Progress report for GS24-307
Project Information
Pseudoperonospora cubensis is an oomycete pathogen that causes cucurbit downy mildew (CDM) on a wide range of cucurbitaceous hosts. CDM results in significant crop losses in the US annually, and it is a major disease limiting cucurbit production. The pathogen has two genetic clades that have differences in host preference and fungicide sensitivity. This pathogen is dispersed via air currents and it is mainly managed with weekly fungicide applications since complete host resistance is not commercially available. Contact fungicides are applied weekly while CDM site-specific fungicide applications are only initiated once the disease is detected in a neighboring state due to their higher cost. A challenge in CDM management is cost-effective fungicide use and prevention of fungicide resistance for site-specific fungicides. To reduce fungicide application costs and improve outcomes, we propose a CDM monitoring system that relies on mobile spore trapping combined with molecular tests for pathogen clade detection and fungicide resistance monitoring. Our system will quickly sample large fields to detect the pathogen prior to disease onset, which will reduce the number of applications for site-specific fungicides. Our qPCR molecular tests will inform: 1) which host to spray based on clade detection and host preference, 2) which fungicides are not effective due to detection of fungicide resistance mutations. Our CDM biosurveillance system will empower growers with real-time weekly information of airborne inoculum levels to best utilize site-specific fungicides for CDM management while preventing fungicide resistance.
- Determine if a vacuum and a roto-rod spore trap can detect pathogen spores before any disease can be observed on crop leaves.
-Expected outcome #1: Results will help assess which trap type is best at capturing P. cubensis sporangia.
2. Determine which vehicle type (drone, rover, stationary) is most effective for pathogen spore sampling with vacuum and roto-rod spore traps.
-Expected outcome #2: Results will serve to address which vehicle-trap combination is better to use for a future biosurveillance system in large commercial fields.
3. Determine the occurrence of clade, Oxysterol binding protein inhibition (OSBPI), Carboxylic Acid Amide (CAA) and Quinone outside Inhibitor (QoI) fungicide resistance in spore trap samples to establish fungicide resistance patterns in the populations of the pathogen (P. cubensis).
-Expected Outcome #3: Results will serve to establish which products are not effective for CDM management.
Cooperators
Research
Field sites: Field experiments in years 1 and 2 will be established at the Central Crops Research Station in Clayton, NC. The field will be 8 rows of 200 ft each, covered in white plastic with a drip line in each row. The row spacing will be 5ft and the plant spacing will be 1ft.Rows will alternate between cucumber (Liszt) and squash (Butternut Waltham), for a total of 4 rows of cucumbers and 4 rows of squash. Irrigation will be every week via drip line. The rows will be harvested weekly to allow the cucurbits to produce more vines instead of fruit. Manual weeding will be performed weekly. The plots will be inoculated with natural infestation only. Disease incidence and severity will be recorded for every row weekly.
Trap and vehicle type experiments: Field sites will be sampled weekly from May (before CDM typically arrives to NC) until October. Roto-rod (2 rods) and vacuum traps (8 rods) will be equipped with small, greased plastic rods as the sampling unit to impact the pathogen spores.
Two trap types (roto-rod and vacuum)and three vehicles (post, rover, and drone) will be tested in different combinations. Roto-rod traps will be mounted in a post (stationary), hanging from a drone, and above a rover. Vacuum traps will be mounted on a lateral arm on a rover and hanging from a drone. Traps will be positioned directly above the plant canopy.
Trap-vehicle combinations will be deployed as follows. Four rotorod traps will be positioned on a cucumber and a squash row forming a square with an anemometer in the middle of the plot to monitor wind and other environmental variables. Each trap will sample airborne inoculum at 120 min, 60 min, and 30 min, with the fourth trap used to sample inoculum at the same time as when either the rover or drone traps are deployed to serve as a control.
The vacuum and roto-rod traps on the remote controlled rover, and the control stationary roto-rod trap, will be deployed at the same time. The rover will perform two sampling drives, 15 minutes each, one for a cucumber row, one for a squash row.
The vacuum and roto-rod traps hanging from an UAV (Unmanned aerial vehicle), and the control stationary roto-rod trap, will be deployed at different times and rows so that the drone turbulence does not affect sampling. The traps on the drone will be sampled one after the other in different rows, and the control stationary trap will be deployed at the same time as each of the drone traps but also on a different row. The UAV will perform one flight of 10 minutes covering three rows of the experimental field, leaving the fourth row for the control stationary roto-rod trap.
The rods for each weekly sampling event with all the trap-vehicle combinations will be collected in 2ml tubes once sampling is complete and stored in a 4C refrigerator for later processing in the lab. Rating for CDM disease incidence and severity will be done weekly for each row and reports to the CDMipmPIPE will be recorded.
Clade and fungicide resistance diagnostics: The rod processing will consist of three steps. First, a DNA Extraction using the NucleoSpin Plant II, Mini kit for DNA (Macherey Nagel). Second, a check for DNA concentration and quality in each one of the samples, using a spectrophotometer (NanoDrop®). The third step will be to perform four qPCR assays in the CFX Connect Real-Time PCR Detection System-BioRad to determine the following information in each sample: clade (Clade assay) and fungicide sensitivity to CAA, QoI and OSBPI (CAA, QoI and OSBPI assays).
Data analysis: Once all four qPCR assays (Clade, CAA, QoI and OSBPI assays) have been completed, the Cq values (amplification values generated by the CFX Connect Real-Time PCR Detection System-BioRad) from the assays will be used to determine which clade each sample belongs to and the fungicide sensitivity (resistant or sensitive) for each sample as previously described (D’Arcangelo et al., 2022; Rahman et al., 2021).
Clade and fungicide resistance genotypes detected for each trap-vehicle combination will be plotted by week. Weekly disease incidence and severity (quantitative), and CDMipmPIPE reports (qualitative) will also be plotted as previously described (Rahman et al., 2021). The plotted data will be used to determine if the vacuum and/or roto-rod traps were able to detect the pathogen before any visual symptoms were detected on cucumber or squash plants. We will also determine if our system was closer in date when detecting the pathogen in the field vs. visual symptom detection vs. CDMipmPIPE reports.
Formal statistical analyses will also be performed to determine if the vacuum trap had more or less pathogen detection events per week than the roto-rod trap at the different sampling times tested. Statistical analysis includes a latent class analysis (LCA), using the ground spore traps as a gold standard for comparison. In conjunction with the LCA, ROC (Receiving operating characteristic) curves will be generated to graphically represent the data. Similarly, we will test for significant differences in pathogen detection events per week for the vacuum and roto-rod traps mounted on the different vehicles tested.
Clade, QoI and CAA genotypes will be plotted and used for statistical analysis using Pearson’s correlation to determine if any category occurs more frequently in association to one another. Weather and wind data from the anemometer and local weather stations will be used to determine correlations between environmental variables and weekly pathogen detection events.
For the field sample collection, samples were collected for the first year of the project. A total of 242 samples were collected for the different types of traps used (rotorod, rover and drone). This sampling was done at the Central Crops Research Station in Clayton,NC. The field was 8 rows of 200 ft each and it was covered in white plastic with a drip line in each row. The row spacing was 5 ft apart. The seeds were planted 1 ft apart. We planted alternating rows between cucumber (Liszt) and squash (Butternut Waltham), for a total of 4 rows of cucumbers and 4 rows of squash. Irrigation was done every week via drip line. Once the cucurbits started producing fruit, the rows were harvested weekly to allow the cucurbits to produce more vines instead of fruit. Manual weeding was performed when necessary. The plots were inoculated with natural infestation only. Disease incidence and severity was recorded for every row weekly.
Two trap types (roto-rod and vacuum)and three vehicles (post, rover, and drone) were tested in different combinations. Roto-rod traps were mounted in a post (stationary). Vacuum traps will be mounted on a lateral arm on a rover and hanging from a drone. Traps were positioned directly above the plant canopy. Four rotorod traps were positioned on a cucumber and a squash row forming a square with an anemometer in the middle of the plot to monitor wind and other environmental variables. Each trap sampled airborne inoculum at 120 min, 60 min, and 30 min, with the fourth trap used to sample inoculum at the same time as when either the rover or drone traps were deployed to serve as a control. The vacuum and roto-rod traps on the remote controlled rover, and the control stationary roto-rod trap, were deployed at the same time. The rover performed two sampling drives, 15 minutes each, one for a cucumber row, one for a squash row.
The vacuum trap hanging from an UAV (Unmanned aerial vehicle), and the control stationary roto-rod trap, were deployed. The UAV performed one flight of approximately 10 minutes covering four rows of the experimental field.The rods for each weekly sampling event with all the trap-vehicle combinations were collected in 2ml tubes and stored in a -20C freezer for later processing in the lab.
For the sample processing, the total number of samples (242) was processed. A DNA extraction was performed followed by a sample quality check (Nanodrop). Once the DNA samples were available, a qPCR to detect the clade of the pathogen was done. Of the 242 samples, 110 detected P. cubensis in them. We had clade 1 only samples (24), clade 2 only samples (51) and mixed samples (35).
For the data analysis we have a new working collaboration with Dr. James Clothier, a statistician at North Carolina State University. Based on the data we have so far, our collaborator is creating a model for the preliminary data analysis. The model parameters were estimated in SAS’ PROC GLIMMIX.
For the preparation of the upcoming field season there were two main aspects. More reagents were ordered in preparation for the samples of the upcoming field season (pipette tips, primers, probes, DNA extraction kit). All the equipment was examined to make sure that the vehicles and traps are currently in working conditions. Field equipment with damages or in need of maintenance is being fixed by our collaborators in engineering (team of Lirong Xiang and Andrea Monteza). We have also located a grower cooperator for on-farm testing in year 2.
Educational & Outreach Activities
Participation Summary:
Research Presentations
Prieto Torres M. and Quesada-Ocampo L. M. (2025). Oxathiapiprolin fungicide resistance mutation biosurveillance in Pseudoperonospora cubensis using spore trapping in North Carolina. American Phytopathological Society, Southern Division and Caribbean Division Meeting 2025, Gainesville, Florida, March 2025.
Prieto Torres M. and Quesada-Ocampo L. M. (2024). Using biosurveillance for detection of Pseudoperonospora cubensis, causal agent of cucurbit downy mildew. Department of Entomology and Plant Pathology Graduate Symposium. Raleigh, NC, November 2024
Extension Presentations
Quesada-Ocampo L. M., Rosado-Rivera Y.I., and Prieto M. Cucurbit downy mildew management updates. 38th Annual Southeast Vegetable and Fruit Expo. Myrtle Beach, SC, December 2024.
Prieto Torres, M., Quesada-Ocampo L. M. Biosurveillance and disease management for cucurbit downy mildew (Pseudoperonospora cubensis). Pickle Packers International Annual Meeting. Chicago, IL, October 2024.
Project Outcomes
Our project will contribute to future sustainability. Preliminary results from the first year suggest that the novel mobile traps are catching spores from both clades. Additionally, the mobile traps have the potential to be tested in a large acreage setting. This is a big milestone for the bigger vision of the potential of this project. On the economic side, if the system we are working on developing could be used in a farm, a grower could save some fungicide applications if the disease is detected timely instead of applying sprays when not necessary.
Our awareness of sustainable agriculture increased since starting working on this project, especially when preparing and executing the field work. Making this work happen has a lot of challenges, but understanding that it has the potential to support sustainable agricultural practices in our state makes us more aware of its importance. Additionally, our knowledge increased because we are looking at a large acreage sustainable solution that can be used in real growers farms, not only on research plots, so we have to always be thinking about effective ways that this technology can work for our growers. This required us to gain a lot of knowledge in the underexplored are of mobile spore trapping.