprising isolates from Cucumis spp. and Cucurbita maxima. Phenotypic characterization showed that lineage II isolates were of the A1 mating type and belonged to pathotypes 1 and 3 that were not known to be present in the United States prior to the resurgence of CDM in 2004. The association of lineage II isolates with the new pathotypes and a lack of genetic diversity among these isolates suggest that lineage II of P. cubensis is associated with the resurgence of CDM on cucumber in the United States.

Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients

Empirical and mechanistic modeling indicate that pathogens transmitted via aerially dispersed inoculum follow a power law, resulting in dispersive epidemic waves. The spread parameter (b) of the power law model, which is an indicator of the distance of the epidemic wave front from an initial focus per unit time, has been found to be approximately 2 for several animal and plant diseases over a wide range of spatial scales under conditions favorable for disease spread. Although disease spread and epidemic expansion can be influenced by several factors, the stability of the parameter b over multiple epidemic years has not been determined. Additionally, the size of the initial epidemic area is expected to be strongly related to the final epidemic extent for epidemics, but the stability of this relationship is also not well established. Here, empirical data of cucurbit downy mildew epidemics collected from 2008 to 2014 were analyzed using a spatio-temporal model of disease spread that incorporates logistic growth in time with a power law function for dispersal. Final epidemic extent ranged from 4.16 ×10⁸ km² in 2012 to 6.44 ×10⁸ km² in 2009. Current epidemic extent became significantly associated (P < 0.0332; 0.56 < R² < 0.99) with final epidemic area beginning near the end of April, with the association increasing monotonically to 1.0 by the end of the epidemic season in July. The position of the epidemic wave-front became exponentially more distant with time, and epidemic velocity increased linearly with distance. Slopes from the temporal and spatial regression models varied with about a 2.5-fold range across epidemic years. Estimates of b varied substantially ranging from 1.51 to 4.16 across epidemic years. We observed a significant b ×time (or distance) interaction (P < 0.05) for epidemic years where data were well described by the power law model. These results suggest that the spread parameter b may not be stable over multiple epidemic years. However, b ≈ 2 may be considered the lower limit of the distance traveled by epidemic wave-fronts for aerially transmitted pathogens that follow a power law dispersal function.

A Model for Predicting Onset of Stagonospora nodorum Blotch in Winter Wheat Based on Preplanting and Weather Factors

Stagonospora nodorum blotch (SNB) caused by Parastagonospora nodorum is a serious disease of wheat worldwide. In the United States, the disease is prevalent on winter wheat in many eastern states, and its management relies mainly on fungicide application after flag leaf emergence. Although SNB can occur prior to flag leaf emergence, the relationship between the time of disease onset and yield has not been determined. Such a relationship is useful in identifying a threshold to facilitate prediction of disease onset in the field. Disease occurred in 390 of 435 disease cases that were recorded across 11 counties in North Carolina from 2012 to 2014. Using cases with disease occurrence, the effect of disease onset on yield was analyzed to identify a disease onset threshold that related time of disease onset to yield. Regression analysis showed that disease onset explained 32% of the variation in yield (P < 0.0001) and from this relationship, day of year (DOY) 102 was identified as the disease onset threshold. Below-average yield occurred in 87% of the disease cases when disease onset occurred before DOY 102 but in only 28% of those cases when onset occurred on or after DOY 102. Subsequently, binary logistic regression models were developed to predict the occurrence and onset of SNB using preplanting factors and cumulative daily infection values (cDIV) starting 1 to 3 weeks prior to DOY 102. Logistic regression showed that previous crop, latitude, and cDIV accumulated 2 weeks prior to DOY 102 (cDIV.2) were significant (P < 0.0001) predictors of disease occurrence, and wheat residue, latitude, longitude, and cDIV.2 were significant (P < 0.0001) predictors of disease onset. The disease onset model had a correct classification rate of 0.94 and specificity and sensitivity rates >0.90. Performance of the disease onset model based on the area under the receiver operating characteristic curve (AUC), κ, and the true skill statistic (TSS) was excellent, with prediction accuracy values >0.88. Similarly, internal validation of the disease onset model based on AUC, κ, and TSS indicated good performance, with accuracy values >0.88. This disease onset prediction model could serve as a useful decision support tool to guide fungicide applications to manage SNB in wheat.

Virulence Structure Within Populations of Pseudoperonospora cubensis in the United States

Cucurbit downy mildew (CDM), caused by the obligate oomycete Pseudoperonospora cubensis, has resurged around the world during the past three decades. A new pathotype or genetic recombinant of P. cubensis have been suggested as possible reasons for the resurgence of CDM in the United States in 2004. In total, 22 isolates collected between 2004 and 2014, mainly in the eastern United States, were tested for their compatibility with a set of 15 cucurbit host types. The virulence structure within these isolates was evaluated on a set of 12 differential genotypes from eight genera. All isolates were highly compatible with the susceptible cultivar of Cucumis sativus, whereas the least compatibility was observed with Luffa cylindrica and Momordica charantia. Based on the compatibility with the differential host set, five pathotypes (1, 3, 4, 5, and 6) were identified among the 22 isolates examined. Pathotypes 1 and 3 had not been previously described in the United States and isolates of these two new pathotypes were also compatible with 'Poinsett 76', a cultivar of C. sativus known to be resistant to CDM prior to 2004. Virulence within the pathogen population was expressed based on virulence factors, virulence phenotypes, and virulence complexity. The number of virulence factors ranged from two to eight, indicating a complex virulence structure, with 77% of the isolates having five to eight virulence factors. Thirteen virulence phenotypes were identified; the mean number of virulence factors per isolate and mean number of virulence factors per virulence phenotype was 5.05 and 5.23, respectively, indicating that complex isolates and phenotypes contributed equally to the complex virulence structure of P. cubensis. Gleason and Shannon indices of diversity were 3.88 and 2.32, respectively, indicating a diverse virulence structure of P. cubensis within the United States population. The diverse virulence and high virulence complexity within the pathogen population indicate that host resistance alone in available cucurbit cultivars will not be effective to control CDM. An integrated approach involving a combination of fungicide application and introduction of cultivars with new resistance genes will be required for effective management of CDM.

Occurrence and Distribution of Mating Types of Pseudoperonospora cubensis in the United States

During the past two decades, a resurgence of cucurbit downy mildew has occurred around the world, resulting in severe disease epidemics. In the United States, resurgence of the disease occurred in 2004 and several hypotheses, including introduction of a new genetic recombinant or pathotype of the pathogen, have been suggested as potential causes for this resurgence. Occurrence and distribution of mating types of Pseudoperonospora cubensis in the United States were investigated using 40 isolates collected from cucurbits across 11 states from 2005 to 2013. Pairing of unknown isolates with known mating-type tester strains on detached leaves of cantaloupe or cucumber resulted in oospore formation 8 to 10 days after inoculation. Isolates differed in their ability to form oospores across all coinoculation pairings, with oospore numbers ranging from 280 to 1,000 oospores/cm² of leaf tissue. Oospores were hyaline to golden-yellow, spherical, and approximately 36 μm in diameter. Of the 40 isolates tested, 24 were found to be of the A1 mating type, while 16 were of the A2 mating type. Mating type was significantly (P < 0.0001) associated with host type, whereby all isolates collected from cucumber were of the A1 mating type, while isolates from squash and watermelon were of the A2 mating type. Similarly, mating type was significantly (P = 0.0287) associated with geographical region, where isolates from northern-tier states of Michigan, New Jersey, New York, and Ohio were all A1, while isolates belonging to either A1 or A2 mating type were present in equal proportions in southern-tier states of Alabama, Florida, Georgia, North Carolina, South Carolina, and Texas. Viability assays showed that oospores were viable and, on average, approximately 40% of the oospores produced were viable as determined by the plasmolysis method. This study showed that A1 and A2 mating types of P. cubensis are present and the pathogen could potentially reproduce sexually in cucurbits within the United States. In addition, the production of viable oospores reported in this study suggests that oospores could have an important role in the biology of P. cubensis and could potentially influence the epidemiology of cucurbit downy mildew in the United States.

Using Next-Generation Sequencing to Develop Molecular Diagnostics for Pseudoperonospora cubensis, the Cucurbit Downy Mildew Pathogen

Advances in next-generation sequencing (NGS) allow for rapid development of genomics resources needed to generate molecular diagnostics assays for infectious agents. NGS approaches are particularly helpful for organisms that cannot be cultured, such as the downy mildew pathogens, a group of biotrophic obligate oomycetes that infect crops of economic importance. Unlike most downy mildew pathogens that are highly host-specific, Pseudoperonospora cubensis causes disease on a broad range of crops belonging to the family Cucurbitaceae. In this study, we identified candidate diagnostic markers for P. cubensis by comparing NGS data from a diverse panel of P. cubensis and P. humuli isolates, two very closely related oomycete species. P. cubensis isolates from diverse hosts and geographical regions in the United States were selected for sequencing to ensure that candidates were conserved in P. cubensis isolates infecting different cucurbit hosts. Genomic regions unique to and conserved in P. cubensis isolates were identified through bioinformatics. These candidate regions were then validated using PCR against a larger collection of isolates from P. cubensis, P. humuli, and other oomycetes. Overall seven diagnostic markers were found to be specific to P. cubensis. These markers could be used for pathogen diagnostics on infected tissue, or adapted for monitoring airborne inoculum with real-time PCR and spore traps.

Predicting Pre-planting Risk of Stagonospora nodorum blotch in Winter Wheat Using Machine Learning Models

Pre-planting factors have been associated with the late-season severity of Stagonospora nodorum blotch (SNB), caused by the fungal pathogen Parastagonospora nodorum, in winter wheat (Triticum aestivum). The relative importance of these factors in the risk of SNB has not been determined and this knowledge can facilitate disease management decisions prior to planting of the wheat crop. In this study, we examined the performance of multiple regression (MR) and three machine learning algorithms namely artificial neural networks, categorical and regression trees, and random forests (RF), in predicting the pre-planting risk of SNB in wheat. Pre-planting factors tested as potential predictor variables were cultivar resistance, latitude, longitude, previous crop, seeding rate, seed treatment, tillage type, and wheat residue. Disease severity assessed at the end of the growing season was used as the response variable. The models were developed using 431 disease cases (unique combinations of predictors) collected from 2012 to 2014 and these cases were randomly divided into training, validation, and test datasets. Models were evaluated based on the regression of observed against predicted severity values of SNB, sensitivity-specificity ROC analysis, and the Kappa statistic. A strong relationship was observed between late-season severity of SNB and specific pre-planting factors in which latitude, longitude, wheat residue, and cultivar resistance were the most important predictors. The MR model explained 33% of variability in the data, while machine learning models explained 47 to 79% of the total variability. Similarly, the MR model correctly classified 74% of the disease cases, while machine learning models correctly classified 81 to 83% of these cases. Results show that the RF algorithm, which explained 79% of the variability within the data, was the most accurate in predicting the risk of SNB, with an accuracy rate of 93%. The RF algorithm could allow early assessment of the risk of SNB, facilitating sound disease management decisions prior to planting of wheat.

Environmental distribution and genetic diversity of vegetative compatibility groups determine biocontrol strategies to mitigate aflatoxin contamination of maize by Aspergillus flavus

Maize infected by aflatoxin-producing Aspergillus flavus may become contaminated with aflatoxins, and as a result, threaten human health, food security and farmers' income in developing countries where maize is a staple. Environmental distribution and genetic diversity of A. flavus can influence the effectiveness of atoxigenic isolates in mitigating aflatoxin contamination. However, such information has not been used to facilitate selection and deployment of atoxigenic isolates. A total of 35 isolates of A. flavus isolated from maize samples collected from three agro-ecological zones of Nigeria were used in this study. Ecophysiological characteristics, distribution and genetic diversity of the isolates were determined to identify vegetative compatibility groups (VCGs). The generated data were used to inform selection and deployment of native atoxigenic isolates to mitigate aflatoxin contamination in maize. In co-inoculation with toxigenic isolates, atoxigenic isolates reduced aflatoxin contamination in grain by > 96%. A total of 25 VCGs were inferred from the collected isolates based on complementation tests involving nitrate non-utilizing (nit(-)) mutants. To determine genetic diversity and distribution of VCGs across agro-ecological zones, 832 nit(-) mutants from 52 locations in 11 administrative districts were paired with one self-complementary nitrate auxotroph tester-pair for each VCG. Atoxigenic VCGs accounted for 81.1% of the 153 positive complementations recorded. Genetic diversity of VCGs was highest in the derived savannah agro-ecological zone (H = 2.61) compared with the southern Guinea savannah (H = 1.90) and northern Guinea savannah (H = 0.94) zones. Genetic richness (H = 2.60) and evenness (E5  = 0.96) of VCGs were high across all agro-ecological zones. Ten VCGs (40%) had members restricted to the original location of isolation, whereas 15 VCGs (60%) had members located between the original source of isolation and a distance > 400 km away. The present study identified widely distributed VCGs in Nigeria such as AV0222, AV3279, AV3304 and AV16127, whose atoxigenic members can be deployed for a region-wide biocontrol of toxigenic isolates to reduce aflatoxin contamination in maize.

Quantifying the Effects of Wheat Residue on Severity of Stagonospora nodorum Blotch and Yield in Winter Wheat

Stagonospora nodorum blotch (SNB), caused by the fungus Parastagonospora nodorum, is a major disease of wheat (Triticum aestivum). Residue from a previously infected wheat crop can be an important source of initial inoculum, but the effects of infected residue on disease severity and yield have not previously been quantified. Experiments were conducted in Raleigh and Salisbury, North Carolina, in 2012, 2013, and 2014 using the moderately susceptible winter wheat cultivar DG Shirley. In 2014, the highly susceptible cultivar DG 9012 was added to the experiment and the study was conducted at an additional site in Tyner, North Carolina. Four (2012) or six (2013 and 2014) wheat residue treatments were applied in the field in a randomized complete block design with five replicates. Treatments in 2012 were 0, 30, 60, and 90% residue coverage of the soil surface, while 10 and 20% residue treatments were added in 2013 and 2014. Across site-years, disease severity ranged from 0 to 50% and increased nonlinearly (P < 0.05) as residue level increased, with a rapid rise to an upper limit and showing little change in severity above 20 to 30% soil surface coverage. Residue coverage had a significant (P < 0.05) effect on disease severity in all site-years. The effect of residue coverage on yield was only significant (P < 0.05) for DG Shirley at Raleigh and Salisbury in 2012 and for DG 9012 at Salisbury in 2014. Similarly, residue coverage significantly (P < 0.05) affected thousand-kernel weight only of DG 9012 in 2014 at Raleigh and Salisbury. Our results showed that when wheat residue was sparse, small additions to residue density produced greater increases in SNB than when residue was abundant. SNB only led to effects on yield and test weight in the most disease-conducive environments, suggesting that the economic threshold for the disease may be higher than previously assumed and warrants review.

Resurgence of Pseudoperonospora cubensis: The Causal Agent of Cucurbit Downy Mildew

The downy mildew pathogen, Pseudoperonospora cubensis, which infects plant species in the family Cucurbitaceae, has undergone major changes during the last decade. Disease severity and epidemics are far more destructive than previously reported, and new genotypes, races, pathotypes, and mating types of the pathogen have been discovered in populations from around the globe as a result of the resurgence of the disease. Consequently, disease control through host plant resistance and fungicide applications has become more complex. This resurgence of P. cubensis offers challenges to scientists in many research areas including pathogen biology, epidemiology and dispersal, population structure and population genetics, host preference, host-pathogen interactions and gene expression, genetic host plant resistance, inheritance of host and fungicide resistance, and chemical disease control. This review serves to summarize the current status of this major pathogen and to guide future management and research efforts within this pathosystem.

Epidemiology and population biology of Pseudoperonospora cubensis: a model system for management of downy mildews

The resurgence of cucurbit downy mildew has dramatically influenced production of cucurbits and disease management systems at multiple scales. Long-distance dispersal is a fundamental aspect of epidemic development that influences the timing and extent of outbreaks of cucurbit downy mildew. The dispersal potential of Pseudoperonospora cubensis appears to be limited primarily by sporangia production in source fields and availability of susceptible hosts and less by sporangia survival during transport. Uncertainty remains regarding the role of locally produced inoculum in disease outbreaks, but evidence suggests multiple sources of primary inoculum could be important. Understanding pathogen diversity and population differentiation is a critical aspect of disease management and an active research area. Underpinning advances in our understanding of pathogen biology and disease management has been the research capacity and coordination of stakeholders, scientists, and extension personnel. Concepts and approaches developed in this pathosystem can guide future efforts when responding to incursions of new or reemerging downy mildew pathogens.

Resurgence of Cucurbit Downy Mildew in the United States: A Watershed Event for Research and Extension

In 2004, an outbreak of cucurbit downy mildew (CDM) caused by the oomycete Pseudoperonospora cubensis (Berk. & M. A. Curtis) Rostovzev resulted in an epidemic that stunned the cucumber (Cucumis sativus L.) industry in the eastern United States. The disease affects all major cucurbit crops, including cucumber, muskmelon, squashes, and watermelon. Although the 2004 epidemic began in North Carolina, the cucumber crop from Florida to the northern growing regions in the United States was devastated, resulting in complete crop loss in several areas. Many cucumber fields were abandoned prior to harvest. The rapid spread of the disease coupled with the failure of fungicide control programs surprised growers, crop consultants, and extension specialists. The epidemic raised several fundamental questions about the potential causes for the resurgence of the disease. Some of these questions revolved around whether the epidemic would recur in subsequent years and the possible roles that changes in the host, pathogen, and environment may have played in the epidemic.

First Report of Pseudoperonospora cubensis Causing Downy Mildew on Momordica balsamina and M. charantia in North Carolina

Momordica balsamina (balsam apple) and M. charantia L. (bitter melon/bitter gourd/balsam pear) commonly grow in the wild in Africa and Asia; bitter melon is also cultivated for food and medicinal purposes in Asia (1). In the United States, these cucurbits grow as weeds or ornamentals. Both species are found in southern states and bitter melon is also found in Pennsylvania and Connecticut (3). Cucurbit downy mildew (CDM), caused by the oomycete Pseudoperonospora cubensis, was observed on bitter melon and balsam apple between August and October of 2013 in six North Carolina sentinel plots belonging to the CDM ipmPIPE program (2). Plots were located at research stations in Johnston, Sampson, Lenoir, Henderson, Rowan, and Haywood counties, and contained six different commercial cucurbit species including cucumbers, melons, and squashes in addition to the Momordica spp. Leaves with symptoms typical of CDM were collected from the Momordica spp. and symptoms varied from irregular chlorotic lesions to circular lesions with chlorotic halos on the adaxial leaf surface. Sporulation on the abaxial side of the leaves was observed and a compound microscope revealed sporangiophores (180 to 200 μm height) bearing lemon-shaped, dark sporangia (20 to 35 × 10 to 20 μm diameter) with papilla on one end. Genomic DNA was extracted from lesions and regions of the NADH dehydrogynase subunit 1 (Nad1), NADH dehydrogynase subunit 5 (Nad5), and internal transcribed spacer (ITS) ribosomal RNA genes were amplified and sequenced (4). BLAST analysis revealed 100% identity to P. cubensis Nad1 (HQ636552.1, HQ636551.1), Nad5 (HQ636556.1), and ITS (HQ636491.1) sequences in GenBank. Sequences from a downy mildew isolate from each Momordica spp. were deposited in GenBank as accession nos. KJ496339 through 44. To further confirm host susceptibility, vein junctions on the abaxial leaf surface of five detached leaves of lab-grown balsam apple and bitter melon were either inoculated with a sporangia suspension (10 μl, 10⁴ sporangia/ml) of a P. cubensis isolate from Cucumis sativus ('Vlaspik' cucumber), or with water as a control. Inoculated leaves were placed in humidity chambers to promote infection and incubated using a 12-h light (21°C) and dark (18°C) cycle. Seven days post inoculation, CDM symptoms and sporulation were observed on inoculated balsam apple and bitter melon leaves. P. cubensis has been reported as a pathogen of both hosts in Iowa (5). To our knowledge, this is the first report of P. cubensis infecting these Momordica spp. in NC in the field. Identifying these Momordica spp. as hosts for P. cubensis is important since these cucurbits may serve as a source of CDM inoculum and potentially an overwintering mechanism for P. cubensis. Further research is needed to establish the role of non-commercial cucurbits in the yearly CDM epidemic, which will aid the efforts of the CDM ipmPIPE to predict disease outbreaks. References: (1) L. K. Bharathi and K. J. John. Momordica Genus in Asia-An Overview. Springer, New Delhi, India, 2013. (2) P. S. Ojiambo et al. Plant Health Prog. doi:10.1094/PHP-2011-0411-01-RV, 2011. (3) PLANTS Database. Natural Resources Conservation Service, USDA. Retrieved from http://plants.usda.gov/ , 7 February 2014. (4) L. M. Quesada-Ocampo et al. Plant Dis. 96:1459, 2012. (5) USDA. Index of Plant Disease in the United States. Agricultural Handbook 165, 1960.

Use of Quantitative Traits to Assess Aggressiveness of Phakopsora pachyrhizi Isolates from Nigeria and the United States

Soybean rust, caused by Phakopsora pachyrhizi, is one of the most important foliar diseases of soybean worldwide. The soybean-P. pachyrhizi interaction is often complex due to genetic variability in host and pathogen genotypes. In a compatible reaction, soybean genotypes produce tan-colored lesions, whereas in an incompatible reaction soybean genotypes produce an immune response (complete resistance) or reddish-brown lesions (incomplete resistance). In this study, in total, 116 and 72 isolates of P. pachyrhizi from Nigeria and the United States, respectively, were compared based on six quantitative traits to assess their aggressiveness on two soybean genotypes. All isolates produced reddish-brown lesions on plant introduction (PI) 462312 and tan lesions on TGx 1485-1D. The number of days after inoculation to first appearance of lesions, uredinia, and sporulation, along with the number of lesions and sporulating uredinia per square centimeter of leaf tissue, and the number of uredinia per lesion, were significantly (P < 0.001) different between the two soybean genotypes for all isolates from each country. The number of days to first appearance of lesions, uredinia, and sporulation were greater on PI 462312 than on TGx 1485-1D for all the test isolates. Similarly, the number of lesions and sporulating uredinia per square centimeter, and the number of uredinia per lesion were lower on PI 462312 than on TGx 1485-1D. For both soybean genotypes, the number of sporulating uredinia per square centimeter significantly (P = 0.0001) increased with an increase in the number of lesions per square centimeter. Although the slope of the regression of sporulating uredinia on number of lesions was greater (P < 0.0001) when TGx 1485-1D was inoculated with Nigerian isolates compared with U.S. isolates, slopes of the regression lines did not differ significantly (P > 0.0675) when PI 46312 was inoculated with Nigerian or U.S. isolates. This is the first study that used a large number of isolates from two continents to assess aggressiveness of P. pachyrhizi using multiple traits in soybean genotypes with contrasting types of disease reaction.

Novel necrotrophic effectors from Stagonospora nodorum and corresponding host sensitivities in winter wheat germplasm in the southeastern United States

Stagonospora nodorum blotch (SNB), caused by the necrotrophic fungus Stagonospora nodorum (teleomorph: Phaeosphaeria nodorum), is among the most common diseases of winter wheat in the United States. New opportunities in resistance breeding have arisen from the recent discovery of several necrotrophic effectors (NEs, also known as host-selective toxins) produced by S. nodorum, along with their corresponding host sensitivity (Snn) genes. Thirty-nine isolates of S. nodorum collected from wheat debris or grain from seven states in the southeastern United States were used to investigate the production of NEs in the region. Twenty-nine cultivars with varying levels of resistance to SNB, representing 10 eastern-U.S. breeding programs, were infiltrated with culture filtrates from the S. nodorum isolates in a randomized complete block design. Three single-NE Pichia pastoris controls, two S. nodorum isolate controls, and six Snn-differential wheat controls were also used. Cultivar-isolate interactions were visually evaluated for sensitivity at 7 days after infiltration. Production of NEs was detected in isolates originating in each sampled state except Maryland. Of the 39 isolates, 17 produced NEs different from those previously characterized in the upper Great Plains region. These novel NEs likely correspond to unidentified Snn genes in Southeastern wheat cultivars, because NEs are thought to arise under selection pressure from genes for resistance to biotrophic pathogens of wheat cultivars that differ by geographic region. Only 3, 0, and 23% of the 39 isolates produced SnToxA, SnTox1, and SnTox3, respectively, by the culture-filtrate test. A Southern dot-blot test showed that 15, 74, and 39% of the isolates carried the genes for those NEs, respectively; those percentages were lower than those found previously in larger international samples. Only two cultivars appeared to contain known Snn genes, although half of the cultivars displayed sensitivity to culture filtrates containing unknown NEs. Effector sensitivity was more frequent in SNB-susceptible cultivars than in moderately resistant (MR) cultivars (P = 0.008), although some susceptible cultivars did not exhibit sensitivity to NEs produced by isolates in this study and some MR cultivars were sensitive to NEs of multiple isolates. Our results suggest that NE sensitivities influence but may not be the only determinant of cultivar resistance to S. nodorum. Specific knowledge of NE and Snn gene frequencies in this region can be used by wheat breeding programs to improve SNB resistance.

Interactive Effects of Temperature and Leaf Wetness Duration on Sporangia Germination and Infection of Cucurbit Hosts by Pseudoperonospora cubensis

Outbreaks of cucurbit downy mildew caused by Pseudoperonospora cubensis are dependent on the weather but effects of temperature and leaf wetness duration on infection have not been studied for different cucurbits. To determine the effects of these two weather variables on sporangia germination and infection of cucurbit host types by P. cubensis, three host types; cucumber ('Straight 8'), cantaloupe ('Kermit'), and acorn squash ('Table Queen'), were inoculated and exposed to leaf wetness durations of 2 to 24 h at six constant temperatures ranging from 5 to 30°C in growth-chamber experiments. Sporangia germination was assessed after each wetness period, and leaf area infected was assessed 5 and 7 days after inoculation. Germination of sporangia was highest on cantaloupe (16.5 to 85.7%) and lowest on squash (10.7 to 68.9%), while disease severity was highest and lowest on cucumber and cantaloupe, respectively. Host type, temperature, wetness duration and their interactions significantly (P < 0.0001) affected germination and disease severity. Germination and disease data for each host type were separately fitted to a modified form of a Weibull function that characterizes a unimodal response and monotonic increase of germination or infection with temperature and wetness duration, respectively. The effect of host type on germination and infection was characterized primarily by differences in the upper limit parameter in response to temperature. Differences among host types based on other parameters were either small or inconsistent. Temperature and wetness duration that supported a given level of germination or infection varied among host types. At 20°C, 15% leaf area infected was expected following 2, 4, and 8 h of wetness for cucumber, squash, and cantaloupe, respectively. When temperature was increased to 25°C, 15% disease severity was expected following 3, 7, and 15 h of wetness for cucumber, squash, and cantaloupe, respectively. Risk charts were constructed to estimate the potential risk of infection of cucurbit host types by P. cubensis based on prevailing or forecasted temperature and leaf wetness duration. These results will improve the timing and application of the initial fungicide spray for the control of cucurbit downy mildew.

A Degree-Day Model for the Latent Period of Stagonospora nodorum Blotch in Winter Wheat

Stagonospora nodorum blotch (SNB), which is caused by Stagonospora nodorum, occurs frequently in the southeastern United States, and severe epidemics can lead to substantial yield losses. To develop a model for the progress of SNB based on the effects of temperature on the latent period of the pathogen, batches of two winter wheat cultivars, AGS 2000 and USG 3209, were inoculated with S. nodorum at weekly intervals for 16 weeks. After 72 h of incubation, inoculated plants were exposed to outdoor conditions where temperatures ranged from -6.6 to 35.8°C, with a mean batch temperature ranging from 9.7 to 24.7°C. Latent period, expressed as time from inoculation until the first visible lesions with pycnidia, ranged from 13 to 34 days. The relationship between the inverse of the latent period and mean temperature was best described by a linear model, and the estimated thermal time required for the completion of the latent period was 384.6 degree-days. A shifted cumulative gamma distribution model with a base temperature of 0.5°C significantly (P < 0.0001) described the relationship between increasing number of lesions with pycnidia and accumulated thermal time. When latent period was defined as time to 50% of the maximum number of lesions with pycnidia (L50), the model estimated L50 as 336 and 326 degree-days above 0.5°C for AGS 2000 and USG 3209, respectively. The relationship between 1/L50 and mean temperature was also best described using a linear model (r² = 0.93, P < 0.001). This study provides data that link disease progress with wheat growth, which facilitates accurate identification of thresholds for timing of fungicide applications.

Spatiotemporal spread of cucurbit downy mildew in the eastern United States

The dynamics of cucurbit downy mildew, caused by Pseudoperonospora cubensis, in the eastern United States in 2008 and 2009 were investigated based on disease records collected in 24 states as part of the Cucurbit downy mildew ipmPIPE monitoring program. The mean season-long rate of temporal disease progress across the 2 years was 1.4 new cases per day. Although cucurbit downy mildew was detected in mid-February and early March in southern Florida, the disease progressed slowly during the spring and early summer and did not enter its exponential phase until mid-June. The median nearest-neighbor distance of spread of new disease cases was ≈110 km in both years, with ≈15% of the distances being >240 km. Considering disease epidemics on all cucurbits, the epidemic expanded at a rate of 9.2 and 10.5 km per day in 2008 and 2009, respectively. These rates of spatial spread are at the lower range of those reported for the annual spread of tobacco blue mold in the southeastern United States, a disease that is also aerially dispersed over long distances. These results suggest that regional spread of cucurbit downy mildew may be limited by opportunities for establishment in the first half of the year, when fewer cucurbit hosts are available for infection. The O-ring statistic was used to determine the spatial pattern of cucurbit downy mildew outbreaks using complete spatial randomness as the null model for hypothesis testing. Disease outbreaks in both years were spatially aggregated and the extent of spatial dependence was up to 1,000 km. Results from the spatial analysis suggests that disease outbreaks in the Great Lakes and mid-Atlantic regions may be due to the spread of P. cubensis sporangia from outbreaks of the disease near the Georgia/South Carolina/North Carolina border rather than from overwintering sites in southern Florida. Space-time point pattern analysis indicated strong (P < 0.001) evidence for a space-time interaction and a space-time risk window of ≈3 to 5 months after first disease outbreak and 300 to 600 km was detected in both years. Results of this study support the hypothesis that infection of cucurbits by P. cubensis appears to be an outcome of a contagion process, and the relative large space-time window suggests that factors occurring on a large spatial scale (≈1,000 km) facilitate the spread of cucurbit downy mildew in the eastern United States.

Dynamics of Soybean Rust Epidemics in Sequential Plantings of Soybean Cultivars in Nigeria

Soybean rust, caused by Phakopsora pachyrhizi, is an important foliar disease of soybean. Disease severity is dependent on several environmental factors, although the precise nature of most of these factors under field conditions is not known. To help understand the environmental factors that affect disease development, soybean rust epidemics were studied in Nigeria by sequentially planting an early-maturing, highly susceptible cultivar, TGx 1485-1D, and a late-maturing, moderately susceptible cultivar, TGx 1448-2E, at 30- to 45-day intervals from August 2004 to September 2006. Within each planting date, disease onset occurred earlier on TGx 1485-1D than on TGx 1448-2E, and rust onset was at least 20 days earlier on soybean planted between August and October than on soybean planted between November and April. The logistic model provided a better description of the temporal increase in rust severity than the Gompertz model. Based on the logistic model, the highest absolute rates of disease increase were observed on soybean planted in September 2006 and October 2004 for TGx 1485-1D and TGx 1448-2E, respectively. Disease severity as measured by the relative area under disease progress curve (RAUDPC) was significantly (P < 0.05) negatively correlated with evaporation (r = -0.73), solar radiation (r = -0.59), and temperature (r = -0.64) but positively correlated with urediniospore concentration (r = 0.58). Planting date and soybean cultivar significantly (P < 0.05) affected disease severity, with severity being higher on soybean crops planted during the wet season than those planted in the dry season. Within the wet season, planting in May and July resulted in a significantly (P < 0.05) lower RAUDPC than planting between August and October. Yields were significantly (P < 0.001) related to RAUDPC during the wet season, whereby an increase in RAUDPC resulted in a linear decrease in yield. This study suggests that selection of planting date could be a useful cultural practice for reducing soybean rust.

A quantitative review of fungicide efficacy for managing downy mildew in cucurbits

A meta-analysis of the effect of fungicides on cucurbit downy mildew was conducted using data previously published in Fungicide & Nematicide Tests and Plant Disease Management Reports from 2000 to 2008. Standardized mean effect size (the difference in disease intensity expressed in standard deviation units between the fungicide treatment and its corresponding untreated control) was calculated for each of the 105 field studies evaluating the effects of fungicides on cucurbit downy mildew. Fixed- and random-effects meta-analyses were performed on the log-transformed standardized mean effect sizes to estimate the overall mean effect size (L+), and to determine the variability in the effect size among studies. Fungicides led to a significant (P<0.001) reduction in disease with an L+ value of 1.198, indicating that, overall, fungicides were highly effective against cucurbit downy mildew. Fixed- and random-effects meta-analyses were then conducted to determine the effects of moderator variables on L+. The fixed-effects model resulted in narrower 95% confidence intervals and generally lower estimates of moderator subgroup mean effect size (L) than the random-effects models. Fungicide efficacy was significantly (P<0.001) greater in cucumber, with L being 26.5% higher in cucumber than in other cucurbits. Year of study, number of sprays, and disease pressure in the control significantly (P<0.001) affected L. Fungicide efficacy was significantly lower during the 2004-05 season than prior to or after the 2004-05 season. Studies in which disease pressure was moderate had a significantly higher L than studies with either low or high disease pressure. Fungicide efficacy was ≥22% in studies that received 5 to 6 sprays than in studies that received 1 to 4 or >6 sprays. Fungicide products led to a significant (P<0.001) reduction in disease, although there was substantial between-study variability. The pyridinylmethyl-benzamide group of fungicides (fluopicolide) was the most effective, followed by the carbamate (propamocarb) and quinone inside inhibitors (cyazofamid) group of fungicides, while the carboxylic acid amide group (mandipropamid and dimethomorph) was the least effective. A combination of protectant and systemic fungicides resulted in a proportional increase in L compared with sole application of either protectant or systemic fungicides.

Quantitative models for germination and infection of Pseudoperonospora cubensis in response to temperature and duration of leaf wetness

The influence of temperature and leaf wetness duration on germination of sporangia and infection of cantaloupe leaves by Pseudoperonospora cubensis was examined in three independent controlled-environment experiments by inoculating plants with a spore suspension and exposing them to a range of leaf wetness durations (2 to 24 h) at six fixed temperatures (5 to 30 degrees C). Germination of sporangia was assessed at the end of each wetness period and infection was evaluated from assessments of disease severity 5 days after inoculation. Three response surface models based on modified forms of the Weibull function were evaluated for their ability to describe germination of sporangia and infection in response to temperature and leaf wetness duration. The models estimated 15.7 to 17.3 and 19.5 to 21.7 degrees C as the optimum temperature (t) range for germination and infection, respectively, with little germination or infection at 5 or 30 degrees C. For wetness periods of 4 to 8 h, a distinct optimum for infection was observed at t = 20 degrees C but broader optimum curves resulted from wetness periods >8 h. Model 1 of the form f(w,t) = f(t) x (1 - exp{-[B x w](D)}) resulted in smaller asymptotic standard errors and yielded higher correlations between observed and predicted germination and infection data than either model 2 of the form f(w,t) = A{1 - exp[- f(t) x (w - C)](D)} or model 3 of the form f(w,t) = [1 - exp{-(B x w)(2)}]/cosh[(t - F)G/2]. Models 1 and 2 had nonsignificant lack-of-fit test statistics for both germination and infection data, whereas a lack-of-fit test was significant for model 3. The models accounted for approximately 87% (model 3) to 98% (model 1) of the total variation in the germination and infection data. In the validation of the models using data generated with a different isolate of P. cubensis, slopes of the regression line between observed and predicted germination and infection data were not significantly different (P > 0.2487) and correlation coefficients between observed and predicted values were high (r(2) > 0.81). Models 1 and 2 were used to construct risk threshold charts that can be used to estimate the potential risk for infection based on observed or forecasted temperature and leaf wetness duration.

Efficiency of adaptive cluster sampling for estimating plant disease incidence

Conventional sampling designs such as simple random sampling (SRS) tend to be inefficient when assessing rare and highly clustered populations because most of the time is spent evaluating empty quadrats, leading to high error variances and high cost. In previous studies with rare plant and animal populations, adaptive cluster sampling, where sampling occurs preferentially in the neighborhood of quadrats in which the species of interest is detected during the sampling bout, has been shown to estimate population parameters with greater precision at an effort comparable to SRS. Here, we use computer simulations to evaluate the efficiency of adaptive cluster sampling for estimating low levels of disease incidence (0.1, 0.5, 1.0, and 5.0%) at various levels of aggregation of infected plants having variance-to-mean ratios (V/M) of approximately 1, 3, 5, and 10. For each simulation, an initial sample size of 50, 100, and 150 quadrats was evaluated, and the condition to adapt neighborhood sampling (CA), i.e., the minimum number of infected plants per quadrat that triggers a switch from random sampling to sampling in neighboring quadrats, was varied from 1 to 4 (corresponding to 7.7 to 30.8% incidence of infected plants per quadrat). The simulations showed that cluster sampling was consistently more precise than SRS at a field-level disease incidence of 0.1 and 0.5%, especially when diseased plants were highly aggregated (V/M = 5 or 10) and when the most liberal condition to adapt (CA = 1) was used. One drawback of adaptive cluster sampling is that the final sample size is unknown at the beginning of the sampling bout because it depends on how often neighborhood sampling is triggered. In our simulations, the final sample size was close to the initial sample size for disease incidence up to 1.0%, especially when a more conservative condition to adapt (CA > 1) was used. For these conditions, the effect of disease aggregation was minor. In summary, both precision and the sample size required with adaptive cluster sampling responded similarly to disease incidence and aggregation, i.e., both were most favorable at the lowest disease incidence with the highest levels of clustering. However, whereas relative precision was optimized with the most liberal condition to adapt, the ratio of final to initial sample size was best for more conservative CA values, indicating a tradeoff. In our simulations, precision and final sample size were both simultaneously favorable for disease incidence of up to 1.0%, but only when infected plants were most aggregated (V/M = 10).

Pathogenic variation of Phakopsora pachyrhizi infecting soybean in Nigeria

Soybean rust, caused by Phakopsora pachyrhizi, is an important disease in Nigeria and many other soybean-producing countries worldwide. To determine the geographical distribution of soybean rust in Nigeria, soybean fields were surveyed in the Derived Savanna (DS), Northern Guinea Savanna (NGS), and Southern Guinea Savanna (SGS) agroecological zones in Nigeria between 2004 and 2006. Disease severity in each zone was determined and analyzed using geostatistics. Prevalence of infected fields and disease severity in surveyed fields were significantly (P < 0.05) different between geographical zones with both variables being higher in the DS zone than in either NGS or SGS zones. Geostatistical analysis indicated that the spatial influence of disease severity at one location on severity at other locations was between 75 and 120 km. An exponential model best described the relationship between semivariance and lag distance when rust severity was high. Spatial interpolation of rust severity showed that locations in the DS zone were more conducive for the rust epidemic compared to areas in the NGS zone. In the 2005 survey, 116 purified isolates were established in culture on detached soybean leaves. To establish the nature of pathogenic variation in P. pachyrhizi, a set of four soybean accessions with Rpp(1), Rpp(2), Rpp(3), and Rpp(4) resistance genes, two highly resistant and two highly susceptible genotypes were inoculated with single uredinial isolates. Principal component analysis on the number of uredinia per square centimeter of leaf tissue for 116 isolates indicated that an adequate summary of pathogenic variation was obtained using only four genotypes. Of these four, PI 459025B (with Rpp(4) gene) and TGx 1485-1D had the lowest and highest number of uredinia per square centimeter, respectively. Based on cluster analysis of the number of uredinia per square centimeter, seven pathotype clusters were determined. Isolates in cluster III were the most virulent, while those in cluster IV were the least virulent. Shannon's index (H) revealed a more diverse pathogen population in the DS zone (H = 1.21) compared to the rust population in SGS and NGS with H values of 1.08 and 0.91, respectively. This work will be useful in breeding and management of soybean rust by facilitating identification of resistant genotypes and targeting cultivars with specific resistance to match prevailing P. pachyrhizi pathotypes in a given geographical zone.

Evaluation of Soybean Germplasm for Resistance to Soybean Rust (Phakopsora pachyrhizi) in Nigeria

Soybean rust, caused by Phakopsora pachyrhizi, is one of the most important constraints to soybean production worldwide. The absence of high levels of host resistance to the pathogen has necessitated the continued search and identification of sources of resistance. In one set of experiments, 178 soybean breeding lines from the International Institute of Tropical Agriculture were rated for rust severity in the field in 2002 and 2003 at Ile-Ife, Yandev, and Ibadan, Nigeria. Thirty-six lines with disease severity ≤3 (based on a 0-to-5 scale) were selected for a second round of evaluation in 2004 at Ibadan. In the third round of evaluation under inoculated field conditions, 11 breeding lines with disease severity ≤2 were further evaluated for rust resistance at Ibadan in 2005 and 2006. The breeding lines TGx 1835-10E, TGx 1895-50F, and TGx 1903-3F consistently had the lowest level of disease severity across years and locations. In another set of experiments, 101 accessions from the United States Department of Agriculture-Agricultural Research Service and National Agriculture Research Organization (Uganda) were evaluated in the first round in 2005 under inoculated conditions in the screenhouse; 12 accessions with disease severity ≤20% leaf area infected were selected for evaluation in the second round in 2005 and 2006 under inoculated field conditions at Ibadan. Highly significant differences (P < 0.0001) in disease severity were observed among the 101 accessions during this first round of rust evaluation. Significant (P < 0.0001) differences in rust severity and sporulation also were observed among the 12 selected accessions. Accessions PI 594538A, PI 417089A, and UG-5 had significantly (P < 0.05) lower disease severity than all other selected accessions in both years of evaluation, with rust severities ranging from 0.1 to 2.4%. These results indicate that some of the breeding lines (TGx 1835-10E, TGx 1895-50F, and TGx 1903-3F) and accessions (PI 594538A, PI 417089A, and UG-5) would be useful sources of soybean rust resistance genes for incorporation into high-yielding and adapted cultivars.

Novel Sources of Resistance to Fusarium Stalk Rot of Maize in Tropical Africa

Fusarium stalk rot is one of the most widespread and destructive diseases of maize, and deployment of resistant genotypes is one of the most effective strategies for controlling the disease. Fifty inbred lines and four checks from the breeding program of the International Institute of Tropical Agriculture were evaluated in field trials at Ikenne and Ibadan, Nigeria in 2003 and 2004 to identify new sources of resistance to stalk rot caused by Fusarium verticillioides. Evaluations were conducted under artificial inoculation and natural infection at Ibadan and Ikenne, respectively. Disease severity was recorded using a severity scale (SS) and direct estimation of stalk discoloration (SD). The two methods of disease assessment were compared and combined to classify genotypes into resistance groups using results from rank-sum analysis. In 2003, disease severity ranged from SS = 1 to 5 and SD = 1.3 to 33.8% at both locations. Both SS and SD were significantly (P < 0.01) higher in 2003 than in 2004 at the two locations. In both years, inbred lines significantly differed in SS (P < 0.02) and SD (P < 0.04) at Ibadan. Similarly, inbred lines significantly differed in SS (P < 0.04) and SD (P < 0.04) when genotypes were evaluated at Ikenne. Disease assessments based on SS and SD were significantly correlated (0.68 < r < 0.95, P < 0.01) in both years. Based on the results from rank-sum analysis, inbred lines were separated into highly resistant, resistant, moderately resistant, moderately susceptible, susceptible, and highly susceptible groups. At Ibadan, 6 (11.1%) and 8 (14.8%) were identified as highly resistant and resistant, respectively, whereas 11 (20.4%) were identified as resistant at Ikenne. Inbred lines 02C14609, 02C14643, 02C14654, and 02C14678 were consistently classified as either highly resistant or resistant to stalk rot across locations and years while the check genotypes were classified either as susceptible or moderately susceptible to stalk rot. These four inbred lines identified to have high levels of disease resistance may be used for breeding maize with resistance to Fusarium stalk rot.

Distribution and toxigenicity of Aspergillus species isolated from maize kernels from three agro-ecological zones in Nigeria

Maize samples were collected during a survey in three agro-ecological zones in Nigeria to determine the distribution and aflatoxin-producing potential of members of Aspergillus section Flavi. The three agro-ecological zones were, Derived Savannah (DS) and Southern Guinea Savannah (SGS) in the humid south and North Guinea Savannah (NGS) in the drier north. Across agro-ecological zones, Aspergillus was the most predominant fungal genera identified followed by Fusarium with mean incidences of 70 and 24%, respectively. Among Aspergillus, A. flavus was the most predominant and L-strains constituted >90% of the species identified, while the frequency of the unnamed taxon S(BG) was <3%. The incidence of atoxigenic strains of A. flavus was higher in all the districts surveyed except in the Ogbomosho and Mokwa districts in DS and SGS zones, respectively, where frequency of toxigenic strains were significantly (P<0.05) higher than that of atoxigenic strains. The highest and lowest incidence of aflatoxin positive samples was recorded in the SGS (72%) and NGS (20%), respectively. Aflatoxin contamination in grain also followed a similar trend and the highest mean levels of B-aflatoxins were detected in maize samples obtained from Bida (612 ng g(-1)) and Mokwa (169 ng g(-1)) districts, respectively, in the SGS. Similarly, the highest concentrations of G-aflatoxins were detected in samples from Akwanga district in the SGS with a mean of 193 and 60 ng g(-1), respectively. When agro-ecological zones were compared, B-aflatoxins were significantly (P<0.05) higher in SGS than in NGS, and intermediate in maize samples from the DS agro-ecological zone.

First Report of Rust Caused by Phakopsora pachyrhizi on Soybean in Democratic Republic of Congo

Nigeria (1) and Uganda (3) are the closest countries to the Democratic Republic of Congo (DRC) where soybean rust caused by Phakopsora pachyrhizi has been reported. In February 2007, during a disease survey in DRC, soybean (Glycine max) leaves with rust symptoms (tan, angular lesions with erumpent sori exuding urediniospores) were observed in 10 fields in the following areas in Bas Congo Province: Bangu, Kimpese, Kolo-Fuma, Lukala, Mbanza-Ngungu, Mpalukide, Mvuazi, and Ntemo. Rust incidence in these fields ranged from 85 to 100%, while severity ranged between 3 and 35% of the leaf area on infected plants. Urediniospores were hyaline, minutely echinulate, and 23 to 31 × 16 to 20 μm. Within a week of collection, infected leaf samples were sent to the USDA-ARS Foreign Disease-Weed Science Research Unit (FDWSRU) for pathogen identification. DNA was extracted from sections of leaves containing sori with the Qiagen DNeasy Plant Mini kit (Valencia, CA), and all 10 field samples amplified in a real-time fluorescent PCR with the P. pachyrhizi-specific primers Ppm1 and Ppa2 (2). Infected leaves of cultivar Vuangi collected from one field each in the INERA Research Station, Kimpese-Crawford, and Kimpese-Ceco were separately washed in sterile water to collect urediniospores that were used to separately inoculate three detached leaves of susceptible cultivar TGx 1485-1D (4). Lesions on inoculated leaves developed 5 days after inoculation (DAI), and pustules (110 to 130 μm) formed 7 DAI and erupted 2 days later exuding columns of urediniospores similar in size to the initially collected isolates. Inoculation of another set of detached leaves with a spore suspension (1 × 10⁶ spores per ml) from the first set of detached leaves resulted in typical rust symptoms. Seedlings of cultivar Williams also showed typical rust symptoms when inoculated separately with urediniospores collected from nine fields (i.e., all except Kimpese-Ceco, which was infective in the detached leaf assay). Inoculation and incubation were carried out at the FDWSRU Plant Pathogen Containment Facility at Fort Detrick as described earlier (2). The PCR assay, morphological characters of the isolates, and pathogenicity tests demonstrate that P. pachyrhizi occurs in DRC. To our knowledge, this is the first report of P. pachyrhizi infecting soybean in DRC. References: (1) O. A. Akinsanmi et al. Plant Dis. 85:97, 2001. (2) R. D. Frederick et al. Phytopathology 92:217, 2002. (3) E. Kawuki et al. J. Phytopathol. 151:7, 2003. (4) M. Twizeyimana et al. Online publication. http://www.plantmanagementnetwork.org/ infocenter/topic/soybeanrust/2006/posters/41.asp. Plant Management Network, 2006.

Comparison of Field, Greenhouse, and Detached-Leaf Evaluations of Soybean Germplasm for Resistance to Phakopsora pachyrhizi

Fourteen soybean accessions and breeding lines were evaluated for resistance to soybean rust caused by the fungus Phakopsora pachyrhizi. Evaluations were conducted in replicated experiments in growth chambers using detached leaves and under greenhouse and field conditions. In growth-chamber experiments, inoculation of detached leaves with 1 × 10⁶ spores/ml resulted in a significantly (P < 0.0001) higher total number of pustules and spores per unit leaf area than inoculations with lower spore concentrations. Amending agar medium with plant hormones significantly (P < 0.0001) aided retention of green leaf color in detached leaves. Leaf pieces on a medium containing kinetin at 10 mg/liter had 5% chlorosis at 18 days after plating compared with leaf pieces on media amended with all other plant hormones, which had higher levels of chlorosis. Leaf age significantly affected number of pustules (P = 0.0146) and number of spores per pustule (P = 0.0088), and 3- to 4-week-old leaves had a higher number of pustules and number of spores per pustule compared with leaves that were either 1 to 2 or 5 to 6 weeks old. In detached-leaf and greenhouse screening, plants were evaluated for days to lesion appearance, days to pustule formation, days to pustule eruption, lesion number, lesion diameter, lesion type, number of pustules, and spores per pustule in 1-cm² leaf area. Plants also were evaluated for diseased leaf area (in greenhouse and field screening) and sporulation (in field screening) at growth stage R6. There were significant (P < 0.0001) differences among genotypes in their response to P. pachyrhizi infection in the detached-leaf, greenhouse, and field evaluations. Accessions PI 594538A, PI 417089A, and UG-5 had very low levels of disease compared with the susceptible checks and all other genotypes. Detached-leaf, greenhouse, and field results were comparable, and there were significant correlations between detached-leaf and greenhouse (absolute r = 0.79; P < 0.0001) and between detached-leaf and field resistance (absolute r = 0.83; P < 0.0001) across genotypes. The overall results show the utility of detached-leaf assay for screening soybean for rust resistance.