Dissemination of Goss's Wilt of Corn and Epiphytic Clavibacter michiganensis subsp. nebraskensis from Inoculum Point Sources.

Goss's wilt of corn, caused by Clavibacter michiganensis subsp. nebraskensis, has reemerged since 2006 as an economically important disease of corn in in the Midwestern United States. In 2012 and 2013, field plot studies were conducted with a pathogenic, rifampicin-resistant C. michiganensis subsp. nebraskensis isolate and a Goss's wilt-susceptible corn hybrid to monitor epiphytic C. michiganensis subsp. nebraskensis population densities and the temporal and spatial spread of Goss's wilt incidence originating from inoculum point sources. The randomized complete block trial included three treatments: noninoculated control, inoculum point sources established by wound inoculation, and inoculum point sources consisting of C. michiganensis subsp. nebraskensis-infested corn residue. Epiphytic C. michiganensis subsp. nebraskensis was detected on asymptomatic corn leaves collected up to 2.5 m away from inoculum sources at 15 days after inoculation in both years. The percentage of asymptomatic leaf samples on which epiphytic C. michiganensis subsp. nebraskensis was detected increased until mid-August in both years, and reached 90, 55, and 35% in wound-, residue-, and noninoculated plots, respectively, in 2012; and 50, 11, and 2%, respectively, in 2013. Although both growing seasons were drier than normal, Goss's wilt incidence increased over time and space from all C. michiganensis subsp. nebraskensis point sources. Plots infested with C. michiganensis subsp. nebraskensis residue had final Goss's wilt incidence of 7.5 and 1.8% in 2012 and 2013, respectively; plots with a wound-inoculated source had final Goss's wilt incidence of 16.6 and 14.0% in 2012 and 2013, respectively. Our findings suggest that relatively recent outbreaks of Goss's wilt in new regions of the United States may be the result of a gradual, nondetected buildup of C. michiganensis subsp. nebraskensis inoculum in fields.

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.

Quantifying Loss Caused by Ray Blight Disease in Tasmanian Pyrethrum Fields.

The efficacy of newly implemented fungicide recommendations on reducing the intensity of ray blight disease caused by Phoma ligulicola to achieve site-specific attainable yield potentials in Tasmanian pyrethrum fields was quantified over two seasons in 46 and 51 fields during the 2003 and 2004 growing seasons, respectively. Disease intensity and yield in two plots (10 × 24 m), one following the commercial fungicide protocol recommendations and the second receiving no fungicide, were assessed in each pyrethrum field. The commercial fungicide protocol consisted of one application of azoxystrobin at 150 g a.i./ha, followed by two applications of a tank mixture of difenoconazole at 125 g a.i./ha and chlorothalonil at 1,008 liters a.i./ha at 14- to 21-day intervals. This program resulted in significant decreases in defoliation severity and the incidence of stems and flowers with ray blight, and increases in the height of stems and number of flowers produced per stem in October and November. In plots receiving the commercial fungicide protocol, the dry weight of flowers was increased by 76 and 68% in 2003 and 2004, respectively. Moreover, pyrethrin yield increased by 81 and 78% when the commercial fungicide protocol was used compared with the nontreated plots. Tobit regression was used to examine the relationships and thresholds among disease intensity measures (defoliation severity, stem severity, and incidence of flowers with ray blight) assessed just prior to harvest. This regression utilized a left-censored regression model to define subminimal thresholds, as none of the disease intensity measures could be less than 0. Defoliation severity had a threshold of 35.3% before stem severity linearly increased and a threshold of 38.2% before the incidence of flowers with ray blight linearly increased. Finally, the threshold for stem severity was 13.7% before the incidence of flowers with ray blight linearly increased. These thresholds can be used to assist growers in making disease management decisions with the objective of minimizing loss of flowers by maintaining defoliation severity below the critical point at which the incidence of flowers with ray blight begins to linearly increase.

Use of a Multispectral Radiometer for Noninvasive Assessments of Foliar Disease Caused by Ray Blight in Pyrethrum.

Foliar disease due to ray blight (Phoma ligulicola) in pyrethrum was quantified at three locations over 2 years in Tasmania, Australia. To obtain a range of ray blight disease intensities, replicated plots were treated with fungicides that varied in efficacy to control ray blight. Visual disease assessments and measurement of canopy reflectance were made at least once during spring (September through December). Visual assessments involved removal of flowering stems at ground level from which measurements of defoliation severity and the incidence of stems with ray blight were obtained. Reflectance of sunlight from pyrethrum canopies was measured at 485, 560, 660, 830, and 1,650 nm using a handheld multispectral radiometer. Measurements from these wavelengths also were used to calculate all possible reflectance ratios, as well as four vegetative indices. Relationships between wavelength bands, reflectance ratios, vegetative indices, and disease intensity measures were described by linear regression analyses. Several wavelength bands, ratios, and vegetative indices were significantly related in a linear fashion to visual measures of disease intensity. The most consistent relationships, with high R2 and low coefficients of variation values, varied with crop growth stage over time. The ratio 830/560 was identified as the best predictor of stem height, defoliation severity, and number of flowers produced on each stem in October. However, reflectance within the near-infrared range (830 nm) and the difference vegetative index was superior in November. The use of radiometric assessment of disease was noninvasive and provided savings in disease assessment time, which is critical where visual assessment is difficult and requires destructive sampling, as with pyrethrum.

Quantification and modeling of crop losses: a review of purposes.

This review considers the cascade of events that link injuries caused by plant pathogens on crop stands to possible (quantitative and qualitative) crop losses (damage), and to the resulting economic losses. To date, much research has focused on injury control to prevent this cascade of events from occurring. However, this cascade involves a complex succession of components and processes whereby knowledge on crop loss generates entry points for management. Proposed here is a framework linking different types of knowledge on crop loss to a range of decision categories, from tactical to strategic short- or long-term. Important advances in this field are now under way, including a probabilistic treatment of the injury-damage relationship, or analyses of the sources of uncertainty attached to some components of the decision process. Management of injury profiles, rather than individual injuries, and shifts in dimensionality of crop losses are anticipated to contribute to the design of sustainable agricultural systems, and address global issues concerning food security and food safety.

Use of Survival Analysis to Determine the Postincubation Time-to-Death of Papaya Due to Yellow Crinkle Disease in Australia.

The current management recommendation for papaya (Carica papaya) plants exhibiting symptoms of yellow crinkle disease in Australia is the practice of ratooning infected plants. Ratooning involves removing the main stem of diseased papaya plants and allowing a lateral stem (supposedly pathogen-free) to develop and replace the diseased stem. Using nonparametric and parametric methods of survival analysis, we tested different hypotheses regarding plant factors that may influence the postincubation period survival time of phytoplasma-infected papaya. The factors included plant age, the season (wet versus dry) when papaya plants first became symptomatic, and the two predominant phytoplasma strains causing papaya yellow crinkle: tomato big bud (TBB) or sweet potato little leaf strain V4 (SPLL-V4). Median survival time was estimated to be from 4 to 5 months. Therefore, we estimated that the infectious period (incubation period plus the period from postincubation to time-to-death period) of infected papaya ranges from 6 to 9 months. Using parametric accelerated failure modeling and nonparametric Cox proportional hazard modeling, no significant improvement from a null model (no covariates) was found when analyzing plant age, the season a plant was observed to be symptomatic, or phytoplasma strain. However, the season in which a papaya plant became symptomatic differed between the two phytoplasma strains, indicating that the TBB and SPLL-V4 strains may have different modes of insect acquisition and transmission. Because of the long infectious period and the rate of plantto-plant spread, we question the use of ratooning as the primary management tactic for managing papaya yellow crinkle.

Spatiotemporal Description of Epidemics Caused by Phoma ligulicola in Tasmanian Pyrethrum Fields.

ABSTRACT Spatial and temporal patterns of foliar disease caused by Phoma ligulicola were quantified in naturally occurring epidemics in Tasmanian pyrethrum fields. Disease assessments (defoliation incidence, defoliation severity, incidence of stems with ray blight, and incidence of flowers with ray blight) were performed four times each year in 2002 and 2003. Spatial analyses based on distribution fitting, runs analysis, and spatial analysis by distance indices (SADIE) demonstrated aggregation in fields approaching their first harvest for all assessment times between September and December. In second-year harvest fields, however, the incidence of stems with ray blight was random for the first and last samplings, but aggregated between these times. Spatiotemporal analyses were conducted between the same disease intensity measures at subsequent assessment times with the association function of SADIE. In first-year harvest fields, the presence of steep spatial gradients was suggested, most likely from dispersal of conidia from foci within the field. The importance of exogenous inoculum sources, such as wind-dispersed ascospores, was suggested by the absence of significant association between defoliation intensity (incidence and severity) and incidence of stems with ray blight in second-year harvest fields. The logistic model provided the best temporal fit to the increase in defoliation severity in each of six first-year harvest fields in 2003. The logistic model also provided the best fit for the incidence of stems with ray blight and the incidence of flowers with ray blight in four of six and three of six fields, respectively, whereas the Gompertz model provided the best fit in the remaining fields. Fungicides applied prior to mid-October (early spring) significantly reduced the area under disease progress curve (P < 0.001) for defoliation severity, the incidence of stems with ray blight, and the incidence of flowers with ray blight for epidemics at all field locations. This study provides information concerning the epidemiology of foliar disease and ray blight epidemics in pyrethrum and offers insight on how to best manage these diseases.

Temporal and Spatial Analysis of Grapevine Leafroll-Associated Virus 3 in Pinot Noir Grapevines in Australia.

An epidemic of grapevine leafroll disease (GLD), caused by grapevine leafroll-associated virus 3 (GLRaV-3), was monitored over an 11-year period in Nuriootpa, South Australia. Inoculum originated from infected budwood, and initial GLD incidence at the time of transplanting in 1986 was 23.1%. Infected vines were planted in a random spatial pattern. Change in disease incidence was not observed until 8 years after planting, when disease incidence increased to 27.9%. Disease incidence increased to 51.9% by 1996. Disease progress and rate curves (dy/dt versus time) indicated that the logistic (R2 = 96.2) and Gompertz (R2 = 96.3) growth models would best describe disease progress. However, the logistic model, which has a simpler data transformation with fewer model assumptions, was chosen for the purpose of comparing this epidemic (South Australia) with a GLRaV-3 epidemic in Cabernet Sauvignon grapevines in New Zealand. The logistic rate of GLD spread with respect to time was 0.35 logit/year in South Australia and was nearly three times faster (1.19 logits/year) for GLRaV-3 spread in New Zealand. Ordinary runs analyses indicated that the arrangement of infected vines within rows in South Australia was random up to 8 years after transplanting but subsequently became highly aggregated. Thus, GLD-infected plants are contributing to new infections (i.e., there is evidence for plant-to-plant spread), and a biotic vector with a steep dispersal gradient from each point source is likely to be involved.