Progress report for LS24-394
Project Information
During on-farm visits and one-on-one meetings with growers, crop consultants, and Extension agents in southern Florida, early blight, caused by the fungal pathogen Cercospora apii, emerged as the most important foliar disease affecting celery production (Xavier 2022, personal communication). Florida plays a crucial role as a major producer of vegetables for the fresh market, including celery, supplying the nationwide demand during the winter season. However, the detrimental effects of this disease, characterized by stunted plant growth and damaged leaves, pose a significant threat to the marketability of the final product. To mitigate these yield losses, celery growers rely on weekly fungicide applications as a preventive measure, primarily due to the absence of alternative curative or preventive measures. Therefore, there exists a critical need to identify and establish sustainable management strategies for C. apii. Failure to address the need for sustainable management of early blight on celery production will result in significant yield losses, reduced marketability, increased chemical fungicide use, environmental and health risks, economic strain on growers, and potential dissatisfaction among consumers, posing threats to both the celery industry and the environment. Our long-term goal is to develop sustainable and future-proof solutions for controlling early blight in both conventional and organic celery production systems. Our overarching goal is to create both an early detection system and biocontrol products against early blight on celery. Our central hypothesis is that it is feasible to develop and implement more efficient, environmentally sustainable, and socially beneficial management strategies for early blight in celery production, resulting in economic advantages for growers. We are well-positioned to lead this project based on our 56-year partnership with celery stakeholders in Florida, our access to cutting-edge technologies, and our interdisciplinary team of experts. Moreover, our dedication to community engagement ensures we understand local concerns and needs, building trust vital for project success. We plan to attain the overall objective by pursuing the following two specific aims: 1) Develop a UAV-assisted disease monitoring system to visualize and track disease onset and progression in celery. Our working hypothesis is that current machine/deep-learning algorithms have the capability to accurately identify celery plants infected with C. apii. Combining these algorithms with previously established C. apii forecasting models will yield an effective decision-making system for growers. 2) Identify, select, and evaluate effective biological control agents against C. apii for the management of early blight in celery. Our working hypothesis is that the Everglades Agricultural Area harbors a reservoir of powerful microorganisms with the capacity to effectively control C. apii. Economic analysis will guide the timing and optimization of the deployment of controlling measures, ensuring a cost-effective approach for growers. Upon the successful completion of this project, it is our expectation that we will have established novel, economically advantageous, and safe strategies for early detection of early blight, advancing sustainable agriculture. This project offers achievable and practical solutions for celery growers that, if adopted, can enhance disease management practices, leading to improved production outcomes and the overall ecosystem health.
Our central hypothesis revolves around the notion that more effective and sustainable management of Cercospora early blight in celery is not only attainable but also economically advantageous. Below, we delineate four specific objectives, along with their corresponding working hypotheses, research design, and anticipated outcomes.
Objective 1: Develop a UAV-assisted disease monitoring system to visualize and track disease onset and progression in celery. (Drs. Xavier, Ferreira, and Wang’s supervision).
Working hypothesis: Celery plants undergoing pre-symptomatic stages of early blight have a distinctive spectral profile. Current machine/deep-learning algorithms have the capability to accurately identify celery plants infected with C. apii. Combining these algorithms with previously established C. apii forecasting models will yield an effective decision-making system for growers.
Research design: Our experiment will focus on the early detection of Cercospora early blight of celery, specifically at pre-symptomatic stages. To achieve this, we will employ an innovative disease monitoring system using AI-powered Unmanned Aerial Vehicles (UAVs) equipped with multispectral cameras Expected outcome: Substantial reductions in fungicide usage in both organic and conventional cultivation systems, coupled with enhanced control over Cercospora early blight.
Objective 2: Identify, select, and evaluate effective biological control agents against C. apii for the management of early blight in celery. (Dr. Ferreira and Xavier’s supervision).
Working hypothesis: The EAA harbors a reservoir of powerful microorganisms with the capacity to effectively control C. apii.
Research design: We will employ a comprehensive research approach that spans laboratory, greenhouse, and on-farm field trials. This multifaceted strategy will enable us to identify, assess, and validate potential biological control agents effective against C. apii.
Expected outcome: A biopesticide product effective at commercial celery production, and consequently reduction of contamination by reducing chemical fungicide use.
Objective 3: Develop an economic analysis for organic and conventional growers to manage Cercospora early blight based on standard and new management practices. (Dr. Guan’s supervision)
Working hypothesis: The proposed solutions proposed are cost-effective, yielding a positive economic impact for growers who adopt these technologies.
Research design: Economic analysis will be performed for the five field trials to be conducted at this proposed project, comparing standard management practices used by growers and the new ones developed in this proposal. The goal is to provide growers with a cost-benefit analysis to evaluate the profitability of the proposed management practices.
Expected outcome: Empowerment of our approach, facilitating its adoption among growers, and attracting new growers who recognize the economic benefits of implementing these practices.
Objective 4: Disseminate research findings and educate growers about the benefits of biocontrol and UAV technology via events and written publications. (MS Meszaros and Dr. Xavier’s supervision).
Working hypothesis: Individuals and institutions already engaged in the celery business will be interested in improving their disease management practices, particularly when they discern the potential economic gains.
Expected outcome: Increased awareness of improved C. apii management practices as well as adoption of the proposed solutions among celery growers, enabling them, workers, and society at large to seize of potential benefits provided by each solution.
Cooperators
- - Producer
- - Producer
- - Producer
- - Producer
Research
Objective 1:
1.1: Get appropriate training for all personnel involved in this project in artificial intelligence (AI) use. And to develop an initial AI model for detection of Cercospora early blight.
1.2: Test the preliminary model for early disease detection using drone technology and efficacy field trail at the EREC. (Year 1&2)
This trial was artificially inoculated. Design: randomized complete block design (n=4) with the treatment groups: (1) non-inoculated and non-treated control; (2) inoculated and non-treated control; (3) non-inoculated and conventional grower-standard; (4) inoculated and conventional grower-standard; (5) conventional fungicide program 1; (6) conventional fungicide program 2; (7) organic grower-standard, (8) organic biopesticide program 1, (9) organic biopesticide program 2; and (10) organic biopesticide program 3. Observation: This trial was suggestion of our growers. During a meeting to discuss this project, they expressed a strong need to test the efficacy of the products they currently use. We agreed that it would be beneficial to conduct this test while we can evaluate the drone data for early detection in comparison to visual evaluation.
Grower participation: Duda’s crew provided the transplants, brought their machinery to plant it at the EREC. We performed the fungicide applications and evaluations (Objective 4).
Aerial imaging and data collection: We will utilize consumer-grade drones equipped with high-resolution multispectral cameras for aerial imaging. These drones will be programmed to fly over celery fields at regular intervals to capture multispectral images. Multispectral images were captured using a hand held camera from non-inoculated plants to establish a baseline for pre-symptomatic disease signatures.
Ground truth validation: the focus was to confirm the presence of pre-symptomatic infections in naturally occurring cases. A postdoc inspected the celery crops weekly, documented disease presence as symptoms become visible, and provided validation for the AI-driven disease detection system.
1.3: Next: Multispectral image processing and disease identification: The collected multispectral images will undergo advanced image recognition algorithms powered by Artificial Intelligence (AI), such as AlexNetOWTBn, VGG, and EfficientNetV2-B4. These algorithms will be specifically trained to identify subtle spectral cues and anomalies associated with pre-symptomatic stages of Cercospora early blight.
Statistical analysis: Our approach to AI model development will involve a meticulously curated training dataset, comprising multispectral images acquired from artificially inoculated celery plants intentionally exposed to Cercospora apii to induce symptoms. The testing dataset will feature multispectral images collected from naturally occurring symptomatic plants in the field. In evaluating the model's performance, we will employ a suite of essential metrics. Sensitivity will gauge the model's accuracy in identifying true pre-symptomatic infections (true positives), while specificity will measure its ability to correctly identify cases with no infection (true negatives). Overall accuracy will provide a summary of the model's correctness in identifying both pre-symptomatic and non-symptomatic cases. For visual insight into model performance, we will utilize a confusion matrix, revealing true positives, true negatives, false positives, and false negatives, pinpointing areas of success and improvement needs. The ROC curve will assess the model's capacity to distinguish pre-symptomatic infections from non-infected cases, with AUC-ROC quantifying its performance. In addition, the precision-recall curve will strike a balance between precision (positive predictive value) and recall (sensitivity) at various thresholds, particularly in identifying pre-symptomatic infections while minimizing false positives. To enhance model robustness and mitigate overfitting, we will implement k-fold cross-validation. The dataset will be divided into subsets (folds), with the model trained and tested iteratively to assess its generalizability. Hypothesis testing will be conducted to assess the statistical significance of differences in performance metrics between the training data (artificially inoculated plants) and testing data (naturally occurring infections). The outcomes will inform ongoing model refinement and optimization.
1.4: Retrieve and analyze weather data from FAWN: local weather data from the EREC station in Belle Glade will be obtained from the FAWN website (http://fawn.ifas.ufl.edu/). By analyzing multispectral images captured by the UAVs and cross-referencing them with concurrent weather data, the system will offer recommendations tailored to the specific conditions of each celery field. Decision-making system based on imaging data and weather-based forecasting. When favorable weather conditions for disease development are identified, the system will alert growers to take proactive measures, such as targeted fungicide applications or the deployment of biological control agents. Thus, in addition to the development and validation of our AI-powered UAV-assisted disease monitoring system, our project aims to implement a sophisticated decision-making system that integrates multispectral imaging data with the Berger model for weather-based forecasting of early blight (Raid et al. 2008) when weather data is available.
1.5: Development of user interface: To facilitate the seamless integration of multispectral image processing and weather data analysis, a user-friendly web-based platform will be developed. This platform will be hosted on dedicated servers at the University of Florida (UF) to ensure the necessary computational resources and data storage capacity. This interface will be equipped with features that allow users to easily upload multispectral images collected by UAVs and receive real-time analysis results, including disease risk assessments based on weather data.
1.6: Field trial to validate AI-powered decision-making system at Duda’s Conventional Farm. This will be under natural inoculation. (Year 3). Treatment for include: (i) non-inoculated and non-treated control; (ii) treated with biological agent 1; (iii) treated with biological agent 2, (iv) treated with the standard-grower program, (v) fungicide program 1 (from 1.2), (vi) fungicide program 2 (from 1.2), spray recommendation (from 1.2), (vii) fungicide program 3 (from 1.2), spray recommendation (from 1.2). A drone equipped with a multispectral camera will collect imagery data as described above.
Grower participation: Duda’s crew will provide the land, transplants, machinery to plant. We will perform fungicide applications and evaluations together with the grower. Their decisions will be compared to those obtained by our AI-powered system. In Case of a rainfall event in the region (e.g. hurricane), second plan is to conduct this trial at RFi Rothert Farm at Okeechobee, on sandy soils. Jake will help with planning, providing feedback on our trails for improvement. He is willing to incorporate our recommendations on new management strategies.
Data security and privacy: Strict data security measures will be in place to protect sensitive information collected during the experiment. Consent and privacy considerations will be addressed for all participants involved in the project. Grower participation: All the supporting growers will be trained on this.
Objective 2:
2.1: We have conducted soil and tissue sampling of biocontrol agents and Cercospora isolates in South Florida. Biocontrol agents were collected in South Florida, from (i) conventional farm, (ii) one organic farm, (iii) one conservation areas, (iv) two areas within the EREC, encompassing pathogen-suppressive soils, disease-free plants, known disease-affected areas, and uncultivated regions. The same farms were visited and surveyed during celery growing season to obtain Cercospora isolates. Isolates are preserved to inoculate field trials as well as greenhouse and in vitro tests. All the microorganisms of interest were preserved in either glycerol or filter paper and stored at -80 °C.
Grower participation: Samples were collected at Dudas and C&B. When this project started the celery growing season at RFi Rothert Farm was already finished.
2.2: Assessments of direct antibiosis in vitro has being completed: Isolation was performed in 1/4 PDA Potato Dextrose Agar (PDA) and Nutrient Agar (NA) media. We selected 48 fungi and 122 bacteria on PDA and NA, respectively. We assessed their ability to inhibit C. apii growth using the formula:
RI = (C – T)/(C – D) × 100
where RI is the radial inhibition (%), C is the mean value of the colony diameter of the control, T is the colony diameter of the treatment, and D is the plug diameter. This experiment included 5 and 8 replicates for fungi and bacteria, respectively and performed twice.
2.3: Conducted molecular identification of selected bioagents (17 fungi and 10 bacteria):
Ten from the in vitro screening will advance to the greenhouse screening. First, these isolates will undergo molecular identification through the sequencing conserved regions, including 16S (bacteria), and ITS, TEF1 and LSU (fungi). Total DNA extraction was performed using the Synergy 2.0 (OPS Diagnostics). PCR amplified fragments were sequenced using the Sanger method. Sequencing data were processed in Geneious Prime and the curated sequences were compared to the NR/NT database on GenBank.
Next: For phylogenetic analysis, both Bayesian inference and Maximum likelihood methods will be utilized, with Mr.Bayes and RaxML software, respectively. Any isolates identified as species with known clinical or detrimental effects will be replaced.
2.4: Greenhouse screening in planta: (On going) Celery plants were inoculated with C.apii isolate KX 493 (2.5x105 UFC per mL). After inoculation plants were sprayed with a separately suspension of 2.5x105 UFC/ml (fungi) or 108 and 109 (bacteria) UFC/ml of the biocontrol agents. Two sets of control: (i) untreated and non-inoculated, and (ii) untreated and inoculated. Disease levels will be regularly assessed until control plants display symptoms in 50% of foliar area..
Grower participation: Duda’s Farm provided the transplants to the GH trial. We performed biocontrol applications, inoculations, and will evaluate.
2.5: NEXT: Microscopy and histo-biochemical analyses: We will investigate the biocontrol mechanisms (hyperparasitism, antibiosis, competition, and/or plant growth promotion), which will help us determine the optimal application method for the selected biocontrol agents (BCAs). To determine the effects of the BCAs on C. apii, we will conduct an in vitro experiment featuring three treatment groups: C. apii x BCA1, C. apii x BCA2, C. apii, BCA1, and BCA2. These organisms/treatment groups will be cultivated in solid media plates and incubated under controlled conditions at 25 °C with a photoperiod of 16 h for 7 days. The experiment will include four replicates for each treatment. Microscopy observations will be made on these plates to assess any visible effects, such as hyperparasitism. After microscopic analyses, C. apii mycelia will be harvested from plates growing with and without (control) each biocontrol agent and immediately frozen in liquid nitrogen (N2). Likewise, cells from the biocontrol agents growing with and without C. apii will be collected and immediately frozen in N2. The collected tissues/cells will be subjected to mass spectrometry-based proteomics with trypsin digestion. Peptide spectral matches will be identified through searches against a proteomic database. Further bioinformatics analyses will be performed.
2.6: NEXT:Formulation of biocontrol product: We will explore the use of diverse substrates, such as sorghum grains and by-products from the sugarcane and rice industries in the EAA. Examples of substrates that can be tested are sugarcane bagasse, molasses, filter press mud, rice straw, and husks. Substrates will be autoclaved and inoculated with a spore suspension of 1x106 spores/ml of each BCA and incubated at room temperature for 10 days. The experiment will be performed in triplicate. The spore density on different substrates will be assessed by mixing 1 g/ml of colonized substrate with 9 ml of autoclaved distilled water and quantifying spores using a Neubauer chamber. The best substrate for each BCA will undergo further experiments to optimize its moisture content (50, 60, and 65 %) and incubation time (5, 10, and 15 days). Once the optimal composition for each BCA formulation is identified, we will carry out greenhouse experiments to determine the most effective application rates.
Grower participation: We are going to invite growers from the Everglades to participate by donating the substrates to produce our formulation.
2.7: NEXT:On-farm efficacy trials: The efficacy of two derived biocontrol products will be evaluated in on-farm field trials conducted at organic farm sites in years 2 and 3, at Duda and C&B Farms, respectively. These trials will involve natural infections to mimic real-world conditions. Disease severity assessments will be conducted bi-weekly. The treatment groups for these trials will include (i) non-inoculated and non-treated control; (ii) treated with biological agent 1 (identified in experiment 3), sprayed based on the grower-calendar spray program; (iii) treated with biological agent 2 (identified in experiment 3), sprayed based on the grower-calendar spray program; (iv) treated with biological agent 1 (identified in experiment 3), sprayed based on our prediction system, (v) treated with biological agent 2 (identified in experiment 3), sprayed based on our prediction system, (vi) grower standard program. Drone and statistical methods are described above.
Grower participation: Duda’s and C&B crew (which one in their farm) will provide the land, transplants, machinery to plant. We will perform fungicide applications and evaluations together with the grower. They will work closely with us to maintain the trial and make decisions regarding disease management. Their decisions will be compared to those obtained by our AI-powered system. The field trial results will guide the refinement of the biocontrol product formulation based on their performance in real-world conditions. This will be discussed very well with the growers on the daily basis.
Objective 3
Trial 1.2 will be performed twice in years 1 (This has already been performed, and the harvest yield data has been collected. The economic analysis is currently ongoing.) and 2 at the EREC station. It had 10 treatments, including the non-treated; and two grower standards that will be used to compare with the treatments that will be applied such as the fungicide programs. Based on the economic analysis the growers will be able to decide if applying a model for early disease detection using drone technology will be cost-effective.
Trial 1.4 Field trial to validate AI-powered decision-making system at Duda’s Conventional Farm: Conduct efficacy trials to validate the UAV-assisted disease prediction model at a conventional on-farm grower site. It will have 7 treatments, including the non-treated; a grower-standard that will be used to compare with the treatments, based on the economic analysis. Then growers will be able to decide if applying a model for early disease detection using drone technology will be cost-effective.
Trial 2.7 On-farm efficacy trials. To test if it is cost-effective to produce and use the newly developed two biocontrol products, we will perform the economic analysis of the biological efficacy trials conducted at Duda and C&B Farms. We are also going to take into consideration the cost of producing these biocontrol agents.
Grower participation: This part will be presented to the growers during the advisory committees, field days, workshops and lettuce advisory committees. They will give us feedback for improvements not only based on the results from the field but also based on the economic analysis.
Objective 4.
4.1: To ensure grower engagement and participation in this project, we initially planned to establish assembly and advisory grower committees to meet once per season (Years 1, 2, and 3: 2024, 2025, and 2026). These committees will have a roundtable discussion each season between August and December at EREC. However, due to scheduling conflicts, it was not possible to find a time when all growers were available to meet. As a result, we conducted one-on-one meetings to gather their feedback for Year 1.
These committees will play a pivotal role in shaping the content, planning, and execution of field days, workshops, and other educational events. Their insights and feedback will guide us in tailoring our outreach efforts to address the specific needs and concerns of celery growers in the region. This client-centered approach ensures that our educational programs are aligned with the industry's priorities.
Before drafting the pre-proposal, we met with the celery growers and incorporated their input into this project. Moving forward, our goal is to maintain an ongoing feedback loop with them, ensuring their continued involvement and keeping them informed about our research findings through various venues listed here.
4.2: Research Findings Dissemination: We presented our results at local (at two Lettuce Advisory Committee), and regional (one Southern Division Plant Pathology Meeting), allowing us to reach a broad audience of agricultural stakeholders and researchers.
NEXT: Additionally, we will produce Extension publications (University of Florida Extension publication-EDIS) that distill our research outcomes into accessible and actionable information for growers. These publications will serve as valuable resources for growers seeking to implement biocontrol and UAV technology in their celery cultivation practices. In addition to Extension publications, we will contribute to the scientific community by publishing peer-reviewed articles that detail our research methodologies, results, and implications. These articles will ensure that our findings are rigorously examined and contribute to the body of knowledge in agricultural science.
4.3: Field days: We organized a field days specifically tailored for celery growers and workers. There will be two field days at the EREC in Belle Glade in years 1 (it happened on Feb of 2025, attendance: 17 people among crop consultants, Extension agents, farm workers, growers, farm managers, researchers, students and others), another is planned for next season. These events serve as crucial platforms for hands-on engagement and assessment of treatment efficacy. Overall, growers and workers will be actively involved in the field day activities, including evaluating the performance of different treatments. These events have a particular focus on providing the four growers supporting this project the opportunity to evaluate the disease severity on-site and to rank our plots with their own eyes. Thus, they can give feedback for improvement. Their participation will also encompass training sessions aimed at enhancing their skills in early disease detection using our AI-powered model and optimizing the application methods for the derived biocontrol product. This active involvement will empower growers and workers with practical knowledge and equip them to implement these innovative technologies effectively.
Demonstrations at South Florida Fair (Jan 2025): An interactive display was set up at the South Florida Fair featuring sealed plates showcasing biocontrol agents and C. apii samples from the Everglades Agricultural Area. The display also included both symptomatic and healthy plants, along with the protective equipment we use when spraying the trial, to demonstrate proper chemical safety protocols. The South Florida Fair is an annual event that attracts over 500,000 people.
4.4. Workshop: Our research findings and knowledge will be transferred to the growers and workers during a local workshop (Year 3). This workshop will provide a structured environment for in-depth learning and knowledge transfer. Topics covered will include the practical application of biocontrol methods, the utilization of UAV technology for disease management. The workshop will be conducted with the active participation of growers and workers, fostering a collaborative learning environment.
Grower participation: Objective 4, the grower participation is listed above for each item.
1.2: Testing the Preliminary AI Model with Drone Technology
A field trial was conducted to evaluate the preliminary AI model for early disease detection using drone technology at the Everglades Research and Education Center (EREC). The trial was designed as a randomized complete block design (n=4) with 10 treatment groups. The treatment groups included various control, fungicide, and biopesticide programs, as well as grower-standard treatments. However we just finished this field trial last week and data analysis is still pending.
Objective 2: Biocontrol Agent Development and Testing
2.1: Biocontrol Agent and Cercospora Isolate Sampling
Soil and tissue sampling for biocontrol agents and C. apii isolates was successfully completed across various locations in South Florida, including conventional and organic farms, conservation areas, and pathogen-suppressive soils. The isolates have been preserved. And even used to inoculate greenhouse and field trial for year 1 of this project.
2.2: In Vitro Antibiosis Assessments
In vitro testing of biocontrol agents showed promising results in inhibiting the growth of C. apii. The radial inhibition (RI) values for fungi and bacteria were calculated, and 17 fungi (Figure 1 ) and 12 bacteria (Figure 2 ) biocontrol agents showed promising antagonistic activity against the pathogen. A summary of inhibition is shown in Figure 3. These results suggest that certain biocontrol agents could be effective for controlling C. apii in the field.
2.3: Molecular Identification of Biocontrol Agents
Molecular identification of the selected biocontrol agents is ongoing. DNA sequencing of conserved regions, including 16S for bacteria and ITS, TEF1, and LSU for fungi, has been performed. This process will allow for accurate identification of species and ensure that any harmful organisms are excluded from further testing. The top 10 bacteria biocontrol agents were identified as Bacillus spp. (n=3), Pseudomonas spp. (n=4), Achromobacter xylosoxidans (n=1), Pantoea sp. (n=1), Chryseobacterium sp. (n=1.); and the top 17 fungi as Mucor spp. (n=2), F. incarnatum-equiseti (n=6), Neopestalatiopsis spp. (n=6), Nigrospora sp. (n=1), Epicoccum sp. (n=1), Aspergillus sp. (n=1).
2.4: Greenhouse Screening of Biocontrol Agents
Greenhouse trials are in progress to assess the effectiveness of biocontrol agents in controlling C. apii on celery plants. The results will inform the selection of the most promising biocontrol agents for field application.
Objective 3: Economic Analysis of Disease Detection and Biocontrol
3.1: Harvest Yield and Economic Analysis
The economic analysis for the trials conducted in Year 1 and Year 2 is currently ongoing. The data from these trials, including harvest yield and disease severity, will be used to assess the cost-effectiveness of the AI-powered disease detection system and the biocontrol products. Growers will be able to evaluate whether these technologies justify the investment based on improved disease management and yield.
Objective 4: Grower Engagement and Outreach
4.1: Grower Committees and Advisory Panels
Despite scheduling challenges, we were able to engage growers through one-on-one meetings to gather feedback for Year 1. These meetings were valuable in refining the project and ensuring that our research aligns with growers' needs, this included adding more organic products/ treatments. Moving forward, we will continue to engage growers through advisory committees, field days, and workshops.
4.2: Research Findings Dissemination
Our findings were disseminated through local and regional presentations, including the two Lettuce Advisory Committee and the one Southern Division Plant Pathology Meeting.
4.3: Field Days and Demonstrations
Field days have been successfully organized to engage growers in hands-on learning. The first field day at EREC in February 2025 was attended by 17 people, including crop consultants, Extension agents, and growers. These events provide valuable opportunities for growers to evaluate treatment efficacy and provide feedback on the project.
Concluding Remarks
The project has made significant progress in developing AI-powered disease detection and biocontrol solutions for celery growers. The results to date suggest that both technologies have the potential to improve disease management and yield. However, further refinement and validation in real-world conditions are needed to optimize these tools for widespread adoption.
Education
The educational approach in this project incorporated various methods to engage and educate growers, stakeholders, and the broader public. Key elements of the approach included:
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Grower Engagement: Growers actively participated in all stages of the project, from providing land and transplants to engaging in field trials and advisory committees. This collaboration ensured that the project aligned with grower needs, offering them valuable insights into the effectiveness of the technologies being tested.
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Workshops and Field Days: These events provided growers with hands-on experience and direct exposure to the research during the field day.
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Interactive Demonstrations at the South Florida Fair (Jan 2025): An interactive display at the South Florida Fair showcased sealed plates with biocontrol agents and C. apii samples from the Everglades Agricultural Area. The display featured both symptomatic and healthy plants, along with protective equipment used during trial spraying, to educate the public on chemical safety protocols. This event provided an opportunity to reach a broader audience and increase awareness about sustainable farming practices and innovative agricultural technologies.
Educational & Outreach Activities
Participation Summary:
Target Audience:
- Celery growers: The primary beneficiaries of this project are celery growers, both conventional and organic, in Southern Florida. These growers will directly benefit from the disease management strategies and early detection technologies developed during this project. By reducing fungicide use and improving disease control, the project aims to enhance crop yields, product quality, and profitability.
- Farm workers: Farm workers involved in celery production are another crucial target audience. They will benefit from a safer working environment due to reduced exposure to chemical pesticides. Additionally, through project outreach and education efforts, they will gain knowledge and skills related to the use of biocontrol agents and early disease detection technologies.
- Young individuals and students: The project will actively engage with students and young individuals in Florida. By participating in workshops, field days, and educational programs, these individuals will have the opportunity to learn about innovative disease management practices, sustainable agriculture, and the use of cutting-edge technologies in farming. This engagement aims to empower the next generation of agricultural leaders and encourage them to adopt sustainable practices.
- Extension agents: Extension agents play a vital role in disseminating research findings to growers. They will be an important target audience for this project. By providing them with valuable information on disease management and early detection technologies, we aim to equip them with the tools needed to support local growers effectively.
- Local agricultural organizations: Organizations such as the Lettuce Advisory Committee, will be engaged in project activities. These organizations often serve as intermediaries between researchers and growers. Their involvement will help ensure that project findings are effectively communicated to a wider audience of growers.
- Crop advisors/consultants: these professionals are essential stakeholders in the agricultural supply chain. By demonstrating the benefits of biocontrol agents and early disease detection technologies, the project aims to encourage their adoption and integration into agricultural practices. They will also benefit from a safer working environment due to reduced exposure to chemical pesticides.
Education and Outreach Components:
- Grower committees and advisory panels: Advisory grower committees will be scheduled once per season to ensure that our celery growers have participation in all aspects of this project (Years 1, 2, and 3).
- Field days: Field days will be organized to engage growers, farm workers, and agricultural students. These events will provide the four growers supporting this project the opportunity to evaluate the disease severity and rank our plots on their own. Thus, they can give feedback for improvement.
- Workshop: The project will host a workshop targeting celery growers, farm workers, and young individuals interested in agriculture. This event will provide hands-on experience with disease management practices, biocontrol agents, and the use of UAV technology for early detection. The workshop will be conducted at the EREC station in Belle Glade.
- Educational materials: The project will produce educational materials, including fact sheets, EDIS publications, and news posts at the Commercial Vegetable Production website of the University of Florida. These materials will explain disease management practices, the use of biocontrol agents, and the advantages of early disease detection. They will be distributed at workshops, field days, and other outreach events. (Years 1, 2 and 3).
- Written publication: Research findings will be documented in peer-reviewed scientific journals and extension publications. These publications will be accessible to a wide audience, including growers, extension agents, and the academic community.
- Local and national meetings: Project results will be presented at local agricultural meetings, such as the Lettuce Advisory Meeting; regional, such as the Southern Division Plant Pathology Meeting; and national conferences, such as the Plant Health Conference. These presentations will reach a broad audience of agricultural professionals and researchers.
Options for possible implementation and adoption:
- Open access to model: To ensure widespread accessibility and adoption of our disease prediction model, we are committed to providing an open-access solution. We will develop a user-friendly web application hosted by the University of Florida, where growers, agricultural professionals, and researchers can easily access and utilize the model. This web-based platform will allow users to input relevant data, such as multispectral images collected from their celery fields, and receive real-time disease predictions. By making the model openly available through this web application, we aim to democratize the benefits of our research and empower a wide range of stakeholders in the celery farming community to make informed decisions about disease management. This open-access approach aligns with our commitment to fostering collaboration and knowledge-sharing within the industry. Moreover, as part of our commitment to supporting the successful adoption of our technology, we will provide guidance and consultation concerning the acquisition of the necessary equipment to implement the model effectively. We aim to assist growers and professionals in making informed choices that align with the requirements of our model, such as drone and camera systems.
- Creation of start-up company to produce biocontrol products: To ensure efficient and widespread distribution of our biocontrol product, we are taking the innovative step of creating a start-up company. This endeavor will be in collaboration with UF INNOVATE, an innovation hub at the University of Florida. The establishment of a start-up company represents a strategic approach to not only manufacture and distribute the biocontrol product but also to license the underlying technology. The creation of this company will play a crucial role in commercializing our research outcomes and making the biocontrol product accessible to a broader agricultural audience. By partnering with UF INNOVATE, we will have access to a wealth of resources, expertise, and support, allowing us to navigate the complexities of technology transfer and business development. This initiative is aligned with our mission to not only advance the science behind disease management in celery farming but also to facilitate practical applications of our innovations.
- On-farm multiplication of inoculum: A critical component of our implementation and adoption strategy involves making the biocontrol product readily available and accessible to celery growers. To achieve this, we will develop a protocol for on-farm multiplication of the biocontrol inoculum. This approach allows growers to produce their biocontrol agents, reducing dependence on external sources and ensuring a sustainable supply for disease management. Our plan includes providing growers with the necessary training and resources to carry out on-farm multiplication effectively. This training will cover the principles of inoculum production, maintenance of inoculum cultures, and application methods. By empowering growers with the knowledge and skills needed to multiply the biocontrol agents, we promote self-sufficiency and cost-effectiveness in disease management.
- Worker training: By providing training and education to farm workers, the project seeks to ensure that the knowledge and skills needed for effective disease management are transferred to those responsible for daily field operations.
Project Outcomes
This project will contribute to the future sustainability of celery farming by addressing key challenges through innovative technologies and practices. It offers a range of economic, environmental, and social benefits for farmers:
Economic Benefits:
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Increased Efficiency: The AI-powered early disease detection system and biocontrol applications will help farmers identify and manage diseases more effectively, reducing the need for broad-spectrum fungicide applications. This could lead to significant cost savings in crop protection.
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Improved Crop Yields: By detecting diseases at an early stage, the project helps minimize crop damage and loss, leading to better yields and increased profitability for farmers.
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Cost-Effective Disease Management: The integration of weather-based forecasting and AI-driven recommendations allows for more precise, timely interventions, reducing unnecessary treatments and optimizing resource use. This helps lower overall input costs while maintaining high crop quality.
Environmental Benefits:
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Reduced Chemical Usage: The project promotes the use of biocontrol agents and targeted fungicide applications, which reduces reliance on chemical pesticides. This shift supports more sustainable farming practices and helps protect local ecosystems and biodiversity.
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Sustainable Pest Management: By focusing on biocontrol agents, the project encourages the adoption of natural, eco-friendly pest control methods, reducing the environmental impact associated with chemical pesticides.
Social Benefits:
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Knowledge Transfer and Capacity Building: Through workshops, field days, and extension publications, the project facilitates knowledge exchange and provides farmers with the tools and expertise they need to adopt sustainable practices. This fosters a more informed and resilient farming community.
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Increased Farmer Participation: Grower engagement in the project ensures that the developed technologies are practical and relevant to their needs. It promotes a sense of ownership and collaboration, empowering farmers to take an active role in shaping the future of their industry.
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Public Awareness: The project's outreach efforts, including the interactive display at the South Florida Fair, help raise public awareness about sustainable farming practices and the importance of innovative agricultural technologies. This, in turn, strengthens the social license to operate for farmers and promotes broader acceptance of sustainable practices.