Survival of Xanthomonas fragariae on Common Materials

Xanthomonas fragariae causes strawberry angular leaf spot (ALS), an important disease for the strawberry nursery industry in North America. To identify potential inoculum sources, the survival of X. fragariae was examined on the surfaces of 11 common materials found in nurseries: corrugated cardboard, cotton balls, cotton cloth (t-shirt), strawberry leaf, sheet metal, plastic, rubber, Tyvek, wood (balsa), glass (microscope slide), and latex (latex glove). Prefabricated rectangular samples (7.62 by 2.54 cm) of each material were immersed in a bacterial suspension for 15 min, after which the samples were stored at approximately 20°C (room temperature) or -4°C (the cold storage temperature for dormant plants in strawberry nurseries) for 1, 3, 7, 14, 30, 60, 90, 180, 270, and 365 days after inoculation (DAI). After the storage period elapsed, bacteria were recovered from the surfaces of each of the samples with phosphate-buffered saline (PBS)-soaked cotton balls. Survival rate was determined with a viability real-time quantitative PCR procedure and in a plant bioassay that involved rub inoculation of strawberry leaflets with the PBS-soaked cotton balls used to recover bacteria from the samples. Results showed that X. fragariae could survive on all surfaces but that survival rate differed among materials and storage temperature. All materials were capable of harboring viable bacteria up to 7 DAI when stored at -4°C based on the formation of lesions on inoculated leaves in the plant bioassay. The longest survival observed was 270 DAI on cardboard stored at -4°C. At room temperature, cardboard, cotton balls, cotton t-shirt, and strawberry leaf tissue supported small bacterial populations up to 14 DAI. The information from this study can be used to improve sanitation practices for ALS management in strawberry nurseries.

A Long-Amplicon Viability-qPCR Test for Quantifying Living Pathogens that Cause Bacterial Spot in Tomato Seed

Bacterial spot is one of the most serious diseases of tomato. It is caused by four species of Xanthomonas: X. euvesicatoria, X. gardneri, X. perforans, and X. vesicatoria. Contaminated or infected seed can be a major source of inoculum for this disease. The use of certified pathogen-free seed is one of the primary management practices to reduce the inoculum load in commercial production. Current seed testing protocols rely mainly on plating the seed extract and conventional PCR; however, the plating method cannot detect viable but nonculturable cells, and the conventional PCR assay has limited capability to differentiate DNA extracted from viable or dead bacterial cells. To improve the sensitivity and specificity of the tomato seed testing method for bacterial spot pathogens, a long-amplicon quantitative PCR (qPCR) assay coupled with propidium monoazide (PMA-qPCR) was developed to quantify selectively the four pathogenic Xanthomonas species in tomato seed. The optimized PMA-qPCR procedure was evaluated on pure bacterial suspensions, bacteria-spiked seed extracts, and seed extracts of inoculated and naturally infected seed. A crude DNA extraction protocol also was developed, and PMA-qPCR with crude bacterial DNA extracts resulted in accurate quantification of 10⁴ to 10⁸ CFU/ml of viable bacteria when mixed with dead cells at concentrations as high as 10⁷ CFU/ml in the seed extracts. With DNA purified from concentrated seed extracts, the PMA-qPCR assay was able to detect DNA of the target pathogens in seed samples spiked with ≥75 CFU/ml (about 0.5 CFU/seed) of the viable pathogens. Latent class analysis of the inoculated and naturally infected seed samples showed that the PMA-qPCR assay had greater sensitivity than plating the seed extracts on the semiselective modified Tween Medium B and CKTM media for all four target species. Being much faster and more sensitive than dilution plating, the PMA-qPCR assay has potential to be used as a standalone tool or in combination with the plating method to improve tomato seed testing and advance the production of clean seed.

Complete genome sequence of Xanthomonas phage RiverRider, a novel N4-like bacteriophage that infects the strawberry pathogen Xanthomonas fragariae

Xanthomonas phage RiverRider is a novel N4-like bacteriophage and the first phage isolated from the plant pathogen Xanthomonas fragariae. Electron microscopy revealed a Podoviridae morphology consisting of isometric heads and short noncontractile tails. The complete genome of RiverRider is 76,355 bp in length, with 90 open reading frames and seven tRNAs. The genome is characteristic of N4-like bacteriophages in both content and organization, having predicted proteins characterized into the functional groups of transcription, DNA metabolism, DNA replication, lysis, lysis inhibition, structure and DNA packaging. Amino acid sequence comparisons for proteins in these categories showed highest similarities to well-characterized N4-like bacteriophages isolated from Achromobacter xylosoxidans and Erwinia amylovora. However, the tail fiber proteins of RiverRider are clearly distinct from those of other N4-like phages. RiverRider was able to infect seven different strains of X. fragariae and none of the other species of Xanthomonas tested.

Detection of Viable Xanthomonas fragariae Cells in Strawberry Using Propidium Monoazide and Long-Amplicon Quantitative PCR

Xanthomonas fragariae causes angular leaf spot in strawberry. The pathogen's association with its host tissue is thought to be a condition for its survival. Consequently, transmission of the pathogen to field production sites occurs almost exclusively through the movement of contaminated planting stock. The aim of this study was to develop a propidium monoazide (PMA)-quantitative PCR (qPCR) protocol for specific detection of viable X. fragariae cells. The qPCR procedure was developed for two different primer pairs: one producing a long amplicon (863 bp) and the other a short amplicon (61 bp). Both pairs were tested on mixtures of viable and heat-killed bacteria cells, bacteria-spiked strawberry petiole samples, and petioles collected from symptomatic, inoculated plants. The results showed that long-amplicon PMA-qPCR enabled specific and sensitive detection of X. fragariae with a detection limit of 10³ CFU/ml, and it significantly improved PMA efficiency in differentiating viable from dead bacterial cells relative to short-amplicon PMA-qPCR. Based on the delta threshold cycle (C_t) values (i.e., the difference in C_t values between PMA-treated and nontreated samples), the long-amplicon PMA-qPCR was able to suppress the detection of dead X. fragariae cells 1.9- to 3.1-fold across all petiole samples tested. The quantification results from PMA-qPCR for mixtures of viable and dead cells were highly correlated with the predicted bacterial concentrations in a linear relationship (R² = 0.981). This assay can be useful for identifying inoculum sources in the strawberry production cycle, which may lead to improved disease management strategies.

Spatial and Temporal Physiognomies of Whitefly and Tomato Yellow Leaf Curl Virus Epidemics in Southwestern Florida Tomato Fields

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.

Risk Factors for Bud Perennation of Podosphaera macularis on Hop

The hop powdery mildew fungus Podosphaera macularis persists from season to season in the Pacific Northwestern United States through infection of crown buds because only one of the mating types needed to produce the ascigerous stage is presently found in this region. Bud infection and successful overwintering of the fungus leads to the emergence of heavily infected shoots in early spring (termed flag shoots). Historical data of flag shoot occurrence and incidence in Oregon and Washington State during 2000 to 2017 were analyzed to identify their association with the incidence of powdery mildew, growers' use of fungicides, autumn and winter temperature, and other production factors. During this period, flag shoots were found on 0.05% of plants evaluated in Oregon and 0.57% in Washington. In Oregon, the incidence of powdery mildew on leaves was most severe and the number of fungicide applications made by growers greatest in yards where flag shoots were found in spring. Similarly, the incidence of plants with powdery mildew in Washington was significantly associated with the number of flag shoots present in early spring, although the number of fungicide applications made was independent of flag shoot occurrence. The occurrence of flag shoots was associated with prior occurrence of flag shoots in a yard, the incidence of foliar powdery mildew in the previous year, grower pruning method, and, in Washington, winter temperature. A census of hop yards in the eastern extent of the Oregon production region during 2014 to 2017 found flag shoots in 27 of 489 yards evaluated. In yards without flag shoots, 338 yards (73.2%) were chemically pruning or not pruned, whereas the remaining 124 (26.8%) were mechanically pruned. Of the 27 yards with flag shoots, 22 were either chemically pruned or not pruned and 4 were mechanically pruned in mid-April, well after the initial emergence of flag shoots. The prevalence of yards with flag shoots also was related to thoroughness of pruning in spring (8.1% of yards with incomplete pruning versus 1.9% of yards with thorough pruning). A Bayesian logistic regression model was fit to the data from the intensively assessed yards in Oregon, with binary risk factors for occurrence of a flag shoot in the previous year, occurrence of foliar mildew in the previous year, and thoroughness of pruning in spring. The model indicated that the median and 95% highest posterior density interval of the probability of flag shoot occurrence was 0.0008 (0.0000 to 0.0053) when a yard had no risk factors but risk increased to 0.0065 (0.0000 to 0.0283) to 0.43 (0.175 to 0.709) when one to all three of the risk factors were present. The entirety of this research indicates that P. macularis appears to persist in a subset of chronically affected hop yards, particularly yards where spring pruning is conducted poorly. Targeted management of the disease in a subset of fields most at risk for producing flag shoots could potentially influence powdery mildew development regionwide.

Twenty-Five Years of the Binary Power Law for Characterizing Heterogeneity of Disease Incidence

Spatial pattern, an important epidemiological property of plant diseases, can be quantified at different scales using a range of methods. The spatial heterogeneity (or overdispersion) of disease incidence among sampling units is an especially important measure of small-scale pattern. As an alternative to Taylor's power law for the heterogeneity of counts with no upper bound, the binary power law (BPL) was proposed in 1992 as a model to represent the heterogeneity of disease incidence (number of plant units diseased out of n observed in each sampling unit, or the proportion diseased in each sampling unit). With the BPL, the log of the observed variance is a linear function of the log of the variance for a binomial (i.e., random) distribution. Over the last quarter century, the BPL has contributed to both theory and multiple applications in the study of heterogeneity of disease incidence. In this article, we discuss properties of the BPL and use it to develop a general conceptualization of the dynamics of spatial heterogeneity in epidemics; review the use of the BPL in empirical and theoretical studies; present a synthesis of parameter estimates from over 200 published BPL analyses from a wide range of diseases and crops; discuss model fitting methods, and applications in sampling, data analysis, and prediction; and make recommendations on reporting results to improve interpretation. In a review of the literature, the BPL provided a very good fit to heterogeneity data in most publications. Eighty percent of estimated slope (b) values from field studies were between 1.06 and 1.51, with b positively correlated with the BPL intercept parameter. Stochastic simulations show that the BPL is generally consistent with spatiotemporal epidemiological processes and holds whenever there is a positive correlation of disease status of individuals composing sampling units.

Colonization and Movement of Xanthomonas fragariae in Strawberry Tissues

Xanthomonas fragariae causes angular leaf spot of strawberry, an important disease in strawberry growing regions worldwide. To better understand how X. fragariae multiplies and moves in strawberry plants, a green fluorescent protein (GFP)-labeled strain was constructed and used to monitor the pathogen's presence in leaf, petiole, and crown tissue with fluorescence microscopy following natural and wound inoculation in three strawberry cultivars. Taqman PCR was used to quantify bacterial densities in these same tissues regardless of the presence of GFP signal. Results showed X. fragariae colonized leaf mesophyll, the top 1 cm portion of the petiole adjacent to the leaf blade, and was occasionally found colonizing xylem vessels down to the middle of the petioles. The colonization of vascular bundles and the limited systemic movement that was observed appeared to be a passive process, of which the frequency increased with wounding and direct infiltration of bacteria into leaf veins. X. fragariae was able to directly enter petioles and colonize the space under the epidermis. Systemic movement of the bacteria into crown and other uninoculated tissues was not detected visually by GFP. However, X. fragariae was occasionally detected in these tissues by qPCR, but at quantities very near the qPCR detection limit. Petiole tissue harboring bacteria introduced either by direct entry through natural openings or wounds, or by systemic movement from infected foliar tissue, likely serves as a main source of initial inoculum in field plantings.

Development of Phytophthora Fruit Rot Caused by Phytophthora capsici on Resistant and Susceptible Watermelon Fruit of Different Ages

Watermelon is an important crop grown in 44 states in the United States. Phytophthora fruit rot caused by Phytophthora capsici is a serious disease in the southeastern U.S.A., where over 50% of the watermelons are produced. The disease has resulted in severe losses to watermelon growers, especially in Georgia, South Carolina, and North Carolina during the past few years. Several fruit rot-resistant watermelon germplasm lines have been developed for use in breeding programs. To evaluate the development of Phytophthora fruit rot on fruit of different ages, plants of fruit rot-resistant and susceptible lines were planted at weekly intervals for five consecutive weeks in experiments conducted over three years (2011 to 2013). Flowers were routinely inspected and hand pollinated to ensure having fruit of different ages. In each year, different aged fruit were harvested on the same day and inoculated with a 5-mm agar plug from an actively growing colony of P. capsici. Inoculated fruit were maintained in a room set to conditions conducive for disease development (>95% relative humidity, 26 ± 2°C). After 5 days, lesion diameter and intensity of sporulation was recorded for each fruit. Lesion diameter and sporulation intensity were significantly greater on fruit of susceptible lines compared with resistant lines. Fruit age did not have an effect on either measurement on susceptible (Sugar Baby) or resistant lines (PI 560020 and PI 595203). Our results showed that resistance to Phytophthora fruit rot in watermelon was not correlated with fruit age.

Development and Evaluation of ELISA and qRT-PCR for Identification of Squash vein yellowing virus in Cucurbits

Squash vein yellowing virus (SqVYV) causes viral watermelon vine decline. To facilitate detection of SqVYV, enzyme linked-immunosorbent assay (ELISA) and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) diagnostic methods were developed. Both methods were capable of detecting SqVYV in a wide range of cucurbit hosts. ELISA was able to detect virus in infected host tissue diluted to at least 1:2,560, which was sufficient for detection in symptomatic squash and watermelon plants. The qRT-PCR method was capable of reliably detecting as few as 3.4 copies of a cloned fragment of SqVYV genomic RNA with an average cycle threshold (C_t) value of 36.4. The sensitivities and specificities for each detection method were estimated by latent class analysis for a set of inoculated squash and watermelon plants at two sampling scales. The scales were hierarchical, with individual plants representing the upper scale and samples from the plant representing the lower scale. The number of samples per plant varied from 1 to 8, and a plant was diagnosed positive if any of its samples tested positive. For all analyses, a cutoff C_t of 35 was chosen for qRT-PCR, which is approximately 2.5 cycles lower than the lowest C_t value achieved for mock-inoculated plants (presumed to be a false positive). qRT-PCR showed high sensitivities (≥0.99) at both sampling scales for squash and watermelon, whereas the sensitivities for ELISA ranged from 0.58 to 0.76. The specificities for both tests were very similar (≥0.94), with ELISA sometimes outperforming qRT-PCR. These diagnostic methods provide additional tools for the identification of SqVYV and management of SqVYV-induced watermelon vine decline.

Genomic and Biological Characterization of Tomato necrotic streak virus, a Novel Subgroup 2 Ilarvirus Infecting Tomato in Florida

Genomic and biological characterization of Tomato necrotic streak virus (TomNSV), a recently described ilarvirus infecting tomato in Florida, was completed. The full genome sequence revealed that TomNSV is a novel subgroup 2 ilarvirus that is distinct from other previously reported tomato-infecting ilarviruses: Tobacco streak virus, Parietaria mottle virus, and Tomato necrotic spot virus included in subgroup 1. In a host range experiment, TomNSV infected members of the Solanaceae and Chenopodiaceae plant families but did not infect sunflower (Helianthus annuus L.) or green bean (Phaseolus vulgaris L.). In tomato plants, the virus moved downward to the roots from the initial point of infection and then upward from the roots to tissues of active growth such as fruit, flowers, and young leaves where symptoms were produced. Thus, young leaves, fruit, and flowers are ideal for sampling for TomNSV. The transmission rate by seed collected from infected tomato plants was determined to be 0.33%. Collectively, the results of these experiments indicated that TomNSV is the causal agent of the necrotic streak disease of tomato observed in Florida since 2013.

A Loop-Mediated Isothermal Amplification Assay and Sample Preparation Procedure for Sensitive Detection of Xanthomonas fragariae in Strawberry

Xanthomonas fragariae is a bacterium that causes angular leaf spot of strawberry. Asymptomatic infection is common and contributes to the difficulties in disease management. The aim of this study was to develop a loop-mediated isothermal amplification (LAMP) assay as an efficient method for detection of asymptomatic infections of X. fragariae. In addition, a new method of sample preparation was developed that allows sampling of a larger amount of plant tissue, hence increasing the detection rate in real-life samples. The sample preparation procedure includes an overnight incubation of strawberry tissues in phosphate-buffered saline (PBS), followed by a quick sample concentration and a boiling step to extract DNA for amplification. The detection limit of the LAMP assay was approximately 2×10(3) CFU/mL for pure bacteria culture and 300 CFU/mL for bacteria spiked strawberry leaf and petiole samples. LAMP provided a 2-3 fold lower detection limit than the standard qPCR assay but was faster, and more user-friendly. The LAMP assay should serve as a rapid, sensitive and cost-effective tool for detecting asymptomatic infections of X. fragariae in strawberry nursery stock and contribute to improved disease management.

Emergence of Groundnut ringspot virus and Tomato chlorotic spot virus in Vegetables in Florida and the Southeastern United States

Groundnut ringspot virus (GRSV) and Tomato chlorotic spot virus (TCSV) are two emerging tospoviruses in Florida. In a survey of the southeastern United States, GRSV and TCSV were frequently detected in solanaceous crops and weeds with tospovirus-like symptoms in south Florida, and occurred sympatrically with Tomato spotted wilt virus (TSWV) in tomato and pepper in south Florida. TSWV was the only tospovirus detected in other survey locations, with the exceptions of GRSV from tomato (Solanum lycopersicum) in South Carolina and New York, both of which are first reports. Impatiens (Impatiens walleriana) and lettuce (Lactuca sativa) were the only non-solanaceous GRSV and/or TCSV hosts identified in experimental host range studies. Little genetic diversity was observed in GRSV and TCSV sequences, likely due to the recent introductions of both viruses. All GRSV isolates characterized were reassortants with the TCSV M RNA. In laboratory transmission studies, Frankliniella schultzei was a more efficient vector of GRSV than F. occidentalis. TCSV was acquired more efficiently than GRSV by F. occidentalis but upon acquisition, transmission frequencies were similar. Further spread of GRSV and TCSV in the United States is possible and detection of mixed infections highlights the opportunity for additional reassortment of tospovirus genomic RNAs.

Spatial and Temporal Analysis of Squash vein yellowing virus Infections in Watermelon

Squash vein yellowing virus (SqVYV) is a whitefly-transmitted ipomovirus infecting watermelon and other cucurbits that was recently introduced to Florida. Effects on watermelon are devastating, with total vine collapse, often near harvest, and fruit rendered unmarketable by brown, discolored flesh. The epidemiology of SqVYV was studied in a 1-ha field of 'Fiesta' watermelon over six growing seasons (I to VI) to characterize the spatial patterning of disease and temporal rate of disease progress, as well as its association with Cucurbit leaf crumple virus (CuLCrV) and Cucurbit yellow stunting disorder virus (CYSDV), two additional whitefly-transmitted viruses that often occur with SqVYV. The field was scouted at regular intervals for the length of the season for incidence of virus and number of whiteflies. Incidence of SqVYV reached 100% during seasons I, II, and V and 20% during season III. SqVYV did not occur during seasons IV and VI. SqVYV progressed in a characteristic logistic fashion in seasons I, II, and V but less so in season III. The rate of disease progress was similar for the three seasons with high disease incidence, with an average value of 0.18. A positive correlation between the area under the disease progress curve and whitefly-days was found, where both progress curves were calculated as a function of thermal time (degree days, base 0°C). SqVYV displayed significant but variable levels of aggregation, as indicated by its fit to the β-binomial distribution, the binary power law, and ordinary runs analysis. Association analysis indicated that the viruses were largely transmitted independently. Results of this study provide epidemiological information that will be useful in the development of management strategies for SqVYV-induced vine decline, and provide new information for CuLCrV and CYSDV.

The use of latent class analysis to estimate the sensitivities and specificities of diagnostic tests for Squash vein yellowing virus in cucurbit species when there is no gold standard

Squash vein yellowing virus (SqVYV) is the causal agent of viral watermelon vine decline, one of the most serious diseases in watermelon (Citrullus lanatus L.) production in the southeastern United States. At present, there is not a gold standard diagnostic test for determining the true status of SqVYV infection in plants. Current diagnostic methods for identification of SqVYV-infected plants or tissues are based on the reverse-transcription polymerase chain reaction (RT-PCR), tissue blot nucleic acid hybridization assays (TB), and expression of visual symptoms. A quantitative assessment of the performance of these diagnostic tests is lacking, which may lead to an incorrect interpretation of results. In this study, latent class analysis (LCA) was used to estimate the sensitivities and specificities of RT-PCR, TB, and visual assessment of symptoms as diagnostic tests for SqVYV. The LCA model assumes that the observed diagnostic test responses are linked to an underlying latent (nonobserved) disease status of the population, and can be used to estimate sensitivity and specificity of the individual tests, as well as to derive an estimate of the incidence of disease when a gold standard test does not exist. LCA can also be expanded to evaluate the effect of factors and was done here to determine whether diagnostic test performances varied among the type of plant tissue being tested (crown versus vine tissue), where plant samples were taken relative to the position of the crown (i.e., distance from the crown), host (i.e., genus), and habitat (field-grown versus greenhouse-grown plants). Results showed that RT-PCR had the highest sensitivity (0.94) and specificity (0.98) of the three tests. TB had better sensitivity than symptoms for detection of SqVYV infection (0.70 versus 0.32), while the visual assessment of symptoms was more specific than TB and, thus, a better indicator of noninfection (0.98 versus 0.65). With respect to the grouping variables, RT-PCR and TB had better sensitivity but poorer specificity for diagnosing SqVYV infection in crown tissue than it did in vine tissue, whereas symptoms had very poor sensitivity but excellent specificity in both tissues for all cucurbits analyzed in this study. Test performance also varied with habitat and genus but not with distance from the crown. The results given here provide quantitative measurements of test performance for a range of conditions and provide the information needed to interpret test results when tests are used in parallel or serial combination for a diagnosis.

Physiological Effects of Squash vein yellowing virus Infection on Watermelon

Squash vein yellowing virus (SqVYV) is the cause of viral watermelon vine decline. The virus is whitefly-transmitted, induces a systemic wilt of watermelon plants, and causes necrosis and discoloration of the fruit rind. In the field, SqVYV is often detected in watermelon in mixed infections with other viruses including the aphid-transmitted Papaya ringspot virus type W (PRSV-W). In this study, watermelon plants of different ages were inoculated with SqVYV or SqVYV+PRSV-W in the greenhouse or SqVYV in the field to characterize the physiological response to infection. Symptoms of vine decline appeared about 12 to 16 days after inoculation with SqVYV regardless of plant age at time of inoculation, plant growth habit (trellised or nontrellised), and location (greenhouse or field). However, the presence of PRSV-W delayed the appearance of vine decline symptoms by 2 to 4 days, and vine decline did not develop on plants with no fruit. For all inoculation treatments, more severe symptoms were observed in younger watermelon plants. Physiological responses to SqVYV infection included reduction in plant and fruit weights, alterations in fruit rind and flesh color, reduction in fruit sucrose content, increase in fruit acid content, and changes in plant nutrient composition, particularly increases in Ca, Mg, B, Mn, and Zn and decreases in K and N. These results demonstrate wide-ranging physiological effects of SqVYV infection and provide new insights into watermelon vine decline.

Squash vein yellowing virus Infection of Vining Cucurbits and the Vine Decline Response

The responses of a diverse group of vining cucurbits to inoculation with Squash vein yellowing virus (SqVYV) were determined. For the first time, Cucurbita maxima, Cucumis dipsaceus, and Cucumis metuliferus were observed to develop necrosis and plant death similar to the SqVYV-induced vine decline in watermelon (Citrullus lanatus var. lanatus). The majority of cucurbits inoculated, however, either exhibited no symptoms of infection, or developed relatively mild symptoms such as vein yellowing of upper, noninoculated leaves. All inoculated plants were sectioned and tested for the presence of SqVYV. The virus was widely distributed in mature, fruit-bearing cucurbits with over 72% of plant sections testing positive for SqVYV by tissue-blot and/or reverse transcription-polymerase chain reaction. Plants of several cucurbits, including a wild citron (Citrullus lanatus var. citroides), were symptomless and had a decreased frequency of virus infection of vine segments compared to susceptible vining cucurbits, indicating a higher level of resistance. However, no significant relationship between the frequency of infection or virus distribution within plants and the symptom response was observed. These results demonstrate that a diverse group of cucurbits may decline when infected with SqVYV, and suggest that widespread distribution of virus within the plant is not the sole cause of decline.

Considerations of scale in the analysis of spatial pattern of plant disease epidemics

Scale is an important but somewhat neglected subject in plant pathology. Scale serves as an abstract concept, providing a framework for organizing observations and theoretical models, and plays a functional role in the organization of ecological communities and physical processes. Rich methodological resources are available to plant pathologists interested in considering either or both aspects of scale in their research. We summarize important concepts in both areas of the literature, particularly as they apply to the spatial pattern of plant disease, and highlight some new results that emphasize the importance of scaling on the emergence of different types of probability distribution in empirical observation. We also highlight the important links between heterogeneity and scale, which are of central importance in plant disease epidemiology and the analysis of spatial pattern. We consider statistical approaches that are available, where actual physical scale is known, and for more conceptual research on hierarchies, where scale plays a more abstract role, particularly for field-based research. For the latter, we highlight methods that plant pathologists could consider to account for the effect of scale in the design of field studies.

Association of Spring Pruning Practices with Severity of Powdery Mildew and Downy Mildew on Hop

Downy mildew (caused by Pseudoperonospora humuli) and powdery mildew (caused by Podosphaera macularis) are important diseases of hop in the Pacific Northwest United States, and cultural practices may affect the severity of both diseases. The association of spring pruning quality and timing with severity of downy mildew and powdery mildew was assessed through analysis of survey data collected from commercial hop yards in Oregon and Washington. Among 149 hop yards surveyed, the most common pruning method was chemical desiccation (48% of yards), mechanical pruning (23%), or a combination of these practices (15%). The quality of pruning was assessed using a three-category ordinal scale ("excellent", "moderate", or "poor") based on the amount of foliage remaining on plants following pruning. Excellent pruning quality was attained more often in yards pruned twice (74.6 to 82.1% of yards) versus once (33.8% of yards), independent of pruning method. Seasonal severity of downy mildew in Oregon increased approximately twofold with reduction in pruning quality from excellent to moderate to poor. Pruning quality was not significantly related to levels of powdery mildew on leaves or cones in Oregon. Under more severe disease pressure in Washington, however, seasonal severity of powdery mildew on leaves and the incidence of cones with powdery mildew were significantly greater in yards that had poor pruning compared with excellent pruning. Moreover, yards that had excellent pruning quality received, on average, 1.1 to 1.5 fewer fungicide applications per season for downy mildew or powdery mildew compared with yards that had moderate or poor pruning quality. This savings was associated with delayed initiation of the first application by 7.5 to 14.2 days in yards with excellent pruning quality. Replicated experiments in commercial yards in Oregon quantified the effect of delaying pruning timing 5 to 21 days compared with growers' standard practices on the diseases and yield. Downy mildew suppression by delayed pruning was dependent on cultivar and year of sampling, being significantly reduced fivefold only in 'Willamette' in 2007. Severity of powdery mildew and cone yield was similar between plots that received the delayed or standard pruning timing treatments. Collectively, these studies emphasize that early spring sanitation measures are associated with reduced primary inoculum and are critically important for managing both downy mildew and powdery mildew. A savings of at least one fungicide application per year appears achievable when spring pruning is conducted thoroughly and slightly delayed compared with growers' current practices.

Comments regarding the binary power law for heterogeneity of disease incidence

The binary power law (BPL) has been successfully used to characterize heterogeneity (overdispersion or small-scale aggregation) of disease incidence for many plant pathosystems. With the BPL, the log of the observed variance is a linear function of the log of the theoretical variance for a binomial distribution over the range of incidence values, and the estimated scale (?) and slope (b) parameters provide information on the characteristics of aggregation. When b = 1, the interpretation is that the degree of aggregation remains constant over the range of incidence values observed; otherwise, aggregation is variable. In two articles published in this journal in 2009, Gosme and Lucas used their stochastic simulation model, Cascade, to show a multiphasic (split-line) relationship of the variances, with straight-line (linear) relationships on a log-log scale within each phase. In particular, they showed a strong break point in the lines at very low incidence, with b considerably >1 in the first line segment (corresponding to a range of incidence values usually not observed in the field), and b being ?1 in the next segment (corresponding to the range of incidence values usually observed). We evaluated their findings by utilizing a general spatially explicit stochastic simulator developed by Xu and Ridout in 1998, with a wide range of median dispersal distances for the contact distribution and number of plants in the sampling units (quadrats), and through an assessment of published BPL results. The simulation results showed that the split-line phenomenon can occur, with a break point at incidence values of ?0.01; however, the split is most obvious for short median dispersal distances and large quadrat sizes. However, values of b in the second phase were almost always >1, and only approached 1 with extremely short median dispersal distances and small quadrat sizes. An appraisal of published results showed no evidence of multiple phases (although the minimum incidence may generally be too high to observe the break), and estimates of b were almost always >1. Thus, it appears that the results from the Cascade simulation model represent a special epidemiological case, corresponding primarily to a roughly nearest-neighbor population-dynamic process. Implications of a multiphasic BPL property may be important and are discussed.

Outbreak of Cucurbit Powdery Mildew on Watermelon Fruit Caused by Podosphaera xanthii in Southwest Florida

Cucurbit powdery mildew caused by the obligate parasite Podosphaera xanthii occurs commonly on foliage, petioles, and stems of most cucurbit crops grown in the United States. (3). However, in the field, fruit infection on cucurbits including watermelon (Citrullus lanatus), is rarely, if ever, observed (2). Consequently, it was atypical when severe powdery mildew-like symptoms were observed on seedless and seeded watermelon fruit on several commercial farms in southwestern Florida during November and December 2010. Severe powdery mildew was also observed on 'Tri-X 313' and 'Mickey Lee' fruit grown at SWFREC, Immokalee, FL. Infected fruit developed poorly and were not marketable. Powdery mildew symptoms were mainly observed on young immature fruit, but not on mature older fruit. Abundant powdery mildew conidia occurred on fruit surface, but not on the leaves. Conidia were produced in chains and averaged 35 × 21 μm. Observation of conidia in 3% KOH indicated the presence of fibrosin bodies commonly found in the cucurbit powdery mildew genus Podosphaera (3). Orange-to-dark brown chasmothecia (formerly cleisthothecia) containing a single ascus were detected on the surface of some fruit samples. Conidial DNA was subjected to PCR using specific primers designed to amplify the internal transcribed spacer (ITS) region of Podosphaera (4). The resulting amplicons were sequenced and found to be 100% identical to the ITS sequences of P. xanthii in the NCBI database (D84387, EU367960, AY450961, AB040322, AB040315). Sequences from the watermelon fruit isolate were also identical to several P. fusca (synonym P. xanthii), P. phaseoli (GQ927253), and P. balsaminae (AB462803) sequences. On the basis of morphological characteristics and ITS sequence analysis, the pathogen infecting watermelon fruit can be considered as P. xanthii (1,3,4). The powdery mildew isolate from watermelon fruit was maintained on cotyledons of squash (Cucurbita pepo, 'Early Prolific Straight Neck'). Cotyledons and leaves of five plants each of various cucurbits and beans were inoculated with 10 μl of a conidial suspension (10⁵conidia/ml) in water (0.02% Tween 20). Two weeks after inoculation, abundant conidia were observed on cucumber (Cucumis sativus, 'SMR-58') and melon (Cucumis melo) powdery mildew race differentials 'Iran H' and 'Vedrantais'. However, no growth was observed on melon differentials 'PI 414723', 'Edisto 47', 'PMR 5', 'PMR 45', 'MR 1', and 'WMR 29' (2,3). The powdery mildew isolate from watermelon fruit behaved as melon race 1 (3). Mycelium and conidia were also observed on fruit surface of watermelon 'Sugar Baby' and a susceptible U.S. plant introduction (PI 538888) 3 weeks after inoculation. However, the disease was not as severe as what was observed in the fields in fall 2010. The pathogen did not grow on plants of Impatiens balsamina or on select bean (Phaseolus vulgaris) cultivars ('Red Kidney', 'Kentucky Blue', and 'Derby Bush'), but did grow and produce abundant conidia on 'Pinto bush bean'. Powdery mildew on watermelon fruit in production fields can be considered as a potentially new and serious threat requiring further studies to develop management strategies. References: (1) U. Braun and S. Takamatsu. Schlechtendalia 4:1, 2000. (2) A. R. Davis et al. J. Am. Soc. Hortic. Sci. 132:790, 2007. (3) M. T. McGrath and C. E. Thomas. In: Compendium of Cucurbit Diseases. American Phytopathological Society, St. Paul, MN, 1996. (4) S. Takamatsu and Y. Kano. Mycoscience 42:135, 2001.

Cucurbit yellow stunting disorder virus Detected in Pigweed in Florida

Pigweeds (genus Amaranthus) are problematic weeds in crop production throughout the world and are responsible for significant yield losses in many crops (2). Members of this genus can produce hundreds of thousands of seeds per plant and are also capable of supporting populations of important crop pathogens including viruses, nematodes, fungi, and oomycetes. Thirty-one pigweed samples (tentatively identified as Amaranthus lividus L. based on leaf notch and growth habit) were collected in November and December of 2009 from a watermelon field near Immokalee, FL, previously found to contain watermelon plants infected with three whitefly-transmitted viruses: Cucurbit yellow stunting disorder virus (CYSDV), Cucurbit leaf crumple virus (CuLCrV), and Squash vein yellowing virus (SqVYV). Although no obvious virus symptoms were observed on any of the pigweed plants, whiteflies (Bemisia tabaci), a known vector of CYSDV, CuLCrV, and SqVYV, were observed on leaves. Consequently, replica tissue blots were made from all pigweed samples and tested independently by tissue blot nucleic acid hybridization assay for CYSDV, CuLCrV, or SqVYV (3). Tissue blots indicated CYSDV infection in six pigweed samples. Neither CuLCrV nor SqVYV was detected. Three of the tissue blot-positive pigweed samples were further tested by reverse transcription (RT)-PCR amplification from total RNA (extracted from leaf tissue with TRIzol Reagent [Invitrogen, Carlsbad, CA]) with HSP70 and coat protein (CP) gene primers (1). HSP70 and CP gene RT-PCR products of the expected sizes (175 and 707 nt, respectively) were amplified, sequenced, and found to be 100% identical for all three pigweed samples. The partial HSP70 gene sequence from pigweed shared 98.3 to 100% nucleotide identity with CYSDV isolates from Arizona, California, and Spain (GenBank Accession Nos. FJ492808, EU596530, and NC_004810, respectively). The partial CP gene sequence from pigweed shared 88.8 to 100% nucleotide identity with CYSDV isolates from Arizona, Saudi Arabia, Texas, and Spain (GenBank Accession Nos. EF210558, AF312811, AF312806, and AF312808, respectively). To our knowledge, this is the first report of CYSDV infection of pigweed in Florida. Infection of redroot pigweed (A. retroflexus) was recently reported in California (4). These results collectively indicate that control of noncucurbit weeds may be important for effective management of CYSDV in cucurbit crops. References: (1) S. Adkins et al. Online publication. doi:10.1094/PHP-2009-1118-01-BR. Plant Health Progress, 2009. (2) L. Holm et al. World's Weeds: Natural Histories and Distributions. John Wiley and Sons, Inc. New York, NY, 1997. (3) W. W. Turechek et al. Phytopathology 100:1194, 2010. (4) W. M. Wintermantel et al. Plant Dis. 93:685, 2009.

Distribution of four viruses in single and mixed infections within infected watermelon plants in Florida

Whitefly-transmitted Squash vein yellowing virus (SqVYV) and Cucurbit leaf crumple virus (CuLCrV) and aphid-transmitted Papaya ringspot virus type W (PRSV-W) have had serious impact on watermelon production in southwest and west-central Florida in the past 5 years. Tissue-blot nucleic acid hybridization assays were developed for simple, high-throughput detection of these three viruses as well as Cucurbit yellow stunting disorder virus (CYSDV), which was first reported in Florida in 2008. To determine virus distribution within plants, we collected 80 entire plants just before or during the harvest period in a systematic sample, 20 each on 11 April, 18 April, 26 April, and 3 May 2007, from a fruiting commercial watermelon field near Immokalee, FL showing symptoms of infection by SqVYV, CuLCrV, and PRSV-W and, possibly, CYSDV. This was followed by a sampling of five plants collected at harvest showing symptoms of virus infection on 11 October 2007 in a different commercial planting located in Duette, FL. Tissue prints were made from cross sections of watermelon plants from the crowns through the tips at 0.6-m intervals on nylon membranes and nucleic acid hybridization assays were used for virus detection. Results from testing crown tissue showed that SqVYV, CuLCrV, and PRSV-W were present in ≈37, 44, and 54%, respectively, of the 80 plants collected over the four sampling dates from the first field. For individual vines diagnosed with SqVYV, the distribution of SqVYV in vine tissue decreased proportionately with distance from the crown. The probability of detecting SqVYV was 70% at the base of the vine compared with 23% at the tip of the vine. In contrast, CuLCrV tended to be more evenly distributed throughout the plant, with ≈10% higher probability of detection at the growing tip relative to the crown of the plant. The distribution of PRSV-W resembled that of SqVYV but with ≈20% higher probability of detection at the tip of the vine. Similar trends were detected in the smaller sampling; however, CYSDV was also detected in three of the plants. Overall, the results indicated that SqVYV and PRSV-W were distributed differently than CuLCrV in watermelon plants, and this difference has implications on how samples should be collected and may affect vector acquisition and transmission of these viruses.

Screening molecules for control of citrus huanglongbing using an optimized regeneration system for 'Candidatus Liberibacter asiaticus'-infected periwinkle (Catharanthus roseus) cuttings

Citrus huanglongbing is one of the most destructive diseases of citrus worldwide. The disease is associated with three different species of 'Candidatus Liberibacter', of which 'Ca. L. asiaticus' is the most widely distributed. An optimized system using 'Ca. L. asiaticus'-infected periwinkle cuttings was developed to screen chemical compounds effective for controlling the bacterial population while simultaneously assessing their phytotoxicity. The optimal regeneration conditions were determined to be the use of vermiculite as a growth medium for the cuttings, and a fertilization routine using half-strength Murashige and Tucker medium supplemented with both naphthalene acetic acid (4 microg/ml) and indole-3-butyric acid (4 microg/ml). This system allowed a plant regeneration rate of 60.6% for 'Ca. L. asiaticus'-infected cuttings in contrast to the <1% regeneration rate with water alone. Two chemical agents, penicillin G sodium and 2,2-dibromo-3-nitrilopropionamide (DBNPA), were found to be effective at eliminating or suppressing the 'Ca. L. asiaticus' bacterium in this periwinkle regeneration system. When treated with penicillin G sodium at 50 microg/ml, all plants regenerated from 'Ca. L. asiaticus'-infected cuttings were 'Ca. L. asiaticus' negative as determined by both nested polymerase chain reaction (PCR) and quantitative real-time PCR. In addition, DBNPA was also able to significantly reduce the percentage of 'Ca. L. asiaticus'-positive plants and the titer of the 'Ca. L. asiaticus' bacterium at 200 microl/liter.

Site-Specific Risk Factors for Ray Blight in Tasmanian Pyrethrum Fields

Ray blight of pyrethrum (Tanacetum cinerariifolium), caused by Phoma ligulicola var. inoxydablis, can cause defoliation and reductions of crop growth and pyrethrin yield. Logistic regression was used to model relationships among edaphic factors and interpolated weather variables associated with severe disease outbreaks (i.e., defoliation severity ≥40%). A model for September defoliation severity included a variable for the product of number of days with rain of at least 0.1 mm and a moving average of maximum temperatures in the last 14 days, which correctly classified (accuracy) the disease severity class for 64.8% of data sets. The percentage of data sets where disease severity was correctly classified as at least 40% defoliation severity (sensitivity) or below 40% defoliation severity (specificity) were 55.8 and 71%, respectively. A model for October defoliation severity included the number of days with at least 1 mm of rain in the past 14 days, stem height in September, and the product of the number of days with at least 10 mm of rain in the last 30 days and September defoliation severity. Accuracy, sensitivity, and specificity were 72.6, 73.6, and 71.4%, respectively. Youden's index identified predictive thresholds of 0.25 and 0.57 for the September and October models, respectively. When economic considerations of the costs of false positive and false negative decisions and disease prevalence were integrated into receiver operating characteristic (ROC) curves for the October model, the optimal predictive threshold to minimize average management costs was 0 for values of disease prevalence greater than 0.2 due to the high cost of false negative predictions. ROC curve analysis indicated that management of the disease should be routine when disease prevalence is greater than 0.2. The models developed in this research are the first steps toward identifying and weighting site and weather disease risk variables to develop a decision-support aid for the management of ray blight of pyrethrum.

Heat Treatment Effects on Strawberry Plant Survival and Angular Leaf Spot, Caused by Xanthomonas fragariae, in Nursery Production

Angular leaf spot is an important disease in strawberry nursery production. The European and Mediterranean Plant Protection Organization (EPPO) lists Xanthomonas fragariae as an A2 quarantine pathogen. Therefore, nurseries wishing to export plants to European countries must maintain phytosanitary standards to exclude X. fragariae. To help nurseries achieve these standards, heat treatment for killing or reducing the number of viable bacterial cells in strawberry crown tissue was investigated. First, the sensitivity of bacteria to heat was determined by dispensing 1-ml aliquots of standardized cell suspensions in microcentrifuge tubes for each of four isolates of X. fragariae, including the type culture, and submerging the tubes in water at 36, 40, 44, 48, 52, and 56°C for 0, 1, 2.5, 5, 10, 15, 30, 60, 120, 240, 360, and 480 min. Bacteria were transferred to growth medium to determine the proportion surviving heat treatment. Two trials were conducted in a greenhouse to determine the sensitivity of bare-root plants to heat treatment. In the first trial, plants of cvs. Camarosa and Diamante from two different nurseries were heat treated as follows: (i) plants placed in metallic mesh cages and immersed directly into water (industry standard, direct dip); (ii) plants sealed in a plastic bag and the bag immersed in water (bagged dry); or (iii) plants wetted in warm water, sealed in a plastic bag, and then immersed in water (bagged wet). Plants were treated at 44 or 48°C for 0, 60, 120, 180, and 240 min. In the second trial, plants of cvs. Camarosa, Camino Real, Diamante, Oso Grande, Strawberry Festival, and Ventana from a single nursery were subjected to the same treatments. In both trials, plants were potted after treatment and rated for growth characteristics. Results showed that populations of bacteria exposed to 56 and 52°C were killed completely after 15 and 60 min of exposure, respectively; both treatments killed plants. Bacterial populations exposed to 44°C for 4 h or 48°C for 2 h were reduced by 10⁵ or 10⁶ CFU/ml. The same treatments minimally affected vegetative growth of plants bagged dry or wet, but flowering was adversely affected. These heat treatments were selected for testing of nursery stock of several cultivars in field trials established at two locations in successive years. The survival rate among cultivars was similar to that observed in greenhouse trials, and angular leaf spot developed appreciably only in non-heat-treated control plots. Heat treatment of strawberry nursery stock is feasible and can be used to supplement standard production practices for producing pathogen-free nursery stock.

Cucurbit leaf crumple virus Identified in Common Bean in Florida

Virus-like symptoms of leaf deformation and rugosity, especially of younger leaves, and a mild mosaic were observed on fresh market common (green) bean (Phaseolus vulgaris L.) plants in Hendry County in southwest Florida in December of 2007 and again in February of 2008. All bean fields were adjacent to watermelon fields in which Cucurbit leaf crumple virus (CuLCrV), Squash vein yellowing virus (SqVYV), and Papaya ringspot virus type W (PRSV-W) infections had previously been confirmed (fall of 2007) by PCR, reverse transcription (RT)-PCR, and/or ELISA. Whiteflies, Bemisia tabaci, were observed on both bean and watermelon plants in December and February. Fifteen samples (eleven with symptoms) were collected in December and two (both with symptoms) in February. Initial ELISA assays using commercially available antisera for potyviruses or Cucumber mosaic virus (Agdia, Elkhart, IN) were negative. Total nucleic acids were extracted and used for PCR testing. All samples tested negative by RT-PCR using specific primers for SqVYV, PRSV-W, and Cucurbit yellow stunting disorder virus, and degenerate primers for potyviruses. Ten of fifteen December samples (ten of eleven symptomatic samples) and both February samples yielded PCR products of the expected size with the degenerate begomovirus primers, PAR1c496/PAL1v1978, which amplify a portion of the begomovirus A component (3). PCR products from three December and both February samples were cloned and sequenced. The 1,159-nt PCR products shared 99% identity with each other and 96% identity with the corresponding region of A component sequences of Arizona and California CuLCrV isolates (GenBank Accession Nos. AF256200 and AF224760, respectively). Additional degenerate begomovirus primers PBL1v2040/PCRc154, which amplify a 381-nt portion of the hypervariable region of the begomovirus B component (3), and AC1048/AV494, which amplify a 533-nt portion of a conserved region of the coat protein gene (4), were used to confirm the identity of CuLCrV in the three December samples. The PBL1v2040/PCRc154 PCR products shared 98 to 99% identity with each other and 94 to 95% identity with the corresponding region of B component sequences of Arizona and California CuLCrV isolates (GenBank Accession Nos. AF327559 and AF224761, respectively), whereas the AC1048/AV494 PCR products shared 99% identity with each other and 97% identity with the corresponding region of A component sequences of Arizona and California CuLCrV isolates. Nucleic acid dot-blot hybridization assays of sap from homogenized leaves of the three December samples (from which the PCR product clones were obtained) with a digoxigenin-labeled CuLCrV cDNA probe also confirmed the presence of CuLCrV. Although CuLCrV has been reported to experimentally infect common bean and tobacco (2), to our knowledge, this is the first report of CuLCrV infecting any noncucurbit host in Florida. This finding suggests that CuLCrV may be more widely distributed than previously known in Florida (1) and that common bean (and potentially other legumes) are potential reservoirs for CuLCrV. References: (1) F. Akad et al. Plant Dis. 92:648, 2008. (2) J. K. Brown et al. Phytopathology 92:734, 2002. (3) M. R. Rojas et al. Plant Dis. 77:340, 1993. (4) S. D. Wyatt and J. K. Brown. Phytopathology 86:1288, 1996.

Spatial and temporal stability of the estimated parameters of the binary power law

The incidence of hop powdery mildew on leaves, caused by Podosphaera macularis, collected from 1,606 transects in 77 commercial hop yards in Oregon and Washington over 9 years was used to assess variability in heterogeneity of disease and the estimated binary power law parameters. Spatial analyses of data sets were conducted at the level of individual rows (row level) and multiple rows within a yard (yard level). The binary power law provided a good fit to all data sets, with R(2) values ranging from 0.933 to 0.993. At the row level, the intercept parameter ln(A(x)) was >0 for 8 years, but was not significantly greater than 0 in 2006. The parameter b was greater than 1 for all row-level data sets collected from 1999 to 2005, but was <1 in 2006 and not significantly different from 1 in 2007. Covariance analysis indicated the factor 'region' affected ln(A(x)) in 3 years, and b in 2 years. 'Cultivar' had an effect on ln(A(x)) in 3 years and b in year. At the yard level, ln(A(x)) was greater than 0 for 6 years, but in 2006 and 2007, ln(A(x)) was not significantly different from 0. The slope parameter b was greater than 1 in 6 years, but was not significantly different from 1 in 2006 and 2007. Differences in b among years were large enough to have practical implications for sample sizes and precision of fixed and sequential sampling. Although the binary power law parameter tended to be relatively stable, variability of the estimated parameters may have practical consequences for sampling precision and costs.

Analysis of Fire Blight Shoot Infection Epidemics on Apple

Fire blight incidence and spread of the shoot blight phase of the disease was studied in four apple cultivars in replicated blocks over 4 years (1994 to 1997). Cv. York was highly susceptible, followed by 'Fuji' and 'Golden Delicious,' which were moderately susceptible, and 'Liberty,' which was least susceptible. On York, the first appearance of shoot blight was within 48 h of its predicted appearance according to the Maryblyt model in 3 of the 4 years studied. Shoot blight epidemics in York in 1995 and 1996, and Fuji in 1995, were best described with a logistic model that showed apparent infection rates ranging from 0.05 to 0.20, indicating a low to moderately high rate of disease increase. The spatial positions (row and column) of all infected plants in each subplot were recorded on plot maps on each sampling date. The binomial and β-binomial distributions were fit to the data to test for spatial aggregation of disease incidence for each cultivar plot. Maximum likelihood estimation was possible for 92 (43.6%) of the 211 data sets subjected to this analysis. Of these, 35 data sets were better fit by the β-binomial distribution than the binomial distribution. The binary power law was used to characterize the relationship between the variance among quadrats within each plot to the variance expected for that plot given the observed level of disease incidence. The binary power law provided an excellent fit to the full data set and to nearly all of the subsets and, with b > 1, indicated that heterogeneity changed systematically with disease incidence. A covariance analysis was conducted to determine the effect of the factors 'year,' 'cultivar,' 'orchard plot,' and 'observation date' on the intercept and slope parameters of the binary power law. In general, plot followed by year had the greatest impact on parameter estimates and is an indication that location and seasonal factors impact heterogeneity of disease, although the specifics could not be ascertained from this study. Ordinary runs analysis was used to analyze the pattern of diseased trees within rows and detected significant nonrandom patterns of disease incidence in 63.5% of the orchard plots over the 4-year study. From these data sets, 68.7% had significantly fewer runs, particularly at disease incidences greater than 0.1. The fewer-than-expected runs at incidences greater than 0.10 provides strong evidence of localized spread.

Incidence, Distribution, and Association of Spongospora subterranea and Potato mop-top virus in Costa Rica

A survey was conducted in 39 potato (Solanum tuberosum) fields in Costa Rica to determine incidence and association of Spongospora subterranea f. sp. subterranea and Potato mop-top pomovirus (PMTV). The fields were located in Costa Rica's two major potato-production regions and were further characterized by their altitude. In all, 633 paired samples of leaf tissue and corresponding tubers were collected, assessed visually for disease, and subsequently assayed by enzyme-linked immunosorbent assay (ELISA). S. subterranea presence in tuber tissue was tested by double-antibody sandwich (DAS)-ELISA and PMTV presence in leaf and tuber tissues was tested by triple-antibody sandwich (TAS)-ELISA. Moreover, soil samples were collected from 10 fields surveyed and were evaluated for both pathogens via ELISA and bioassay. The incidence of both diseases ranged from 0 to 100% within individual fields, with incidences lower than 40% occurring in more than 70% of the fields. Higher incidences were found in fields located at higher altitudes. Of the 633 paired samples, 179 and 146 were positive for PMTV and S. subterranea, respectively, according to ELISA in either the foliage or tubers. A low correlation was found for PMTV visual symptoms and ELISA test results. Only 14 of the 81 foliar samples testing positive for PMTV had visual symptoms; the remaining 67 samples were asymptomatic. Conversely, comparison of visual evaluation with detection of S. subterranea by ELISA on tubers showed that 70% of the results were coincident. S. subterranea was detected in 4 of 10 soil samples tested by ELISA. Soilborne PMTV was detected by ELISA in roots of bait plants sown in these soil samples. Co-occurrence of both pathogens was detected in 64 samples. A significant but low degree of association for vector and virus was determined, and data suggests that S. subterranea is participating in the transmission of PMTV in Costa Rica in low frequency.

Development and optimization of a real-time detection assay for Xanthomonas fragariae in strawberry crown tissue with receiver operating characteristic curve analysis

Angular leaf spot of strawberry is caused by the bacterium Xanthomonas fragariae. The disease is transmitted primarily through systemically infected nursery stock. This creates problems for nurseries wishing to export plants to Europe because of quarantine restrictions. Currently, field inspections for symptoms are used to certify plants free of X. fragariae, but visual inspection is not useful for detecting plants infected systemically. To detect systemic infections, polymerase chain reaction (PCR) is the desired tool because of its sensitivity, specificity, and ease of use. In this study, we developed three sets of real-time PCR primers and probes and determined optimal reaction conditions for use of these primers for the detection of the bacterium X. fragariae in strawberry crown tissue. Real time detection proved to be both more sensitive and specific than standard PCR. Moreover, the detection of X. fragariae in crown tissue extract was possible with real-time PCR but not with standard PCR which is a significant improvement over standard PCR. The information on sensitivity and specificity of the primer sets was used to evaluate the performance of these primers with receiver operating characteristic (ROC) curve analysis under different tolerances. The results of this analysis can be used to provide guidance on threshold selection to manage disease below unacceptable levels. The results of this research may be useful to regulators and inspectors who must certify that plants meet European and Mediterranean Plant Protection Organization standards.

A Statistical Comparison of the Blossom Blight Forecasts of MARYBLYT and Cougarblight with Receiver Operating Characteristic Curve Analysis

ABSTRACT Blossom blight forecasting is an important aspect of fire blight, caused by Erwinia amylovora, management for both apple and pear. A comparison of the forecast accuracy of two common fire blight forecasters, MARYBLYT and Cougarblight, was performed with receiver operating characteristic (ROC) curve analysis and 243 data sets. The rain threshold of Cougarblight was analyzed as a separate model termed Cougarblight and rain. Data were used as a whole and then grouped into geographic regions and cultivar susceptibilities. Frequency distributions of cases and controls, orchards or regions (depending on the data set), with and without observed disease, respectively, in all data sets overlapped. MARYBLYT, Cougarblight, and Cougarblight and rain all predicted blossom blight infection better than chance (P = 0.05). It was found that the blossom blight forecasters performed equivalently in the geographic regions of the east and west coasts of North America and moderately susceptible cultivars based on the 95% confidence intervals and pairwise contrasts of the area under the ROC curve. Significant differences (P < 0.05) between the forecasts of Cougarblight and MARYBLYT were found with pairwise contrasts in the England and very susceptible cultivar data sets. Youden's index was used to determine the optimal cutpoint of both forecasters. The greatest sensitivity and specificity for MARYBLYT coincided with the use of the highest risk threshold for predictions of infection; with Cougarblight, there was no clear single risk threshold across all data sets.

Sequential Sampling for Estimation and Classification of the Incidence of Hop Powdery Mildew I: Leaf Sampling

Hop powdery mildew (caused by Podosphaera macularis) is an important disease of hops (Humulus lupulus) in the Pacific Northwest. Sequential sampling models for estimation and classification of the incidence of powdery mildew on leaves of hop were developed based on the beta-binomial distribution, using parameter estimates of the binary power law determined in previous studies. Stop lines, models that indicate that enough information has been collected to estimate disease incidence and cease sampling, for sequential estimation were validated by bootstrap simulations of a select group of 18 data sets (out of a total of 198 data sets) from the model-construction data, and through simulated sampling of 104 data sets collected independently (i.e., validation data sets). The achieved coefficient of variation (C) approached prespecified C values as the achieved disease incidence ( ) increased. Achieving a C of 0.1 was not possible for data sets in which < 0.10. The 95% confidence interval of the median difference between the true p and included zero for 16 of 18 data sets evaluated at C = 0.2 and all data sets when C = 0.1. For sequential classification, Monte-Carlo simulations were used to determine the probability of classifying mean disease incidence as less than a threshold incidence, p_t (operating characteristic [OC]), and average sample number (ASN) curves for 16 combinations of candidate stop lines and error levels (α and β). Four pairs of stop lines were selected for further evaluation based on the results of the Monte-Carlo simulations. Bootstrap simulations of the 18 selected data sets indicated that the OC and ASN curves of the sequential sampling plans for each of the four sets of stop lines were similar to OC and ASN values determined by Monte Carlo simulation. Correct classification of disease incidence as being above or below preselected thresholds was 2.0 to 7.7% higher when stop lines were determined by the beta-binomial approximation than when stop lines were calculated using the binomial distribution. Correct decision rates differed depending on the location where sampling was initiated in the hop yard; however, in all instances were greater than 86% when stop lines were determined using the beta-binomial approximation. The sequential sampling plans evaluated in this study should allow for rapid and accurate estimation and classification of the incidence of hop leaves with powdery mildew, and aid in sampling for pest management decision making.

Sequential Sampling for Estimation and Classification of the Incidence of Hop Powdery Mildew II: Cone Sampling

Sequential sampling models for estimation and classification of the incidence of powdery mildew (caused by Podosphaera macularis) on hop (Humulus lupulus) cones were developed using parameter estimates of the binary power law derived from the analysis of 221 transect data sets (model construction data set) collected from 41 hop yards sampled in Oregon and Washington from 2000 to 2005. Stop lines, models that determine when sufficient information has been collected to estimate mean disease incidence and stop sampling, for sequential estimation were validated by bootstrap simulation using a subset of 21 model construction data sets and simulated sampling of an additional 13 model construction data sets. Achieved coefficient of variation (C) approached the prespecified C as the estimated disease incidence, , increased, although achieving a C of 0.1 was not possible for data sets in which < 0.03 with the number of sampling units evaluated in this study. The 95% confidence interval of the median difference between of each yard (achieved by sequential sampling) and the true p of the original data set included 0 for all 21 data sets evaluated at levels of C of 0.1 and 0.2. For sequential classification, operating characteristic (OC) and average sample number (ASN) curves of the sequential sampling plans obtained by bootstrap analysis and simulated sampling were similar to the OC and ASN values determined by Monte Carlo simulation. Correct decisions of whether disease incidence was above or below prespecified thresholds (p_t) were made for 84.6 or 100% of the data sets during simulated sampling when stop lines were determined assuming a binomial or beta-binomial distribution of disease incidence, respectively. However, the higher proportion of correct decisions obtained by assuming a beta-binomial distribution of disease incidence required, on average, sampling 3.9 more plants per sampling round to classify disease incidence compared with the binomial distribution. Use of these sequential sampling plans may aid growers in deciding the order in which to harvest hop yards to minimize the risk of a condition called "cone early maturity" caused by late-season infection of cones by P. macularis. Also, sequential sampling could aid in research efforts, such as efficacy trials, where many hop cones are assessed to determine disease incidence.

Spatial Heterogeneity of the Incidence of Powdery Mildew on Hop Cones

The spatial heterogeneity of the incidence of hop cones with powdery mildew (Podosphaera macularis) was characterized from transect surveys of 41 commercial hop yards in Oregon and Washington from 2000 to 2005. The proportion of sampled cones with powdery mildew ( p) was recorded for each of 221 transects, where N = 60 sampling units of n = 25 cones assessed in each transect according to a cluster sampling strategy. Disease incidence ranged from 0 to 0.92 among all yards and dates. The binomial and beta-binomial frequency distributions were fit to the N sampling units in a transect using maximum likelihood. The estimation procedure converged for 74% of the data sets where p > 0, and a loglikelihood ratio test indicated that the beta-binomial distribution provided a better fit to the data than the binomial distribution for 46% of the data sets, indicating an aggregated pattern of disease. Similarly, the C(α) test indicated that 54% could be described by the beta-binomial distribution. The heterogeneity parameter of the beta-binomial distribution, θ, a measure of variation among sampling units, ranged from 0.01 to 0.20, with a mean of 0.037 and a median of 0.015. Estimates of the index of dispersion ranged from 0.79 to 7.78, with a mean of 1.81 and a median of 1.37, and were significantly greater than 1 for 54% of the data sets. The binary power law provided an excellent fit to the data, with slope and intercept parameters significantly greater than 1, which indicated that heterogeneity varied systematically with the incidence of infected cones. A covariance analysis indicated that the geographic location (region) of the yards and the type of hop cultivar had little effect on heterogeneity; however, the year of sampling significantly influenced the intercept and slope parameters of the binary power law. Significant spatial autocorrelation was detected in only 11% of the data sets, with estimates of first-order autocorrelation, r₁, ranging from -0.30 to 0.70, with a mean of 0.06 and a median of 0.04; however, correlation was detected in only 20 and 16% of the data sets by median and ordinary runs analysis, respectively. Together, these analyses suggest that the incidence of powdery mildew on cones was slightly aggregated among plants, but patterns of aggregation larger than the sampling unit were rare (20% or less of data sets). Knowledge of the heterogeneity of diseased cones was used to construct fixed sampling curves to precisely estimate the incidence of powdery mildew on cones at varying disease intensities. Use of the sampling curves developed in this research should help to improve sampling methods for disease assessment and management decisions.

Pre- and Post-Infection Activity of Pyraclostrobin for Control of Anthracnose Fruit Rot of Strawberry Caused by Colletotrichum acutatum

The effect of pre- and post-infection-period applications of pyraclostrobin (Cabrio EG) on the development of anthracnose fruit rot was characterized in a controlled-climate study and validated in field studies in New York and Florida. Plants of the day-neutral cv. Tristar were inoculated with C. acutatum and placed into mist chambers at 14, 22, or 30°C. The plants were removed from the chambers after 3, 6, 12, or 24 h of misting and placed on greenhouse benches to allow disease development. The fungicide pyraclostrobin was applied to the berries at a concentration equivalent to 168 g a.i./ha at 3, 8, 24, and 48 h prior to inoculation and exposure to their wetting period, or 3, 8, 24, and 48 h following inoculation and exposure to their wetting period. All pyraclostrobin treatments suppressed disease compared with the corresponding untreated control treatments. The highest incidence of disease occurred on plants exposed to the longest wetness durations (12 and 24 h) or highest temperature treatments (22 and 30°C). Post-infection applications of pyraclostrobin provided significant control when applications were made within 3 and often up to 8 h after wetting, but generally were less effective than protective sprays. We further tested the ability of pyraclostrobin to control anthracnose when applied as a protectant or as an after-infection application in inoculated field plots exposed to a short (8 h) or long (24 h) wetting period in Florida and in New York. In three of the four experimental plots, disease control equivalent to or better than the protective spray was achieved when pyraclostrobin was applied up to 24 h after infection for long and short wetting periods. In the remaining plot, conditions for disease development were exceptionally favorable. The protective treatment provided approximately 75% control, whereas the best post-infection treatment provided only 50% control. Our study indicates that for short wetting events, such as those associated with seasonal thunderstorms, growers can wait until after such an infection event before applying pyraclos-trobin and achieve control equivalent to a protective application.

Evaluating predictors of apple scab with receiver operating characteristic curve analysis

ABSTRACT Apple scab (Venturia inaequalis) is a perennial threat to apple production in temperate climates throughout the world. In the eastern United States, apple scab is managed almost exclusively through the regular application of fungicides. Management of the primary phase of disease is focused on preventing infection by ascospores. Management of secondary cycles of infection is largely dependent on how well primary infections were controlled. In this study, we used receiver operating characteristic curve analysis to evaluate how well mid-season assessments of the incidence of apple scab on cluster leaves, clusters (i.e., the whorl of cluster leaves), or immature fruit can serve as predictors of apple scab on harvested fruit (harvest scab) and whether these mid-season assessments of scab could be used reliably to manage scab under various damage thresholds. Results showed that assessment of scab on immature fruit was superior at predicting harvest scab than were assessments made on clusters or cluster leaves at all damage thresholds evaluated. A management action threshold of 7% scab incidence on immature fruit was identified by Youden's index as the optimal action threshold to prevent harvest scab incidence from exceeding 5%. Action thresholds could be higher or lower than 7% when economic assumptions were factored in to the decision process. The utility of such a predictor is discussed.

Spatial pattern analysis of hop powdery mildew in the pacific northwest: implications for sampling

ABSTRACT The spatial pattern of hop powdery mildew was characterized using 3 years of disease incidence data collected in commercial hop yards in the Pacific Northwest. Yards were selected randomly from yards with a history of powdery mildew, and two to five rows were selected for sampling within each yard. The proportion of symptomatic leaves out of 10 was determined from each of N sampling units in a row. The binomial and the beta-binomial frequency distributions were fit to the N sampling units observed in each row and to SigmaN sampling units observed in each yard. Distributional analyses indicated that disease incidence was better characterized by the beta-binomial than the binomial distribution in 25 and 47% of the data sets at the row and yard scales, respectively, according to a log-likelihood ratio test. Median values of the beta-binomial parameter theta, a measure of small-scale aggregation, were near 0 at both sampling scales, indicating that disease incidence was close to being randomly distributed. The variability in disease incidence among rows sampled in the same yard generally increased with mean incidence at the yard scale. Spatial autocorrelation analysis, used to measure large-scale patterns of aggregation, indicated that disease incidence was not correlated between sampling units over several lag distances. Results of a covariance analysis showed that heterogeneity of disease incidence was not dependent upon cultivar, region, or time of year when sampling was conducted. A hierarchical analysis showed that disease incidence at the sampling unit scale (proportion of sampling units with one or more diseased leaves) increased as a saturation-type curve with respect to incidence at the leaf level and could be described by a binomial function modified to account for the effects of heterogeneity through an effective sample size. Use of these models permits sampling at the sampling unit scale while allowing inferences to be made at the leaf scale. Taken together, hop powdery mildew was nearly randomly distributed with no discernable foci, suggesting epidemics are initiated from a well-distributed or readily dispersible overwintering population. Implications for sampling are discussed.

Nonparametric tests in plant disease epidemiology: characterizing disease associations

ABSTRACT Nonparametric tests are suited to many statistical applications, including experimental design, regression, and time series analysis, for example. Often these tests are thought of as alternatives to their parametric counterparts when certain assumptions about the underlying population are questionable. Although suited for this scenario, there are a number of nonparametric tests that fill unique niches in the analysis of data, for example, characterizing interspecific associations. Quantifying the degree of association between two or more pathogens or diseases at a defined spatial scale is essential to gain a thorough understanding of disease dynamics, generate testable hypothesis behind the mechanisms that cause association, and is often necessary in modeling applications. In this paper, nonparametric approaches to characterizing interspecific associations will be covered. Specifically, I will address the use of rank correlation coefficients and the development of a randomization procedure for testing the Jaccard index of association against a null model.

A Two-Phase Resistance Response of Venturia inaequalis Populations to the QoI Fungicides Kresoxim-Methyl and Trifloxystrobin

The class of fungicides acting as respiration inhibitors by binding to the Qo center of cyto-chrome b (QoIs) are in wide use for the management of apple scab caused by Venturia inaequalis. In order to assess responses of V. inaequalis populations to treatments with QoIs, sensitivities of isolates were determined for germinating conidia or for mycelial colonies developing from germinating conidia. Under both test conditions, inhibitory potencies of kresoxim-methyl and trifloxystrobin were largely equivalent. V. inaequalis populations treated with QoIs in a commercial and an experimental orchard both responded with significant shifts toward declining QoI sensitivities. However, the population responses were quantitative in nature, and highly resistant isolates indicative of a cytochrome b target site mutation were not detected. V. inaequalis populations from both orchards investigated also were fully resistant to sterol de-methylation-inhibiting fungicides (DMIs) such as fenarimol and myclobutanil, but isolate sensitivities to QoIs and DMIs were largely unrelated. Performance tests with kresoxim-methyl and trifloxystrobin at the experimental orchard diagnosed as DMI-resistant revealed that the quantitative shift toward declining QoI sensitivities did not constitute the status of practical QoI resistance. In contrast to these quantitative responses, emergence of qualitative QoI resistance was documented for V. inaequalis in an orchard in North Germany, which had been treated intensively with a total of 25 QoI applications over four consecutive seasons. Isolates retrieved from the orchard were highly resistant to both kresoxim-methyl and trifloxystrobin and were characterized as G143A cytochrome b mutants. The results indicated that the paths of QoI resistance can be both quantitative and qualitative in nature. A similar phenomenon has not been described before. Circumstantial evidence suggests that the quantitative phase of V. inaequalis population responses to QoIs might be succeeded by a quantitative selection of highly resistant G143A target-site mutants.

Effect of Variable Temperature on Infection Severity of Podosphaera macularis on Hops

ABSTRACT The effect of variable temperature on the infection severity of Podosphaera macularis was investigated. Potted 'Symphony' hop plants were inoculated and exposed to different temperature regimes that included supraconducive temperatures (30 to 42 degrees C) for varying periods of time (2 to 9 h). Infection severity (lesions per cm(2) of leaf area) was calculated 7 to 10 days after inoculation. Immediately exposing inoculated plants to 30 degrees C for as little as 2 h significantly (P </= 0.05) reduced infection severity compared with exposure at a constant 18 degrees C. However, exposure of inoculated plants to optimal conditions for 24 or 48 h prior to exposure to supraconducive conditions reduced this effect for plants exposed to 30, 33, or 36 degrees C. Exposure to 39 or 42 degrees C for 2 or more hours resulted in infection frequencies not significantly different from that of the uninoculated control regardless of prior exposure to favorable conditions. Exposure to simulated field temperatures programmed into growth chambers indicated that inoculation at 1700 or 2100 h resulted in significantly more disease than did inoculation at 0900 or 1300 h. Plants exposed to supraconducive or simulated field temperatures for 7 days prior to inoculation developed significantly lower disease severity than did plants maintained at 18 degrees C for 7 days. The magnitude, length, and time of exposure to supraconducive temperatures in relation to time of inoculation plays an important role in the development of hop powdery mildew, and rules addressing these variables could be a useful addition to disease risk assessment models.

A generalized linear modeling approach for characterizing disease incidence in a spatial hierarchy

ABSTRACT Several statistical models are introduced to quantify the effect of heterogeneity on disease incidence relationships in a three-scale spatial hierarchy: the sampling unit level (highest), the leaf scale (intermediate), and the leaflet scale (lowest). The models are an extension of the theory previously developed for a two-scale hierarchy and were tested using data collected from strawberry leaf blight epidemics. Disease incidence at the sampling-unit scale (proportion of sampling units with one or more diseased leaflets) increased as a saturation-type curve with increasing leaflet or leaf disease incidence (proportion of leaflets or leaves diseased) as predicted by the good fit of the beta-binomial distribution to the leaflet and leaf data. The relationship could be accurately described, without curve fitting, by several simple nonlinear models, in which the aggregation of disease was represented by a modified binomial function incorporating an effective sample size that was either constant or dependent on mean incidence. The relationship between incidence at the leaflet and leaf scales could be modeled based on the combined sampling-unit models for leaflets and leaves. By taking the complementary log-log (CLL) transformation of incidence, the equations could be expressed as generalized linear models, and curve fitting used to estimate the parameters. Generally, curve fitting gave slight to no improvement in the accuracy of the predictions of incidence. These models have broad applicability in sampling for disease incidence, and results can be used to interpret how diseased individuals at the lowest level in a hierarchy are arranged within sampling units.

First Report of Strawberry Anthracnose (Colletotrichum acutatum) in Strawberry Fields in New York

Strawberry plants with red to black, sunken, fusoid lesions on runners and leaf petioles were found in several first-year plantings in grower's fields in western New York in 2000. Affected cultivars included Honeoye, Jewel, and Primetime. Sections of petiole were excised from lesion margins and plated on potato dextrose agar (PDA) amended with chloramphenicol, streptomycin sulfate, and tetracycline hydrochloride at 100 μg/ml. The fungus, Colletotrichum acutatum (J.H. Simmonds), was consistently isolated and identified based on conidia morphology and its growth rate in culture relative to reference cultures of C. acutatum, C. gloeosporoides, and C. fragariae (1,2). The average size of conidia produced on PDA was 15.2 × 5 μm. For each of six isolates, three plants each of six-week-old Honeoye and Kent were spray inoculated with a conidial suspension (10⁶ conidia per ml), and petioles, leaves, and crowns were stabbed with a sterile pin following inoculation. After 14 days at 20 to 25°C, petioles and leaves on all inoculated plants developed lesions consistent with those seen in the field. The fungus was readily reisolated from leaf and petiole lesions. Subsequent inoculations on detached fruit under the same conditions yielded circular, sunken, dry lesions that produced a salmon-colored, slimy, spore mass typical of C. acutatum. This is the second report of strawberry anthracnose in the northeastern United States (3) and to our knowledge, the first report in New York. References: (1) J. A. García Muñoz et al. Mycologia 92:288, 2000. (2) P. S. Gunnel and W. D. Gubler. Mycologia 84:157, 1992. (3) J. A. LaMondia. Plant Dis. 75:1286, 1991.

Evaluation of Generalized Linear Mixed Models for Analyzing Disease Incidence Data Obtained in Designed Experiments

Diseased individuals (e.g., leaves, plants) typically are clustered in nature, resulting in greater heterogeneity or variability of disease incidence than would be expected for a random pattern. To account for this variability, as well as the binary nature of disease incidence and the multiple sources of variation in designed experiments, a generalized linear mixed model (GLMM) can be used to analyze collected data. GLMMs are becoming more common in many disciplines and may be preferred over analysis of variance for non-normally distributed data. We evaluated several GLMMs for analyzing the incidence of Phomopsis leaf blight of strawberry in relation to fungicide treatments in five experiments which varied greatly in mean incidence and the differences in incidence between treatments. The first model form accounted for heterogeneity through the residual variance (i.e., the overdispersion parameter), which was assumed to be either fixed for the experiment, or dependent on either treatment or incidence. The second model form accounted for heterogeneity explicitly through a within-plot sampling variance, which was assumed to be either constant or dependent on treatment. All GLMMs could be successfully fitted to the data in each experiment, but there was weak evidence based on the conditional deviance and residual plots that the residual-variance models were more appropriate than the sampling-variance models. Model choice had only a minor effect on F tests for treatment effects and significant differences between treatment means. Based on ease of use and evaluation results, we recommend that the simplest (fixed residual variance) model be used as the first choice in analyzing disease incidence data using GLMMs.

Sequential sampling for incidence of phomopsis leaf blight of strawberry

ABSTRACT Sequential sampling models for estimation and classification were developed for the incidence of strawberry leaflets infected by Phomopsis obscurans. Sampling protocols were based on a binary power law analysis of the spatial heterogeneity of Phomopsis leaf blight in commercial fields in Ohio. For sequential estimation, samples were collected until mean disease incidence could be estimated with a preselected coefficient of variation of the mean (C). For sequential classification, samples were collected until there was sufficient evidence to classify mean incidence as being below or above a threshold (p(t)) based on the sequential probability ratio test. Monte-Carlo simulations were used to determine the theoretical average sample number (ASN) and probability of classifying mean incidence as less than p(t) (operating characteristic) for any true value of incidence. Estimation and classification sampling models were both tested with bootstrap simulations of randomly selected data sets and validated by data sets from another year that were not utilized in developing the models. In general, achieved (or calculated) C after sequentially sampling for estimation was close to the preselected C of 0.2, and mean incidence was estimated with little bias. Achieving a C of 0.1 with less than 75 sampling units (the nominal value for many original data sets) was more problematical, especially with true incidence less than 0.2. ASN for classification was only 9 to 18 at disease incidence values near p(t), and approximately five or less at incidence values far from p(t). Correct classification decisions were made in over 88% of the validation data sets. Results indicated that it is possible to estimate Phomopsis leaf blight with high precision and with high correct classification probabilities.

Development of Management Strategies for Hop Powdery Mildew in the Pacific Northwest

Hop powdery mildew, caused by Sphaerotheca macularis, was first discovered in the Yakima Valley of Washington in 1997 and has since become the most serious disease of hop (Humulus lupus) in the Pacific Northwest. Lack of understanding of the epidemiology of S. macularis has made it difficult to develop sound management practices. Results from our field and laboratory studies suggest that control measures applied early in the growing season are probably the most important in shaping the epidemic in a particular field and that late season control measures may not need to be applied at the same intensity as in early to mid-season.

Accepted for publication 9 March 2001. Published 13 March 2001.

Analysis of the association between the incidence of two spatially aggregated foliar diseases of strawberry

ABSTRACT Association of the incidence of leaf blight (caused by Phomopsis obscurans) and leaf spot of strawberry (caused by Mycosphaerella fragariae) was assessed at multiple scales in perennial plantings at several commercial farms over 3 years (1996 to 1998). For each field, the presence or absence of each disease was recorded from n = 15 leaflets in each of N approximately 70 evenly spaced sampling units, and the proportion of leaflets with blight, spot, and total disease (blight or spot) was determined. Individual diseases and total disease incidence were all well described by the beta-binomial distribution but not by the binomial distribution, indicating overdispersion of disease. The Jaccard similarity index was used to measure disease co-occurrence at the leaflet, sampling-unit, and field scales. Standard errors of this index for the lower two scales were obtained using the jackknife (resampling) procedure, and data randomizations were used to determine the expected Jaccard index for an independent arrangement of the two diseases, conditioned on the incidence and spatial heterogeneity of the observed disease data. Results based on these statistics showed that only 4 of 52 data sets at the leaflet level and no data sets at the sampling-unit level had Jaccard index values significantly different from that expected under an independent rearrangement of the two diseases. Rank correlation and cross-correlation statistics were calculated to determine the degree of covariation in incidence between the two diseases. Additionally, covariation between diseases was tested using a new procedure in the Spatial Analysis by Distance IndicEs (SADIE) class of tests. Covariation was detected in 21% of the data sets using rank correlation methods and in 15% of the data sets using the SADIE-based approach. The discrepancy between these two methods may be due to the rank correlation procedure not taking into account the effects of spatial pattern of disease incidence. There was no relationship between mean disease incidence per field of spot and blight or between degree of heterogeneity of the two diseases (as measured by theta of the beta-binomial distribution), demonstrating lack of covariation at the field scale. Incidence of leaflets with either disease (total disease incidence) could be well predicted using a linear combination of the estimated probabilities of leaf blight and leaf spot incidence based on independence of the two diseases. Heterogeneity of total disease incidence, measured with the estimated theta parameter of the beta-binomial distribution, could also be well predicted using a linear combination of the weighted theta values for leaf blight and leaf spot, with weights proportional to incidence of the individual diseases.

Spatial Pattern Analysis and Sequential Sampling for the Incidence of Leaf Spot on Strawberry in Ohio

Spatial pattern of the incidence of strawberry leaf spot, caused by Mycosphaerella fragariae (Ramularia brunnea), was quantified on commercial strawberry farms in Ohio. For each planting of strawberry, one or two transects were randomly chosen, and the proportion of leaflets (out of 15) with leaf spot was determined from N = 29 to 87 evenly spaced sampling units. Based on a likelihood ratio test, the beta-binomial distribution described the frequency of diseased leaflets better than the binomial in 93% of the 59 data sets over 3 years. Estimates of mean incidence ranged from 0.0009 to 0.82, with a median of 0.05. Estimates of the beta-binomial aggregation parameter, θ, ranged from 0 to 1.06, with a median of 0.20. Moreover, the estimate of the slope of the binary power law, fitted to the variance data for the 59 data sets, was significantly (P < 0.01) greater than one, indicating that heterogeneity, and hence the pattern of disease incidence at the spatial scale of the sampling units or smaller, was dependent on mean incidence. Spatial autocorrelation and Spatial Analysis by Distance IndicEs (SADIE) analyses detected significant positive association of disease incidence among sampling units in approximately 40% of the data sets, indicating that disease clusters extended beyond the borders of the sampling units in these fields. Collectively, the results show that strawberry leaf spot was characterized by relatively tight clusters of disease (based on θ) that extended beyond the borders of the sampling units in a little under half of the data sets (based on correlations). The information on heterogeneity was used to develop fixed and sequential sampling curves to precisely estimate disease incidence. The sequential-estimation procedure was evaluated using statistical bootstrap methods and performed well over the range of disease incidences encountered.

Spatial pattern analysis of strawberry leaf blight in perennial production systems

ABSTRACT Spatial pattern of the incidence of strawberry leaf blight, caused by Phomopsis obscurans, was quantified in commercial strawberry fields in Ohio using statistics for heterogeneity and spatial correlation. For each strawberry planting, two transects were randomly chosen and the proportion of leaflets (out of 15) and leaves (out of five) with leaf blight symptoms was determined from N = 49 to 106 (typically 75) evenly spaced sampling units, thus establishing a natural spatial hierarchy to compare patterns of disease. The beta-binomial distribution fitted the data better than the binomial in 92 and 26% of the 121 data sets over 2 years at the leaflet and leaf levels, respectively, based on a likelihood ratio test. Heterogeneity in individual data sets was measured with the index of dispersion (variance ratio), C(alpha) test, a standard normal-based test statistic, and estimated theta parameter of the beta-binomial. Using these indices, overdispersion was detected in approximately 94 and 36% of the data sets at the leaflet and leaf levels, respectively. Estimates of the slope from the binary power law were significantly (P < 0.01) greater than 1 and estimates of the intercept were significantly greater than 0 (P < 0.01) at both the leaflet and leaf levels for both years, indicating that degree of heterogeneity was a function of incidence. A covariance analysis indicated that cultivar, time, and commercial farm location of sampling had little influence on the degree of heterogeneity. The measures of heterogeneity indicated that there was a positive correlation of disease status of leaflets (or leaves) within sampling units. Measures of spatial association in disease incidence among sampling units were determined based on autocorrelation coefficients, runs analysis, and a new class of tests known as spatial analysis by distance indices (SADIE). In general, from 9 to 22% of the data sets had a significant nonrandom spatial arrangement of disease incidence among sampling units, depending on which test was used. When significant associations existed, the magnitude of the association was small but was about the same for leaflets and leaves. Comparing test results, SADIE analysis was found to be a viable alternative to spatial autocorrelation analysis and has the advantage of being an extension of heterogeneity analysis rather than a separate approach. Collectively, results showed that incidence of Phomopsis leaf blight was primarily characterized by small, loosely aggregated clusters of diseased leaflets, typically confined within the borders of the sampling units.