New applications of statistical tools in plant pathology

Biocontrol Agents of Fusarium Head Blight in Wheat: A Meta-Analytic Approach to Elucidate Their Strengths and Weaknesses

The use of biocontrol agents (BCAs) coping with fungal pathogens causing Fusarium head blight (FHB) is a compelling strategy for disease management, but a better elucidation of their effectiveness is crucial. Meta-analysis is the analysis of the results of multiple studies, which is typically performed to synthesize evidence from many possible sources in a formal probabilistic manner. This meta-analytic study, including 30 pathometric, biometric, physiochemical, genetic, and mycotoxin response variables reported in 56 studies, evidences the BCA effects on FHB in wheat. The effectiveness of BCAs of FHB in wheat in terms of pathogen abundance and disease reductions, biomass and yield conservation, and mycotoxin prevention/control was confirmed. BCAs showed higher efficacy (i) in studies published more recently; (ii) under controlled conditions; (iii) in high susceptible wheat cultivars; (iv) when Fusarium inoculation and BCA treatment did not occur directly on the plant (i.e., at the seed and kernel levels) in terms of disease development and mycotoxin control, and vice versa in terms of biomass conservation; (v) if Fusarium inoculation and BCA treatment occurred by spraying spikes in terms of yield; (vi) at 15 to 21 days post Fusarium inoculation or BCA treatment; and (vii) if they were filamentous fungi. However, BCAs overall were less efficacious than conventional agrochemicals, especially in terms of pathogen abundance and FHB reductions, as well as of mycotoxin prevention/control, although inconsistencies were reported among the investigated moderator variables. This study also highlights the complexity of reaching a good balance among BCA effects, and the need for further research.

Plant Disease Models and Forecasting: Changes in Principles and Applications Over the Last 50 Years

This review gives a perspective of selected advances made since the middle of the 20th century in plant disease modeling, and the associated increase in the number of models published during that time frame. This progress can be mainly attributed to advances in (i) sensors and automatic environmental data collection technology, (ii) instrumentation and methods for studying botanical epidemiology, and (iii) data analytics and computer science. We review the evolution of techniques for developing data-based (empirical) models and process-based (mechanistic) models using the wheat rusts as a case study. We also describe the increased importance of knowledge about biological processes for plant disease modeling by using apple scab as a second case study. For both wheat rusts and apple scab, we describe how the models have evolved over the last 50 years by considering certain milestones that have been achieved in disease modeling. Finally, we describe how plant disease models are used as part of a multi-modeling approach to develop decision-making tools in the application of integrated pest management.

Evaluation of the Characteristics and Infectivity of the Secondary Inoculum Produced by Plasmopara viticola on Grapevine Leaves by Means of Flow Cytometry and Fluorescence-Activated Cell Sorting

Plasmopara viticola, the oomycete causing grapevine downy mildew, is one of the most important pathogens in viticulture. P. viticola is a polycyclic pathogen, able to carry out numerous secondary cycles of infection during a single vegetative grapevine season, by producing asexual spores (zoospores) within sporangia. The extent of these infections is strongly influenced by both the quantity (density) and quality (infectivity) of the inoculum produced by the pathogen. To date, the protocols for evaluating all these characteristics are quite limited and time-consuming and do not allow all the information to be obtained in a single run. In this study, a protocol combining flow cytometry (FCM) and fluorescence-activated cell sorting (FACS) was developed to investigate the composition, the infection efficiency and the dynamics of the inoculum produced by P. viticola for secondary infection cycles. In our analyses, we identified different structures within the inoculum, including degenerated and intact sporangia. The latter have been sorted, and single sporangia were directly inoculated on grapevine leaf discs, thus allowing a thorough investigation of the infection dynamics and efficiency. In detail, we determined that, in our conditions, 8% of sporangia were able to infect the leaves and that on a susceptible variety, the time required by the pathogen to reach 50% of total infection is about 10 days. The analytical approach developed in this study could open a new perspective to shed light on the biology and epidemiology of this important pathogen. IMPORTANCE P. viticola secondary infections contribute significantly to the epidemiology of this important plant pathogen. However, the infection dynamics of asexual spores produced by this organism are still poorly investigated. The main challenges in dissecting the grapevine-P. viticola interaction in vitro are attributable to the biotrophic adaptation of the pathogen. This work provides new insights into the infection efficiency and dynamics imputable to P. viticola sporangia, contributing useful information on grapevine downy mildew epidemiology. Moreover, future applications of the sorting protocol developed in this work could yield a significant and positive impact in the study of P. viticola, providing unmatched resolution, precision, and accuracy compared with the traditional techniques.

Intraspecific Growth and Aflatoxin Inhibition Responses to Atoxigenic Aspergillus flavus: Evidence of Secreted, Inhibitory Substances in Biocontrol

The fungus Aspergillus flavus infects corn, peanut, and cottonseed, and contaminates seeds with acutely poisonous and carcinogenic aflatoxin. Aflatoxin contamination is a perennial threat in tropical and subtropical climates. Nonaflatoxin-producing isolates (atoxigenic) are deployed in fields to mitigate aflatoxin contamination. The biocontrol competitively excludes toxigenic A. flavus via direct replacement and thigmoregulated (touch) toxin inhibition mechanisms. To understand the broad-spectrum toxin inhibition, toxigenic isolates representing different mating types and sclerotia sizes were individually cocultured with different atoxigenic biocontrol isolates. To determine whether more inhibitory isolates had a competitive advantage to displace or touch inhibit toxigenic isolates, biomass accumulation rates were determined for each isolate. Finally, to determine whether atoxigenic isolates could inhibit aflatoxin production without touch, atoxigenic isolates were grown separated from a single toxigenic isolate by a membrane. Atoxigenic isolates 17, Af36, and K49 had superior abilities to inhibit toxin production. Small (<400 µm) sclerotial, Mat1-1 isolates were not as completely inhibited as others by most atoxigenic isolates. As expected for both direct replacement and touch inhibition, the fastest-growing atoxigenic isolates inhibited aflatoxin production the most, except for atoxigenic Af36 and K49. Aflatoxin production was inhibited when toxigenic and atoxigenic isolates were grown separately, especially by slow-growing atoxigenic Af36 and K49. Additionally, fungus-free filtrates from atoxigenic cultures inhibited aflatoxin production. Toxin production inhibition without direct contact revealed secretion of diffusible chemicals as an additional biocontrol mechanism. Biocontrol formulations should be improved by identifying isolates with broad-spectrum, high-inhibition capabilities and production of secreted inhibitory chemicals.

Synergistic interaction between the type III secretion system of the endophytic bacterium Pantoea agglomerans DAPP-PG 734 and the virulence of the causal agent of olive knot Pseudomonas savastanoi pv. savastanoi DAPP-PG 722

The endophytic bacterium Pantoea agglomerans DAPP-PG 734 was previously isolated from olive knots caused by infection with Pseudomonas savastanoi pv. savastanoi DAPP-PG 722. Whole-genome analysis of this P. agglomerans strain revealed the presence of a Hypersensitive response and pathogenicity (Hrp) type III secretion system (T3SS). To assess the role of the P. agglomerans T3SS in the interaction with P. savastanoi pv. savastanoi, we generated independent knockout mutants in three Hrp genes of the P. agglomerans DAPP-PG 734 T3SS (hrpJ, hrpN, and hrpY). In contrast to the wildtype control, all three mutants failed to cause a hypersensitive response when infiltrated in tobacco leaves, suggesting that P. agglomerans T3SS is functional and injects effector proteins in plant cells. In contrast to P. savastanoi pv. savastanoi DAPP-PG 722, the wildtype strain P. agglomerans DAPP-PG 734 and its Hrp T3SS mutants did not cause olive knot disease in 1-year-old olive plants. Coinoculation of P. savastanoi pv. savastanoi with P. agglomerans wildtype strains did not significantly change the knot size, while the DAPP-PG 734 hrpY mutant induced a significant decrease in knot size, which could be complemented by providing hrpY on a plasmid. By epifluorescence microscopy and confocal laser scanning microscopy, we found that the localization patterns in knots were nonoverlapping for P. savastanoi pv. savastanoi and P. agglomerans when coinoculated. Our results suggest that suppression of olive plant defences mediated by the Hrp T3SS of P. agglomerans DAPP-PG 734 positively impacts the virulence of P. savastanoi pv. savastanoi DAPP-PG 722.

Assessing the Curative and Protective Impacts of Select Fungicides for Control of Powdery Mildew of Wheat

Powdery mildew, caused by the obligate fungal pathogen Blumeria graminis, has been increasing in incidence and severity on wheat in the Chesapeake Bay region of the mid-Atlantic United States. Although fungicides are used for in-season management of powdery mildew, no studies to date have assessed the ability of these products to control disease after pathogen arrival/infection (curative activity) and the duration of disease control provided after fungicide application (protective activity) under controlled conditions. Five commercially available fungicide products, including Caramba, Stratego YLD, Priaxor, Prosaro, and Trivapro, were applied at either 3 or 5 days after inoculation with B. graminis spores to assess curative activity. In a separate study, protective activity for these fungicides was assessed by applying fungicides and inoculating with B. graminis spores the same day and 21 and 42 days after fungicide application. All fungicides reduced powdery mildew severity on foliage compared with nontreated controls. Priaxor provided 11 to 18% less activity than other fungicides when applied curatively. All products provided protective control up to 42 days after inoculation, with Stratego YLD and Priaxor providing the greatest level of control at 68 and 56%, respectively. Our data indicate that different fungicides can have subtle differences in overall efficacy profiles that may translate to improved control or an extended control window in some situations, but all tested products provide very good to excellent control of powdery mildew on wheat.

Case Study of an Epidemiological Approach Dissecting Historical Soybean Sclerotinia Stem Rot Observations and Identifying Environmental Predictors of Epidemics and Yield Loss

Sclerotinia sclerotiorum is a significant threat to soybean production worldwide. In this study, an epidemiological approach was used to examine 11 years of historical data from a soybean management performance trial in order to advance our understanding of Sclerotinia stem rot (SSR) development and to identify environmental predictors of SSR epidemics and associated yield losses. Recursive partitioning analysis suggested that average air temperature and total precipitation in July were the most significant variables associated with disease severity. High levels of SSR disease severity index were observed when the average temperature in July was below 19.5°C and total precipitation in July was moderate, between 20 and 108.5 mm. A biphasic sigmoidal curve accurately described the relationship between SSR disease severity index (DSI) and yield, with a DSI threshold of 22, below which minimal yield loss was observed. A 10% increase in the DSI, from 22.0 to 24.2, led to an 11% decrease in yield, from 3,308.14 to 2,951.29 kg/ha. Also, a yield threshold (3,353 kg/ha) that was higher than the annual U.S. average soybean yield (3,039.7 kg/ha) was suggested as an expected yield under low or no SSR pressure in the U.S. Midwest. These thresholds can allow soybean stakeholders to assess the value of disease control and establish an SSR baseline for cost-effective management to protect yields. Because S. sclerotiorum has more than 400 plant host species, and because having quantitative information concerning crop losses is crucial for decision making, this study shows the usefulness of historical data on SSR and, hence, can serve as a model in other SSR pathosystems (canola, dry bean, potato, pea, and so on).

Effects of microclimatic variables on the symptoms and signs onset of Moniliophthora roreri, causal agent of Moniliophthora pod rot in cacao

Moniliophthora Pod Rot (MPR) caused by the fungus Moniliophthora roreri (Cif.) Evans et al., is one of the main limiting factors of cocoa production in Latin America. Currently insufficient information on the biology and epidemiology of the pathogen limits the development of efficient management options to control MPR. This research aims to elucidate MPR development through the following daily microclimatic variables: minimum and maximum temperatures, wetness frequency, average temperature and relative humidity in the highly susceptible cacao clone Pound-7 (incidence = 86% 2008-2013 average). A total of 55 cohorts totaling 2,268 pods of 3-10 cm length, one to two months of age, were tagged weekly. Pods were assessed throughout their lifetime, every one or two weeks, and classified in 3 different categories: healthy, diseased with no sporulation, diseased with sporulating lesions. As a first step, we used Generalized Linear Mixed Models (GLMM) to determine with no a priori the period (when and for how long) each climatic variable was better related with the appearance of symptoms and sporulation. Then the significance of the candidate variables was tested in a complete GLMM. Daily average wetness frequency from day 14 to day 1, before tagging, and daily average maximum temperature from day 4 to day 21, after tagging, were the most explanatory variables of the symptoms appearance. The former was positively linked with the symptoms appearance when the latter exhibited a maximum at 30°C. The most important variables influencing sporulation were daily average minimum temperature from day 35 to day 58 and daily average maximum temperature from day 37 to day 48, both after tagging. Minimum temperature was negatively linked with the sporulation while maximum temperature was positively linked. Results indicated that the fungal microclimatic requirements vary from the early to the late cycle stages, possibly due to the pathogen's long latent period. This information is valuable for development of new conceptual models for MPR and improvement of control methods.

Effects of Temperature Stresses on the Resistance of Chickpea Genotypes and Aggressiveness of Didymella rabiei Isolates

Chickpea (Cicer arietinum L.) is an important food and rotation crop in many parts of the world. Cold (freezing and chilling temperatures) and Ascochyta blight (Didymella rabiei) are the major constraints in chickpea production. The effects of temperature stresses on chickpea susceptibility and pathogen aggressiveness are not well documented in the Cicer-Didymella pathosystem. Two experiments were conducted under controlled conditions using chickpea genotypes and pathogen isolates in 2011 and 2012. In Experiment 1, four isolates of D. rabiei (AR-01, AR-02, AR-03 and AR-04), six chickpea genotypes (Ghab-1, Ghab-2, Ghab-3, Ghab-4, Ghab-5 and ICC-12004) and four temperature regimes (10, 15, 20, and 25°C) were studied using 10 day-old seedlings. In Experiment 2, three chickpea genotypes (Ghab-1, Ghab-2, and ICC-12004) were exposed to 5 and 10 days of chilling temperature exposure at 5°C and non-exposed seedlings were used as controls. Seedlings of the three chickpea genotypes were inoculated with the four pathogen isolates used in Experiment 1. Three disease parameters (incubation period, latent period and disease severity) were measured to evaluate treatment effects. In Experiment 1, highly significant interactions between genotypes and isolates; genotypes and temperature; and isolate and temperature were observed for incubation and latent periods. Genotype x isolate and temperature x isolate interactions also significantly affected disease severity. The resistant genotype ICC-12004 showed long incubation and latent periods and low disease severity at all temperatures. The highly aggressive isolate AR-04 caused symptoms, produced pycnidia in short duration as well as high disease severity across temperature regimes, which indicated it is adapted to a wide range of temperatures. Short incubation and latent periods and high disease severity were observed on genotypes exposed to chilling temperature. Our findings showed that the significant interactions of genotypes and isolates with temperature did not cause changes in the rank orders of the resistance of chickpea genotypes and aggressiveness of pathogen isolates. Moreover, chilling temperature predisposed chickpea genotypes to D. rabiei infection; developing multiple stress resistance is thus a pre-requisite for the expansion of winter-sown chickpea in West Asia and North Africa.

Modelling survival: exposure pattern, species sensitivity and uncertainty

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

Computationally Efficient Implementation of a Novel Algorithm for the General Unified Threshold Model of Survival (GUTS)

The General Unified Threshold model of Survival (GUTS) provides a consistent mathematical framework for survival analysis. However, the calibration of GUTS models is computationally challenging. We present a novel algorithm and its fast implementation in our R package, GUTS, that help to overcome these challenges. We show a step-by-step application example consisting of model calibration and uncertainty estimation as well as making probabilistic predictions and validating the model with new data. Using self-defined wrapper functions, we show how to produce informative text printouts and plots without effort, for the inexperienced as well as the advanced user. The complete ready-to-run script is available as supplemental material. We expect that our software facilitates novel re-analysis of existing survival data as well as asking new research questions in a wide range of sciences. In particular the ability to quickly quantify stressor thresholds in conjunction with dynamic compensating processes, and their uncertainty, is an improvement that complements current survival analysis methods.

Shade Effects on the Dispersal of Airborne Hemileia vastatrix Uredospores

Hemileia vastatrix caused a severe epidemic in Central America in 2012-13. The gradual development of that epidemic on nearly a continental scale suggests that dispersal at different scales played a significant role. Shade has been proposed as a way of reducing uredospore dispersal. The effect of shade (two strata: Erythrina poeppigiana below and Chloroleucon eurycyclum above) and full sun on H. vastatrix dispersal was studied with Burkard traps in relation to meteorological records. Annual and daily patterns of dispersal were observed, with peaks of uredospore capture obtained during wet seasons and in the early afternoon. A maximum of 464 uredospores in 1 day (in 14.4 m(3) of air) was recorded in October 2014. Interactions between shade/full sun and meteorological conditions were found. Rainfall, possibly intercepted by tree cover and redistributed by raindrops of higher kinetic energy, was the main driver of uredospore dispersal under shade. Wind gusts reversed this effect, probably by inhibiting water accumulation on leaves. Wind gusts also promoted dispersal under dry conditions in full sun, whereas they had no effect under shaded conditions, probably because the canopy blocked the wind. Our results indicate the importance of managing shade cover differentially in rainy versus dry periods to control the dispersal of airborne H. vastatrix uredospores.

Selection, Fitness, and Control of Grape Isolates of Botrytis cinerea Variably Sensitive to Fenhexamid

Of 683 Botrytis cinerea isolates collected from a fungicide-trial vineyard, 31 were classified as putatively resistant to fenhexamid (50% effective concentration [EC₅₀] ≥ 0.1 μg/ml). For the resistant isolates that survived and sporulated in culture, colony expansion and conidial germination frequency was significantly reduced relative to the mean of 30 representative baseline isolates (EC₅₀ = 0.03 μg/ml). Grape berries were inoculated with four isolates representing a range of fenhexamid sensitivities and treated preventively or curatively with fenhexamid concentrations (150 to 600 mg/liter) representing 25 to 100% of the recommended rate. All treatments significantly delayed disease onset and progress caused by isolates with EC₅₀ values of 0.03 and 0.15 μg/ml but provided little to no control of isolates with EC₅₀ values of 0.32 and 62.5 μg/ml. The latter isolate exhibited a previously unreported F427V mutation of ERG27, an enzyme of ergosterol biosynthesis. In a duplex quantitative polymerase chain reaction test, the ratio of pathogen/host DNA increased significantly for 14 days after inoculation of untreated berries with a baseline isolate but declined slightly in berries treated with fenhexamid at 600 mg/liter 1 day post inoculation. In the vineyard, disease control was affected by the number and rate of fenhexamid applications but B. cinerea isolates with EC₅₀ ≥ 0.1 μg/ml were not preferentially selected.

Rank regression for analyzing ordinal qualitative data for treatment comparison

ABSTRACT Ordinal qualitative data are often collected for phenotypical measurements in plant pathology and other biological sciences. Statistical methods, such as t tests or analysis of variance, are usually used to analyze ordinal data when comparing two groups or multiple groups. However, the underlying assumptions such as normality and homogeneous variances are often violated for qualitative data. To this end, we investigated an alternative methodology, rank regression, for analyzing the ordinal data. The rank-based methods are essentially based on pairwise comparisons and, therefore, can deal with qualitative data naturally. They require neither normality assumption nor data transformation. Apart from robustness against outliers and high efficiency, the rank regression can also incorporate covariate effects in the same way as the ordinary regression. By reanalyzing a data set from a wheat Fusarium crown rot study, we illustrated the use of the rank regression methodology and demonstrated that the rank regression models appear to be more appropriate and sensible for analyzing nonnormal data and data with outliers.

Multivariate mixed linear model analysis of longitudinal data: an information-rich statistical technique for analyzing plant disease resistance

ABSTRACT The mixed linear model (MLM) is an advanced statistical technique applicable to many fields of science. The multivariate MLM can be used to model longitudinal data, such as repeated ratings of disease resistance taken across time. In this study, using an example data set from a multi-environment trial of northern leaf blight disease on 290 maize lines with diverse levels of resistance, multivariate MLM analysis was performed and its utility was examined. In the population and environments tested, genotypic effects were highly correlated across disease ratings and followed an autoregressive pattern of correlation decay. Because longitudinal data are often converted to the univariate measure of area under the disease progress curve (AUDPC), comparisons between univariate MLM analysis of AUDPC and multivariate MLM analysis of longitudinal data were made. Univariate analysis had the advantage of simplicity and reduced computational demand, whereas multivariate analysis enabled a comprehensive perspective on disease development, providing the opportunity for unique insights into disease resistance. To aid in the application of multivariate MLM analysis of longitudinal data on disease resistance, annotated program syntax for model fitting is provided for the software ASReml.

Toward a Reliable Evaluation of Forecasting Systems for Plant Diseases: A Case Study Using Fusarium Head Blight of Wheat

Despite great efforts to forecast plant diseases, many of the existing systems often fall short in providing farmers with accurate predictions. One of the main problems arises from the existence of year and location effects, so that more advanced procedures are required for evaluating existing systems in an unbiased manner. This paper illustrates the case of Fusarium head blight of winter wheat in Belgium. We present a new cross-validation strategy that enables the evaluation of the predictive performance of a forecasting system for years and locations that are different from the years and locations on which the forecast was developed. Four different cross-validation strategies and five regression techniques are used. The results demonstrated that traditional evaluation strategies are too optimistic in their predictions, whereas the cross-year cross-location validation strategy yielded more realistic outcomes. Using this procedure, the mean squared error increased and the coefficient of determination decreased in predicting disease severity and deoxynivalenol content, suggesting that existing evaluation strategies may generate a substantial optimistic bias. The strongest discrepancies between the cross-validation strategies were observed for multiple linear regression models.

Sharing of quorum-sensing signals and role of interspecies communities in a bacterial plant disease

Pathogenic bacteria interact not only with the host organism but most probably also with the resident microbial flora. In the knot disease of the olive tree (Olea europaea), the causative agent is the bacterium Pseudomonas savastanoi pv. savastanoi (Psv). Two bacterial species, namely Pantoea agglomerans and Erwinia toletana, which are not pathogenic and are olive plant epiphytes and endophytes, have been found very often to be associated with the olive knot. We identified the chemical signals that are produced by strains of the three species isolated from olive knot and found that they belong to the N-acyl-homoserine lactone family of QS signals. The luxI/R family genes responsible for the production and response to these signals in all three bacterial species have been identified and characterized. Genomic knockout mutagenesis and in planta experiments showed that virulence of Psv critically depends on QS; however, the lack of signal production can be complemented by wild-type E. toletana or P. agglomerans. It is also apparent that the disease caused by Psv is aggravated by the presence of the two other bacterial species. In this paper we discuss the potential role of QS in establishing a stable consortia leading to a poly-bacterial disease.

Suppression of Common Scab of Potato Caused by Streptomyces turgidiscabies Using Lopsided Oat Green Manure

Field experiments were conducted to determine the effect of green manure as fallow on common scab of potato caused by Streptomyces turgidiscabies. Significantly fewer diseased tubers were harvested from soil incorporated with lopsided oat or woolly pod vetch compared with those from oat and continuous potato cultivation in a planter experiment. Each field experiment consisted of lopsided oat cultivated during the spring and summer prior to the potato planting. Comparisons were also made with several other treatments, including cultivation of woolly pod vetch, oat, soybean, sugar beet, and potato ('Yukirasya', which is resistant to potato common potato scab) and soil application of Ferosand (Fe, mainly FeSO₄, to decrease the soil pH). In field experiments conducted during 1999-2000, treatment with lopsided oat followed by lopsided oat or woolly pod vetch was significantly more effective at suppressing the disease severity than oat and continuous potato cultivation (P < 0.001). An increase in the marketable tuber ratio was also more significant than for oat and continuous potato cultivation (P < 0.001). In field experiments conducted during 2000-01, lopsided oat cultivation alone and with the application of Ferosand (1.8 t/ha) or resistant potato cultivar treatment were significantly more effective at suppressing the disease severity and incidence than sugar beet cultivation (P < 0.001), even under high disease intensity in the field. However, potato yield had a tendency to reduce after lopsided oat treatment with an application of Ferosand (1.8 t/ha) compared with lopsided oat alone or the application of Ferosand at 600 kg/ha, due to low pH conditions. In field experiments conducted during 2001-02, the lowest severity and incidence of common scab of potato were observed in soil treated with lopsided oat than with other treatments (P < 0.05 and P < 0.001, respectively). These findings suggest that lopsided oat used as fallow green manure can reduce the severity of common scab and increase potato yield.

Comparison of soil and corn kernel Aspergillus flavus populations: evidence for niche specialization

Aspergillus flavus is considered a generalist-opportunistic pathogen, but studies are beginning to show that A. flavus populations have strains specific to various hosts. The research objective was to determine whether A. flavus soil populations consist of solely saprophytic strains and strains which can be facultatively parasitic on corn. A. flavus was isolated from both corn kernels and soil within 11 Louisiana fields. Sixteen vegetative compatibility groups (VCGs) were identified among 255 soil isolates. Only 6 of the 16 VCGs were identified in the 612 corn isolates and 88% of corn isolates were in two VCGs, whereas only 5% of soil isolates belonged to the same two VCGs. Isolates were characterized for aflatoxin B1 production and sclerotial size. A random subset of the isolates (99 from corn and 91 from soil) were further characterized for simple-sequence repeat (SSR) haplotype and mating type. SSR polymorphisms revealed 26 haplotypes in the corn isolates and 78 in the soil isolates, and only 1 haplotype was shared between soil and corn isolates. Corn and soil populations were highly significantly different for all variables. Differences between corn and soil populations indicate that some soil isolates are not found in corn and some isolates have become specialized to infect corn. Further understanding of A. flavus virulence is important for development of resistant hybrids and for better biological control against toxigenic A. flavus.

Bean pod mottle virus Spread in Insect-Feeding-Resistant Soybean

Bean pod mottle virus (BPMV) infection reduces yield and seed quality in soybean. To test the hypothesis that virus incidence and movement within plots would be reduced in soybean with resistance to feeding by the virus' bean leaf beetle (Cerotoma trifurcata) vector, BPMV spread was evaluated in five soybean genotypes at two inoculum levels over 2 years at two locations in Ohio. Soybean genotypes included two insect-feeding-susceptible genotypes (Williams 82 and Resnik), two insect-feeding-resistant, semidwarf genotypes (HC95-15 and HC95-24), and an insect-feeding-susceptible, semidwarf genotype (Troll). BPMV incidence was assessed in individual plants at growth stages R5/R6 and R7/R8 using enzyme-linked immunosorbent assay. Beetle feeding was visually assessed in 2004. Data for infection of individual plants were analyzed using a generalized linear mixed model, with a binomial distribution and logit-link. Within plots, BPMV incidence was highest in Resnik and Williams 82 and significantly lower in Troll. Incidence in HC95-15 was not significantly different than in Williams 82 and Resnik but incidence in HC95-24 was lower than in Resnik. BPMV incidence was also significantly (P < 0.05) affected by year, location, inoculum level and sampling date, with increasing incidence over time and higher incidence at the higher inoculum level. Beetle feeding damage was affected by the interaction of location-genotype. Significant spatial aggregation of infected plants was found for most plots but aggregation was independent of host genotype and inoculum level. Although the results indicate that BPMV infection varied by genotype, they do not support the hypothesis that insect-feeding resistance is sufficient to reduce the incidence and spread of BPMV.

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

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

Modeling the rejection probability in plant imports

Phytosanitary inspection of imported plants and flowers is a major means for preventing pest invasions through international trade, but in a majority of countries availability of resources prevents inspection of all imports. Prediction of the likelihood of pest infestation in imported shipments could help maximize the efficiency of inspection by targeting inspection on shipments with the highest likelihood of infestation. This paper applies a multinomial logistic (MNL) regression model to data on import inspections of ornamental plant commodities in the Netherlands from 1998 to 2001 to investigate whether it is possible to predict the probability that a shipment will be (i) accepted for import, (ii) rejected for import because of detected pests, or (iii) rejected due to other reasons. Four models were estimated: (i) an all-species model, including all plant imports (136,251 shipments) in the data set, (ii) a four-species model, including records on the four ornamental commodities that accounted for 28.9% of inspected and 49.5% of rejected shipments, and two models for single commodities with large import volumes and percentages of rejections, (iii) Dianthus (16.9% of inspected and 46.3% of rejected shipments), and (iv) Chrysanthemum (6.9 and 8.6%, respectively). All models were highly significant (P < 0.001). The models for Dianthus and Chrysanthemum and for the set of four ornamental commodities showed a better fit to data than the model for all ornamental commodities. Variables that characterized the imported shipment's region of origin, the shipment's size, the company that imported the shipment, and season and year of import, were significant in most of the estimated models. The combined results of this study suggest that the MNL model can be a useful tool for modeling the probability of rejecting imported commodities even with a small set of explanatory variables. The MNL model can be helpful in better targeting of resources for import inspection. The inspecting agencies could enable development of these models by appropriately recording inspection results.

An Evidence-Based Approach to Plum Pox Virus Detection by DASI-ELISA and RT-PCR in Dormant Period

An evidence-based approach, such as those developed in clinical and veterinary medicine, was applied to the detection of Plum pox virus (PPV) during the dormant period. A standardized methodology was used for the calculation of parameters of the operational capacity of DASI-ELISA and RT-PCR in wintertime. These methods are routinely handled to test the sanitary status of plants in national or international trading and in those cases concerning export-import of plant materials. Diagnosis often has to be performed during the dormant period, when plant material is commercialized. Some guidelines to interpret diagnostic results of wintertime are provided in an attempt to minimize risks associated with the methods and over-reliance on the binary outcome of a single assay. In order to evaluate if a complementary test increased the confidence of PPV diagnosis when discordant results between DASI-ELISA and RT-PCR are obtained, NASBA-FH also was included. Likelihood ratios of each method were estimated based on the sensitivity and specificity obtained in wintertime. Subsequently, a Bayesian approach was performed to calculate post-test probability of PPV infection in spring. Results of evidence-based approach show that different PPV prevalences require different screening tests. Thus, at very low PPV prevalence levels DASI-ELISA should be used as the election method, whilst at the highest PPV prevalence levels RT-PCR should be performed. NASBA-FH could be used at medium prevalences to clarify discordances between DASI-ELISA and RT-PCR.

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

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

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

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

Systemic Modulation of Gene Expression in Tomato by Trichoderma hamatum 382

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

Modelling disease spread and control in networks: implications for plant sciences

Networks are ubiquitous in natural, technological and social systems. They are of increasing relevance for improved understanding and control of infectious diseases of plants, animals and humans, given the interconnectedness of today's world. Recent modelling work on disease development in complex networks shows: the relative rapidity of pathogen spread in scale-free compared with random networks, unless there is high local clustering; the theoretical absence of an epidemic threshold in scale-free networks of infinite size, which implies that diseases with low infection rates can spread in them, but the emergence of a threshold when realistic features are added to networks (e.g. finite size, household structure or deactivation of links); and the influence on epidemic dynamics of asymmetrical interactions. Models suggest that control of pathogens spreading in scale-free networks should focus on highly connected individuals rather than on mass random immunization. A growing number of empirical applications of network theory in human medicine and animal disease ecology confirm the potential of the approach, and suggest that network thinking could also benefit plant epidemiology and forest pathology, particularly in human-modified pathosystems linked by commercial transport of plant and disease propagules. Potential consequences for the study and management of plant and tree diseases are discussed.

Distribution and Pathogenic Characterization of Pyrenophora tritici-repentis and Stagonospora nodorum in Ohio

ABSTRACT To determine the distribution of Stagonospora nodorum and Pyrenophora tritici-repentis on wheat in Ohio, flag leaves with lesions were collected from wheat-producing counties in 2002 and 2003. Counties were arbitrarily grouped into seven regions. Log-linear analysis of pathogen presence within regions indicated that the presence of S. nodorum was independent of the presence of P. tritici-repentis. A logistic analysis revealed that the occurrence of both pathogens varied by region in one or both years. The aggressiveness of S. nodorum isolates was determined by inoculating two susceptible genotypes with a subsample of isolates from each region from both years. S. nodorum isolates obtained from northeast Ohio, with fewer wheat fields, were less aggressive than those from other regions. Isolates obtained from west-central Ohio, surrounded by regions with high wheat production annually, were significantly more aggressive than those obtained in the remaining five regions. Isolates from the five other regions did not differ significantly (P > 0.05) in aggressiveness. Races 1 and 2, and a few race 3 isolates, of P. tritici-repentis were detected in Ohio. The distribution of P. tritici-repentis races 1 and 2 was not associated with any region, although the prevalence of race 1 was three times greater than race 2. The rarer race 3 was associated with three dispersed regions. Results indicate that S. nodorum was the major wheat leaf-blotching pathogen. There were no positive or negative associations of S. nodorum and P. tritici-repentis or individual races of P. tritici-repentis in any of the tested regions, which indicates that neither pathogen can be used to predict the presence of the other. The isolated northeastern corner of Ohio appeared to contain isolates of S. nodorum with unique characteristics and potentially only one race of P. tritici-repentis, indicating that this area may be genetically isolated from the remaining tested areas of the state.

Identifying risk factors for European stone fruit yellows from a survey

ABSTRACT European stone fruit yellows (ESFY) is becoming a major economic problem for Prunus growers in Europe. The causal agent ("Candidatus Phytoplasma prunorum") and its vector (Cacopsylla pruni) have been identified, but the present knowledge of the risk factors for this disease relies, at best, on specific experiments. To assess the relative significance of several factors correlated with ESFY incidence in the field, an exhaustive survey was performed on apricot and Japanese plum orchards in the Crau plain (France). After a preliminary multivariate exploration of the data, we used a logistic regression model to analyze and predict the cumulative number of diseased trees on the basis of a set of quantitative (age, planting density, and area of the orchard) and categorical variables (species, cultivar, and rootstock). Because of the nature of the data, we used an overdispersed binomial model and we developed a parametric bootstrap procedure based on the beta-binomial distribution to obtain confidence intervals. Our results indicated that the age, species, and cultivar of the scion were the major factors explaining the observed number of diseased trees. The planting density and the rootstocks used in the zone under study were less significant, and the area of the orchard had no effect. The residuals of the model showed that some explanatory variables had not been taken into account, because part of the remaining variability could be explained by a grower effect. The spatial distribution of the residuals suggested that one of the reasons for this grower effect was the correlation between orchards closer than 100 m, possibly caused by the flight behavior of infectious vectors.

Analysis of summer epidemic progress of apple scab at different apple production systems in the Netherlands and hungary

ABSTRACT Two, 4-year studies on summer epidemic progress of apple scab were conducted at Randwijk, the Netherlands, from 1998 until 2001 and at Eperjeske, Hungary, from 2000 until 2003. Disease assessments were made on scab-susceptible cv. Jonagold. A range of nonlinear growth functions were fitted to a total of 96 disease progress curves (3 treatment classes x 2 plant parts x 2 disease measures x 4 years x 2 locations) of apple scab incidence and severity. The three-parameter logistic model gave the most consistent fit across three treatment classes in the experiment (integrated, organic-sprayed, and organic-unsprayed). Parameters estimated or calculated from the three-parameter logistic function were used to analyze disease progress. These were disease incidence and severity on the day of the first assessment (Y(s)); final disease incidence or upper asymptote for incidence (Y(if)) or severity (Y(sf)); fruit incidence and severity on day 40, after which no new lesions on fruits appeared (Y(40)); leaf incidence and severity on day 75, at which shoot growth stopped (Y (75)); relative (beta) and "absolute" (theta) rates of disease progress; inflection point (M); and area under the disease progress curve (AUDPC(S)) standardized by the duration of the total epidemic. Comparisons among disease progress curves were made by correlation and factor analysis followed by Varimax rotation. There were large differences but high positive correlations among the parameters Y(s), Y(f), theta, and AUDPC(S) across the three treatment classes. In the factor analysis, two factors accounted for more than 85% of the total variance for both incidence and severity. Factor 1 gave an overall description of epidemic progress of both scab incidence and severity and included the parameters Y(f), Y(40), Y(75), theta, and AUDPC(S). Factor 2 identified a relationship between the relative rate parameter (beta) and the inflection point (M) for severity and a relationship between disease incidence and severity. For an integrated or an organic orchard, theta, AUDPC(S), and one of Y(f) or Y(75) (because of the link with host phenology) can characterize apple scab epidemics during summer. Based on these findings, improved scab management approaches were provided for integrated and organic apple production systems.

The Window of Risk for Emigration of Wheat streak mosaic virus Varies with Host Eradication Method

The wheat curl mite (WCM), Aceria tosichella, the vector of Wheat streak mosaic virus (WSMV), often survives the summer on volunteer wheat (Triticum aestivum) and may disperse from this "green bridge" in fall to newly planted winter wheat. Because some methods for managing volunteer wheat do not directly kill WCM, there is a window of risk for WCM and WSMV emigration after management has been applied. WCM survival in response to treatment of wheat by glyphosate, paraquat, stem cutting, and withholding water was measured in greenhouse experiments to determine how this window of risk for emigration varies with management. WCM populations on plants treated with paraquat or stem cutting decreased from the beginning of the sampling period. WCM populations on plants treated with glyphosate or that received no water increased up to 3 days after application and then decreased by 10 days after application. If glyphosate is used to manage volunteer wheat infested with WCM, it should be applied well before wheat is planted in fall. WCM in declining populations tended to be in an upright posture that could facilitate emigration via wind. The total green leaf area was strongly correlated with the number of WCM for treated plants and could be used in the field to predict the posttreatment survival of mites that pose a risk of emigration.