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Epidemics of tomato yellow leaf curl virus (TYLCV; species Tomato yellow leaf curl begomovirus ) have been problematic to tomato production in the southeastern United States since the first detection of the virus in Florida in the late 1990s. Current strategies for management focus on farm-centric tactics that have had limited success for controlling either TYLCV or its whitefly vector. Areawide pest management (AWPM)-loosely defined as a coordinated effort to implement management strategies on a regional scale-may be a viable management alternative. A prerequisite for development of an AWPM program is an understanding of the spatial and temporal dynamics of the target pathogen and pest populations. The objective of this study was to characterize populations of whitefly and TYLCV in commercial tomato production fields in southwestern Florida and utilize this information to develop predictors of whitefly density and TYLCV disease incidence as a function of environmental and geographical factors. Scouting reports were submitted by cooperating growers located across approximately 20,000 acres in southwestern Florida from 2006 to 2012. Daily weather data were obtained from several local weather stations. Moran's I was used to assess spatial relationships and polynomial distributed lag regression was used to determine the relationship between weather variables, whitefly, and TYLCV. Analyses showed that the incidence of TYLCV increased proportionally with mean whitefly density as the season progressed. Nearest-neighbor analyses showed a strong linear relationship between the logarithms of whitefly densities in neighboring fields. A similar relationship was found with TYLCV incidences. Correlograms based on Moran's I showed that these relationships extended beyond neighboring fields and out to approximately 2.5 km for TYLCV and up to 5 km for whitefly, and that values of I were generally higher during the latter half of the production season for TYLCV. Weather was better at predicting whitefly density than at predicting TYLCV incidence. Whitefly density was best predicted by the number of days with an average temperature between 16 and 24°C (T16to24), relative humidity (RH) over the previous 31 days, and vapor pressure deficit over the last 8 days. TYLCV incidence was best predicted by T16to24, RH, and maximum wind speed over the previous 31 days. Results of this study helped to identify the extent to which populations of whitefly and TYLCV exist over the agricultural landscape of southwestern Florida, and the environmental conditions that favor epidemic growth. This information was used to propose an approach to AWPM for timing control measures for managing TYLCV epidemics.

Scenario analysis constitutes a useful approach to synthesize knowledge and derive hypotheses in the case of complex systems that are documented with mainly qualitative or very diverse information. In this article, a framework for scenario analysis is designed and then, applied to global wheat health within a timeframe from today to 2050. Scenario analysis entails the choice of settings, the definition of scenarios of change, and the analysis of outcomes of these scenarios in the chosen settings. Three idealized agrosystems, representing a large fraction of the global diversity of wheat-based agrosystems, are considered, which represent the settings of the analysis. Several components of global changes are considered in their consequences on global wheat health: climate change and climate variability, nitrogen fertilizer use, tillage, crop rotation, pesticide use, and the deployment of host plant resistances. Each idealized agrosystem is associated with a scenario of change that considers first, a production situation and its dynamics, and second, the impacts of the evolving production situation on the evolution of crop health. Crop health is represented by six functional groups of wheat pathogens: the pathogens associated with Fusarium head blight; biotrophic fungi, Septoria-like fungi, necrotrophic fungi, soilborne pathogens, and insect-transmitted viruses. The analysis of scenario outcomes is conducted along a risk-analytical pattern, which involves risk probabilities represented by categorized probability levels of disease epidemics, and risk magnitudes represented by categorized levels of crop losses resulting from these levels of epidemics within each production situation. The results from this scenario analysis suggest an overall increase of risk probabilities and magnitudes in the three idealized agrosystems. Changes in risk probability or magnitude however vary with the agrosystem and the functional groups of pathogens. We discuss the effects of global changes on the six functional groups, in terms of their epidemiology and of the crop losses they cause. Scenario analysis enables qualitative analysis of complex systems, such as plant pathosystems that are evolving in response to global changes, including climate change and technology shifts. It also provides a useful framework for quantitative simulation modeling analysis for plant disease epidemiology.

Collections of Puccinia triticina, the wheat leaf rust pathogen, were obtained from Pakistan in 2008, 2010, 2011, 2013, and 2014. Collections were also obtained from Bhutan in 2013. Single uredinial isolates were derived and tested for virulence phenotype to 20 lines of Thatcher wheat that differ for single leaf rust resistance genes, and for molecular genotype with 23 simple-sequence repeat (SSR) primers. Twenty-four virulence phenotypes were described among the 89 isolates tested for virulence. None of the isolates had virulence to Thatcher lines with Lr9, Lr24, or Lr18. Virulence to most of the other Thatcher lines was over 50%. The two most common virulence phenotypes, FHPSQ and KHPQQ, had virulence to Lr16, Lr17, and Lr26. Twenty-seven SSR genotypes were found among the 38 isolates tested for molecular variation. The SSR genotypes had high levels of observed heterozygosity and significant correlation with virulence phenotype, which indicated clonal reproduction. Cluster analysis and principal component plots indicated three groups of SSR genotypes that also varied significantly for virulence. Isolates with MBDSS and MCDSS virulence phenotypes from Pakistan and Bhutan were highly related for SSR genotype and virulence to isolates from Turkey, Europe, Central Asia, the Middle East, North America and South America, indicating the possible migration of the rust fungus between continental regions.

The estrogenic mycotoxin zearalenone (ZON) produced by some Fusarium spp. causes reproductive problems and hyperestrogenic syndromes in mammals. In an effort to elucidate the molecular pathways of ZON production, we present a comparative real-time quantitative polymerase chain reaction expression study of seven contiguous genes in the ZON biosynthetic cluster on sterile rice and during wheat and oat infection. Under ZON production on rice, the polyketide synthase (PKS) genes PKS4 and PKS13, alcohol oxidase FG12056 gene, and transcriptional regulator FG02398 gene showed similarly upregulated patterns, whereas the nonribosomal peptide synthetase (NPS) FG02394, the K(+) channel beta subunit FG12015, and the protein kinase FG02399 displayed a variant pattern. During the same time period under wheat infection when no ZON was produced, the PKS genes and the NPS were downregulated relative to rice whereas the K(+) channel beta subunit gene FG12015 was markedly upregulated, suggesting that it may play a role in the infection process. This is the first expression study of ZON biosynthetic genes in planta. The results give insight into the regulation and activities of the ZON gene cluster under different experimental systems and suggest a connection between ZON and a K(+) channel that could reveal a novel function for ZON in Fusarium spp.