Late and early leaf spot, respectively caused by Nothopassalora personata and Passalora arachidicola, are damaging diseases of peanut (Arachis hypogaea) capable of defoliating canopies and reducing yield. Although one of these diseases may be more predominant in a given area, both are important on a global scale. To assist informed management decisions and quantify relationships between end-of-season defoliation and yield loss, meta-analyses were conducted over 140 datasets meeting established criteria. Slopes of proportion yield loss with increasing defoliation were estimated separately for Virginia and runner market type cultivars. Yield loss for Virginia types was described by an exponential function over the range of defoliation levels, with a loss increase of 1.2 to 2.2% relative to current loss levels per additional percent defoliation. Results for runner market type cultivars showed yield loss to linearly increase 2.2 to 2.8% per 10% increase in defoliation for levels up to approximately 95% defoliation, after which the rate of yield loss was exponential. Defoliation thresholds to prevent economic yield loss for Virginia and runner types were estimated at 40 and 50%, respectively. Although numerous factors remain important in mitigating overall yield losses, the integration of these findings should aid recommendations about digging under varying defoliation intensities and peanut maturities to assist in minimizing yield losses.

Controlled-environment studies were conducted to examine effects of temperature (T) and wetness duration (W) on the sporulation rate of Phomopsis viticola on infected grape canes and to determine effects of interrupted wetness duration (IWD) on sporulation. A split-plot design was used to determine T and W effects, with T (5, 12, 15, 18, 20, 22, 25, 28, and 35°C) as the whole-plot and W (11, 23, 35, 47, and 71 h) as the subplot. Linear and nonlinear mixed models were fitted to the data. Lower and upper limits of sporulation were estimated to be 4 and 36°C, respectively, based on the modeling results, optimum sporulation was near 21°C, and sporulation increased monotonically with increasing wetness duration. Of the examined models, a generalization of the Analytis Beta model fit the data best, based on a collection of goodness-of-fit statistical criteria. To determine effects of IWD, a split-plot was used, with T (12, 15, and 20°C) as the whole-plot and IWD (0, 2, 4, 8, 12, and 24 h) as the subplot. Generally, sporulation declined with increasing IWD. An IWD of 8 h or more resulted in significantly and substantially less sporulation compared to the control (0 h IWD) (P < 0.01). Temporal patterns of spore density in the field were determined using a repeated-measures design, in which spore density and environmental data were measured in the vineyard during and following individual rain events over 3 years. The developed model from the controlled-environment study, coupled with a time-of-season weight function and a dispersal index (based on total rain per rain episode), predicted the trend in spore density over time reasonably well, although the total magnitude of spore density could not be predicted because the density of lesions was not known. Results can be used for improving the accuracy of a disease warning system that currently only considers infection of grapes by P. viticola.

A quantitative PCR (qPCR)-assay was developed to detect airborne inoculum of Nothopassalora personata, causal agent of late leaf spot (LLS) on peanut, collected with a modified impaction spore trap. The qPCR assay was able to consistently detect as few as 10 spores with purified DNA and 25 spores based on crude DNA extraction from rods. In 2019, two spore traps were placed in two peanut fields with a history of LLS. Sampling units were replaced every 2 to 4 days and tested with the developed qPCR assay, while plots were monitored for symptom development. The system detected inoculum 35 to 56 days before visual symptoms developed in the field, with detection related to environmental parameters affecting pathogen life-cycle and disease development. This study develops the framework of the qPCR spore trap system and represents the initial steps towards validation of the performance of the system for use as a decision support tool to complement integrated management of LLS.

Phomopsis cane and leaf spot on Vitis spp. (grape) is currently understood to be monocyclic, with primary inoculum only being produced early in the growing season. However, of the few published studies pertaining to sporulation of Phomopsis viticola, none specifically examined rachises, and none were designed to determine when infected tissues become capable of sporulation. The objective of these studies was to determine when grape shoots, canes, and rachises infected with P. viticola develop the capacity to sporulate, and to determine the time period during which those tissues remain capable of sporulation. Starting in 2009 and 2010, infected first-year shoots and rachises were collected biweekly throughout the growing season, into the dormant season, and into the following growing season. Tissues were collected from ‘Catawba,’ ‘Concord,’ and ‘Reliance’ vineyards. Samples were observed for sporulation after 48 h of incubation in a moist chamber at 23°C; the magnitude of the conidia production under these optimal conditions was considered the sporulation potential. For infections that occurred in 2009 and 2010, the production of conidia was not observed until after harvest. In the year following infection, sporulation potential was found from about bud break until shortly after the end of bloom. There was a generally consistent temporal pattern to relative sporulation potential across sampled vineyards, years, and grape tissues (rachises and canes), described by a modified β model, with peak sporulation potential occurring around 16 May. These results confirmed that Phomopsis cane and leaf spot is a monocyclic disease and support control recommendations for use of fungicides in spring.

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.