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Gulf Coast Research and Education Center

Gulf Coast Research and Education Center


The cutting-edge institute aims to transform Tampa Bay into a hub for agricultural technology with a focus on  tackling rising production and labor costs.

The center proposes a shift from labor-intensive to technology-intensive agriculture by utilizing recent advancements in AI and robotics

Smart robotics can automate tasks such as:

  • Plant breeding
    • Quantitative analysis of complex data
    • Machine vision for enhanced evaluation of phenological traits 
  • Crop Production:
    • Automation of labor-intensive tasks
    • Farm data acquisition, transfer, and analysis
  • Pest Management:
    • Real-time pest detection & identification
    • Targeted pest management

- offering sustainable solutions to industry challenges.

The center, a nexus for statewide AI initiatives, will lead in designing, evaluating, and demonstrating novel AI-based technologies.

Anticipated benefits include: 

  • Direct industry support
  • New job positions
  • Resources for ag-tech start-up
  • Training programs

The facility, with 40,000 ft² of cutting-edge space, is estimated to cost $40 million.

Join us in shaping the future of Florida's agriculture—a future powered by innovation, sustainability, and economic growth. The Center for Applied Artificial Intelligence is pioneering a technological revolution for the agricultural industry.


AI Faculty Members

Professor of Plant Pathology

Dr. Natalia Peres conducts basic and applied research on important diseases affecting strawberry production in Florida. The goal of her program is to develop a better understanding of the etiology of the diseases and the environmental factors affecting their development, and to provide more effective disease control recommendations. She also works closely with the strawberry and the ornamental breeders on developing cultivars with some level of disease resistance and oversees the Plant Disease Diagnostic Clinic.

Assistant Professor of Ag Engineering

Dr. Wang adopts deep learning models to enhance the accuracy of complex plant trait estimation that ultimately offer breeders enormous support in selection. His research focuses on building automated proximal and remote sensing systems for field-based plant phenotyping, development novel data analysis and image processing pipelines for plant trait extraction and supporting cutting-edge machine learning methods for complex trait detection and yield prediction.

Assistant Professor of Ag Engineering

Dr. Choi is an expert in precision agriculture, focusing on the development of autonomous systems that integrate AI and mechatronics. Currently, her interest in virtual reality is integrated into her research projects, using digital twin technology for simulations. This approach is specifically aimed at refining AI and mechatronics systems in strawberry cultivation, with the goal of reducing development costs and time

Professor of Geomatics

Dr. Abd-Elrahman’s research focuses on utilizing remote sensing techniques to provide information needed in natural resources management/monitoring and precision agriculture applications. The research program involves multispectral and hyperspectral image classification, lidar data processing, and geospatial analysis.

Assistant Professor of Entomology

Dr. Lahiri is working on collaborative projects to utilize AI in the field of pest monitoring and augmentative biological control techniques. Specifically, efforts are targeted towards relying on AI to recognize feeding damage in plants caused by chilli thrips and spider mite pests in strawberry fields. Additional research work encompasses the development of AI to deploy augmentative biological control agents in response to pest infestation. 

Associate Professor of Horticulture

Dr. Lee's research program is focused on identifying genes and DNA sequence variants that control flavor, fruit quality, and disease resistance in octoploid strawberry. Big multi-omics data sets and comprehensive studies have been implemented to identify potential candidate genes and functional mechanisms for improving fruit flavor and disease resistance to multiple pathogens. Artificial intelligence (AI)-based systems biology approaches in multi-omics data analysis of strawberry will be the most effective way to utilize ‘big’-sized complex data and facilitate the integration of multi breeding traits for new cultivar development. 

Professor of Horticulture

Dr. Whitaker directs the UF/IFAS strawberry breeding program at GREC. He and his team develop flavorful and disease resistant varieties that are widely used in Florida and around the world. Dr. Whitaker uses AI primarily for phenomics, collaborating with Dr. Kevin Wang and Dr. Amr Abd-Elrahman to capture plant traits with cameras mounted on drones and ground vehicles and to extract plant and fruit features from those images in an automated workflow. That trait information is then used to guide breeding decisions.