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.

Temperature response curves under diurnal oscillating temperatures differ from those under constant conditions for all stages of the Phytophthora infestans infection cycle on potatoes. We developed a mechanistic model (BLIGHTSIM) with an hourly time step to simulate late blight under fluctuating environmental conditions and predict late blight epidemics in potato fields. BLIGHTSIM is a modified susceptible (S), latent (L), infectious (I) and removed (R) compartmental model with hourly temperature and relative humidity as driving variables. The model was calibrated with growth chamber data covering one infection cycle and validated with field data from Ecuador. The model provided a good fit to all data sets evaluated. There was a significant interaction between average temperature and amplitude in their effects on the area under the disease progress curve (AUDPC) as predicted from growth chamber data on a single infection cycle. BLIGHTSIM can be incorporated in a potato growth model to study effects of diurnal temperature range on late blight impact under climate change scenarios.

Fusarium wilt caused by Fusarium oxysporum f. sp. niveum (Fon) is an important watermelon (Citrullus lanatus) disease in Florida and the southeast. This disease can cause complete yield loss when susceptible cultivars are grown (Egel and Martyn 2013). Disease symptoms include vascular discoloration, especially around crown and upper taproot and withering and wilting leaves followed by death of either a vine or the whole plant. A Fon isolate was collected from Madison County, Florida in May 2015. It was recovered from infected stem slices that were surface sterilized for 1 min in 0.85% sodium hypochlorite and rinsed with sterile water. The slices were incubated on quarter strength potato dextrose agar (QPDA) until hyphae emerged from the vascular tissue. Conidia from these slices were streaked onto water agar. After 15 h a germinated conidium was transferred to QPDA to obtain a monoconidial culture and labeled 150525. The isolate was amplified by PCR using EF-1α and IGS (O'Donnell et al. 2009) loci. BLAST ...

Watermelon is an important commercial crop in the Southeastern United States and around the world. However, production is significantly limited by biotic factors including fusarium wilt caused by the hemibiotrophic fungus Fusarium oxysporum forma specialis niveum (Fon). Unfortunately, this disease has increased significantly in its presence over the last several decades as races have emerged which can overcome the available commercial resistance. Management strategies include rotation, improved crop resistance, and chemical control, but early and accurate diagnostics are required for appropriate management. Accurate diagnostics require molecular and genomic strategies due to the near identical genomic sequences of the various races. Bioassays exist for evaluating both the pathogenicity and virulence of an isolate but are limited by the time and resources required. Molecular strategies are still imperfect but greatly reduce the time to complete the diagnosis. This article presents the current state of the research surrounding races, both how races have been detected and diagnosed in the past and future prospects for improving the system of differentiation. Additionally, the available Fon genomes were analyzed using a strategy previously described in separate formae speciales avirulence gene association studies in Fusarium oxysporum races.

Target spot of tomato caused by Corynespora cassiicola is one of the most economically destructive diseases of tomato in Florida. A collection of 123 isolates from eight counties in Florida were evaluated for sensitivity to azoxystrobin and fenamidone based on mycelial growth inhibition (MGI), spore germination (SG), detached leaflet assays (DLAs), and sequence-based analysis of the cytochrome b gene (cytb). Cleavage of cytb by restriction enzyme (Fnu4HI) revealed the presence of a mutation conferring a glycine (G) to alanine (A) mutation at amino acid position 143 (G143A) in approximately 90% of the population, correlating with quinone outside inhibitor (QoI) resistance based on MGI (<40% at 5 μg/ml), SG (<50% at 1 and 10 μg/ml), and DLA (<10% severity reduction). The mutation conferring a phenylalanine (F) to leucine (L) substitution at position 129 (F129L) was confirmed in moderately resistant isolates (#9, #19, and #74) based on MGI (40 to 50% at 5 μg/ml), SG (50% at 10 μg/ml), and DLA (>10% and 50% at 5 μg/ml), SG (>50% at 1 μg/ml and 10 μg/ml), and DLA (>50% severity reduction) correlated to non-mutation-containing isolates or those with a silent mutation. This study indicates that QoI resistance among C. cassiicola isolates from tomato is widespread in Florida and validates rapid screening methods using MGI or molecular assays to identify resistant isolates in future studies.

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.