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AI in Agriculture: Innovation and Discovery to Equitably meet Producer Needs and Perceptions

2023 AI Conference • April 17-19, 2023 • Marriott Orlando Airport Lakeside • Orlando, FL

AI in Agriculture: Innovation and Discovery to Equitably meet Producer Needs and Perceptions

2023 AI Conference • April 17-19, 2023 • Marriott Orlando Airport Lakeside • Orlando, FL

Workshops and Sessions

• KeynoteMultistate MeetingPre-Conference Workshop • PanelsSessions •


Announcing Our Keynote Speaker

We are honored to announce our keynote speaker for the 2023 AI in Ag Conference will be Chris Malachowsky.
Chris Malachowsky founded NVIDIA in 1993 and has more than 40 years of industry experience. He serves as a member of the executive staff and a senior technology executive for the company. The University of Florida granted Chris an honorary doctorate in Technology in 2022.
Malachowsky has been instrumental in managing, defining and driving the company’s core technologies as it has grown from a startup to the global leader in visual and parallel computing. As an executive at NVIDIA, he has led numerous functions, including IT, operations and all facets of the company’s product engineering. Most recently, he was responsible for NVIDIA’s world-class research organization, which is chartered with developing the strategic technologies that will help drive the company’s future growth and success.
A recognized authority on integrated-circuit design and methodology, he has authored close to 40 patents. He holds a BSEE degree from the University of Florida and an MSCS degree from Santa Clara University. Both schools have honored Malachowsky with Distinguished Alumnus awards. He also received an honorary doctorate in technology from the University of Silicon Valley in 2022. Beyond his technical accomplishments, Malachowsky has also received an Emmy for a film he helped produce, Inheritance, that won Best Documentary in 2009. He was also inducted into the Florida Inventors Hall of Fame in 2019.
Malachowsky and NVIDIA have been strong supporters of agriculture with their technology providing innovative advancements, including an acceleration platform delivering AI startups with go-to-market support, expertise, and technology. NVIDIA has also been instrumental in supporting the latest in technology to academic and research programs globally, as can be seen through their NVIDIA Academic Hardware Grant Program. Currently, NVIDIA’s and Chris’s investment at University of Florida has been transformative with state-of-the-art computing, NVDIA in-house expertise, and the new Malachowsky Hall for Data Science and Information Technology.

Multistate Meeting

Meeting of S1090: AI in Agroecosystems: Big Data and Smart Technology-Driven Sustainable Production

April 17, 2023 • 10:00am to 12:00pm

Organizer: Thanos Gentimis

Three main objectives of the multistate are:

  1. Develop AI-based approaches for agroecosystems production, processing, & monitoring
    a. AI tools for crop and animal production b. AI tools for autonomous system perception, localization, manipulation, and planning for agroecosystems c. Natural resources scouting and monitoring d. Socioeconomic sustainability e. Phenotyping and genotyping
  2. Data curation, management, accessibility, security, and ethicsa. Develop open-source, public agricultural datasets for benchmarking AI algorithms with a focus on explainability b. Standardization and testbed development
  3. AI adoption (technology transfer) and workforce development
Information about the meeting:

This will be a great opportunity to introduce new members, talk about some collaborative efforts and organize the annual meeting this summer in Louisiana. 

Pre-Conference Workshop

Pre-conference workshop: AI in agriculture: Let's write a modern thesis!

April 17, 2023 • 1:00pm to 3:00pm

Instructors: Thanos Gentimis (LSU), Leticia Santos (LSU)

In this hands-on workshop, Thanos Gentimis and Leticia Santos will present a full description of what a modern thesis could look like for a PhD student in agriculture, incorporating data intensive techniques, with an emphasis on AI based methodologies (Random Forests and Neural Networks). The instructors will give a step-by-step description of the process and go over various data synthesis codes that incorporate images (drones, satelites), weather data (temperature precipitation), soil data (including micronutrients, organic matter composition, etc), as well as various phenotypic indices throughout the growing season. Then the instructors will present a full ML implementation through Python for yield prediction based on all that information. Prior to the workshop, the attendees will receive full instructions on how to install the necessary software (Python through the Anaconda distribution), and they will be given access to an online repository with all the data (synthetic) and codes for the workshop. There are no pre-requisites for this apart from enthusiasm and patience.

To register for this event, complete the google form.


Parameters for the sustainable data management framework in sustainable ag: an industry perspective

April 18, 2023 • 1:30pm to 3:00pm

Moderator: Max Teplitski, Ph.D. Chief Science Officer, International Fresh Produce Association

Description: The panel will highlight the urgent need to align data acquisition and data management in climate-smart agriculture from the field to a thriving marketplace that equitably rewards producers for the adoption of ESG practices.   Harmonization and standardization of measurements of carbon sequestration and GHG fluxes, quantification of social and governance practices, curating and transforming data, tracking ESG commitments, investments and outputs through the supply chain and ensuring economically meaningful framework for the ESG marketplace will be discussed.  Finally, considerations for equitable return to those who contribute data to models (either public or those used by for-profit entities) will be discussed.

Panel Organizer:

Dr. Max Teplitski

Chief Science Officer, International Fresh Produce Association

Dr. Max Teplitski is a Chief Science Officer at the International Fresh Produce Association (IFPA), where he is responsible for the science, ag. technology, supply chain and sustainability programs. Prior to joining IFPA, Dr. Teplitski was Division Director (Acting) and National Program Leader at the USDA National Institute of Food and Agriculture, where he oversaw federal research investment portfolios in produce safety, microbiology and nutrition. An author of over 100 peer-reviewed publications, Dr. Teplitski was a Professor at the University of Florida. Dr. Teplitski served as a Fulbright Specialist in Agriculture (Escuela Politecnica del Litoral), U.S. Embassy Science Fellow, Biotech Outreach Speaker (U.S. Department of State), and G.E. Burch Fellow in Theoretical Medicine (Smithsonian Institution). He is a recipient of J.E. Feeley Award in Recognition of Significant Contributions in Environmental Microbiology, UF-HHMI Science For Life Distinguished Mentor Award, Animal Conservation Award (Lindberg Foundation), and W.E. Krauss Director’s Award for Excellence in Research (Ohio Agricultural Research and Development Center). He is a board member of the Center for Produce Safety. He is also a Courtesy Faculty at the UF Plant Pathology Department.


Dr. Molly Brown

CSO, 6th Grain Corporation

Molly E Brown is the Chief Science Officer of 6th Grain Corporation, a digital agriculture company based in the United States. Dr. Brown has a PhD and Masters in Geography and a Bachelors of Science in Biology. Molly has twenty years of experience in interdisciplinary research using satellite remote sensing data and models with socio-economic and demographic information to better understand food security drivers and agriculture. She has published over 120 journal articles in a variety of disciplines and has two books. In 2015, she was the lead author of a US Climate Assessment report published by the US Department of Agriculture entitled ‘Climate Change, Global Food Security and the U.S. Food System’.

Aaron Hutchinson

President & Co-Founder, CropTrak

Since co-founding CropTrak in 2009, Aaron Hutchinson has led its continuous evolution to remain on the forefront of raw source supply chain data management for the food industries. Leveraging his deep farming roots and data science experience, CropTrak helps food companies collect, process and report crop, contract, research and ESG data – digitally in real-time – for more than 73 identity-preserved and specialty crops in 57 countries worldwide. Previously, Aaron worked for NAVAIR as a senior imagery engineer, designing and delivering geospatial technology for four branches of the U.S. military, Special Operations Command and U.S. intelligence agencies. This experience gave him in-depth exposure to how technology must flex to harsh environmental conditions, support easy adoption by in-field users and ensure real-time accuracy to minimize risk.

Martha Montoya

CEO, AgTools

With over 30 years of worldwide IT/Telecommunications/Food/Agricultural and Supply Chain experience, Martha's career in the agricultural industry started while sourcing ingredients from the Americas. This provided her with the knowledge of the product from the source to delivery and ultimately becoming a leader in the industry, traveling while delivering projects beneficial for the supplier and customers on 4 continents. Dealing with both small and industrial size farms, government entities and sophisticated buyers in Europe, Russia and the United States, she has set up production lines across many crops and commodities. Today she leads Agtools, a Machine Learning and Artificial Intelligence award winner, a SaaS and enterprise firm that delivers global food & agricultural financial and market intelligence data. Agtools offers trusted official data from around the world, in real-time data for farmers and buyers to manage market volatility, increase profitability, and reduce the world’s food waste and CO2, and SO2 footprint. Formal education in Chemistry and Biology with post graduate courses at the University of Chicago, the Tuck School of Business at Dartmouth, Stanford University Entrepreneurial and Scalability program and the UC Davis Institute for Food, Ag & Health Entrepreneurship.

Dr. Jeff Orrey

Founder and CSO, Geovisual Analytics

Jeff is the Founder and Chief Science Officer of GeoVisual Analytics, where he is leading the development
of new capabilities for GeoVisual’s analytics platform for precision agriculture. Before founding GeoVisual,
Jeff was a Lead Program Manager at Microsoft, directing a team to develop and deploy the Bing Maps
Server, a private-cloud version of Microsoft’s Bing Maps that today is the mapping platform for New York
City's counter-terrorism system. As the lead scientist at another startup, Jeff led development of data
analysis technologies that were sold to a Chevron-backed company that is now the worldwide leader in
real-time hydraulic fracture monitoring. Jeff holds a Ph.D. in Physics and has served as a Science and
Technology Policy Fellow at the U.S. Agency for International Development.

Stakeholder Panel Discussion

April 19, 2023 • 10:30am to 12:00pm

Moderator: Joby Sherrod, Director of Agronomy ALICO Incorporated

Description: COMING SOON

Panel Organizer:

Joby Sherrod

Director of Agronomy,
ALICO Incorporated

Joby started off his education at Florida Southern College, earning a Bachelor of Science with a focus in Citrus. He would later go on to obtain his Master of Science degree in Applied Horticulture/Horticulture Operations.  Joby has over 23 years working in the citrus industry, and has had the opportunity to work at many different levels in citrus production, from the bottom to the top.


Scott Berden

US Sugar Corporation

Scott Berden is the Precision Ag Manager for US Sugar. US Sugar was founded in 1931 and grows sugarcane on 200,000 acres of land in 5 counties in South Florida with full vertical integration from the field to the refinery, providing nearly 10 percent of the sugar produced in the United States. Scott has over 20 years of experience in the agriculture technology field. He is responsible for over 300 square miles of infield GIS data and over 350 vehicles outfitted with precision ag technology. Some of the technologies employed include RTK GNSS base station network, large scale Wi-Fi, flow and application controls, auto vehicle guidance, and real time logistics. He also collaborates with equipment manufacturers and technology companies to provide guidance for products of interest to enterprise agriculture. 

Brian Kelly

Vantage Southeast/Trimble

Greg Land


Kyle Norton

Everglades Farm Equipment

Kyle Norton is the Precision Solutions Manager for Everglades Equipment Group. Starting in 1963, Everglades Equipment Group is a family owned John Deere dealership that has grown to 18 locations across the state of Florida. Kyle has been in and around the Ag industry for 30+ years and in the Precision Ag department at Everglades going on 9 years. He and his team are responsible for selling and supporting precision products from John Deere and other third-party companies in the Ag, turf, and golf industries. They look for new opportunities in technology as well as develop custom solutions to help their growers be successful. Examples of technologies supported include the full line of John Deere technologies, RTK network, Third party hardware, software, and autonomy, visual guided spraying, LIDAR, variable rate application, farm management software, telematics, and much more.

 Steve Seamon 

National Marketing Manager, Helena Agri-Enterprises


April 18, 2023 • 10: 30am to 12:30pm • Five Concurrent Sessions

Session 1: AI Applications in Crop Production • Moderators: Aditya Singh and Dana Choi (University of Florida)
Presenter Time Affiliation Title Authors
Abhilash Chandel 10:30-10:50am Virginia Tech AI-Machine Learning with Aerial Spectral Imagery for Peanut Maturity Prediction Abhilash Chandel; Jitender Rathore; Maria Balota
Nikolaos Tsakiridis 10:50-11:10am Aristotle University of Thessaloniki In Situ Hyperspectral Imaging for Estimation of Wine Grape Ripeness Using Attention-Based Convolutional Neural Networks Nikolaos L. Tsakiridis, Eleni Kalopesa, Nikiforos Samarinas, George C. Zalidis, Nikolaos Tziolas
Marcelo Barbosa Junior 11:10-11:30am Louisiana State University Machine Learning Models and UAV Multispectral Imagery to Predict Sugar Content in Sugarcane Fields Marcelo Rodrigues Barbosa Júnior, Bruno Rafael de Almeida Moreira, Romário Porto de Oliveira, Flávia Luize Pereira de Souza, Carolina Trentin, Arthur Borges Brigel Machado, Dulis Duron Chevez, Frantisek Širůček, Giulia Bortolon, Rejina Adhikari, Tri Setiyono, Rouverson Pereira da Silva, and Luciano Shozo Shiratsuchi
Lei Zhao 11:30-11:50am Texas A&M University - Corpus Cristi In-Season Cotton Yield Prediction Based on Transformer and UAV Data Lei Zhao, Mahendra Bhandari, Dugan Um, Kevin Nowka, Pankaj Pal, Jose Landivar, Francisco Gaona, Juan Landivar
Scott Carpenter 11:50am-12:10pm North Carolina State University Sweet Potato Yield Predictions to Aid Harvest Timing Using High-Throughput Portable Scanner and Machine Learning C. Scott Carpenter, Daniela S. Jones, Michael Kudenov, Cranos Williams
Shelly Hunt 12:10-12:30pm SAS An Approach to Feature Engineering and Comparison of Machine Learning and Statistical Models for Crop Yield Prediction Shelly Hunt, Daniela Jones, John Gottula


Session 2: AI in Food Processing, Food Safety and Supply Chain • Moderator: Won Suk "Daniel" Lee (University of Florida)
Name Time Affiliation Title
Genevieve Shattow 10:30-10:50am Throughput, Inc. Finding the Low Hanging Fruit in a Field of Opportunity
Fartash Vasefi 10:50-11:10am SafetySpect Multimode Spectroscopic Scanner with Fusion AI for Fish Quality and Adulteration Assessment and Enhanced Traceability
Frank Asche 11:10-11:30am University of Florida AI in Seafood: Opportunities and Challenges
Sunil Koduri 11:30-11:50am Transparent Path Using AI to Predict Product Freshness in the Food Supply Chain
  11:50am-12:30pm Panel discussion  


Session 3: AI Applications in Soil Moisture and Weather Events • Moderator: Carlos Hernandez (Kansas State University)
Name Time Affiliation Title Authors
Jasia Jannat 10:30-10:50am University of Georgia Quantifying the Frequency of Flash Drought in the Southeastern United States and Estimating Its Effects on Corn and Cotton Yields Jasia Jannat, José Andreis, Gerrit Hoogenboom, Pam Knox, George Vellidis
Eduart Murcia 10:50-11:10am University of Florida A Data Preprocessing and Forecasting Protocol for Soil Moisture Forecasting Using Signal Decomposition Analysis and Long-Short-Term Memory Eduart Murcia, and Sandra M. Guzmán.
Gregory Conde 11:10-11:30am University of Florida A Moving Horizon Estimation Strategy for Soil Moisture Forecasting: A Case Study for Sweetcorn Production in South Florida Gregory Conde, postdoctoral fellow, and Sandra M. Guzmán assistant professor, Department of Agricultural and Biological Engineering, Indian River Research and Education Center University of Florida.
Biswanath Dari 11:30-11:50am North Carolina A&T Explainable Machine Learning Approach Quantified the Long-Term (1981–2015) Impact of Climate and Soil Properties on Yields of Major Agricultural Crops Across CONUS Debjani Sihi, Biswanath Dari, Abraham Kuruvila, Gaurav Jha, Kanad Basu
Xi Zhang 11:50am-12:10pm Florida Institute of Technology Flood Inundation Meets Image Super-Resolution Xi Zhang, Akshay Aravamudan, Zimeena Rasheed, Kira E. Scarpignato, Witold F. Krajewski, Efthymios I. Nikolopoulos and Georgios C. Anagnostopoulos
Emily Bedwell 12:10-12:30pm University of Georgia Estimating Sweet Corn Evapotranspiration in the Southeastern United States to Improve Irrigation Scheduling Efficacy Emily Bedwell, Lorena Lacerda, Ted McAvoy, Brenda Ortiz, John Snider, and George Vellidis


Session 4: Adoption of AI technologies • Moderator: Jeff Vitale (Oklahoma State University)
Name Time Affiliation Title Authors
Tony Balkwill 10:30-10:50am NithField Advanced Agronomy A Grower's Point of View on AI Anthony Balkwill
Kimberly Morgan 10:50-11:10am University of Florida Technology and Farm Risk Management: Why Market Information Drives Long-Term Profitability Kimberly L. Morgan
Omeed Mirbod 11:10-11:30am University of Florida Creating Synthetic Data and Simulated Environment of Plasticulture Production Beds and Strawberry Plants for Training Agricultural Robotics Perception Daeun Choi and Omeed Mirbod
Kendall Kirk 11:30-11:50am Clemson University DATA Sensor Field Lab: Bringing Together Expertise and Multimodal Analytics to Define the Value of Agricultural Sensors Kendall R. Kirk and John Gottula
Hangjin Liu 11:50am-12:10pm North Carolina State University Building an Objective Model for Predicting Ideal Sweet Potatoes Using Shape, Size related Features Hangjin Liu, Michael Boyette, Michael Kudenov, Craig Yencho, Cranos Williams
Jonathan McFadden 12:10-12:30pm USDA Automation and Digital Agriculture in Major U.S. Field Crops: Trends, Drivers, and Opportunities  


Session 5: Incorporating Producers and Consumers into AI Technology Development • Moderator: Joseph Quansah (Tuskegee University)
Name Time Affiliation Title Authors
Ziwen Yu 10:30-10:50am University of Florida Lowering the Threshold for Growers to Participate in the Carbon Market Supported by Research and Extension Resources Ziwen Yu
Tong Wang 10:50-11:10am South Dakota State University Farmer Perceived Challenges Towards Precision Agriculture and Influencing Factors Tong Wang, Hailong Jin, Heidi Sieverding
Chris Boyer 11:10-11:30am University of Tennessee, Knoxville Precision Livestock Farming: Beef Producers Perceived Needs and Barriers Christopher Boyer, Susan Schexnayder, Kevin E. Cavasos, and Jamie Greig
Josh Martin 11:30-11:50am VISIMO Demeter: A Decision Support tool for Small and Mid-Size Farms Constantine Mintas, Joshua Martin, Tyler Seward, Emma Lamberton, Bryan Weichelt
Taisha Venort 11:50am-12:10pm University of Florida Linking Producers’ Livelihood Factors to Agricultural Management Decision-Making and Ecosystems Services Taisha Venort, Cheryl Palm, Rafael Munoz Carpena,Alvaro Carmona-Cabrero
Anupam Bhar 12:10-12:30pm Iowa State University Model-Predictive In-Season Scheduling of Irrigation Or/and Nitrogen Fertilizer for Maximized Profit of Small Farm Holder – The MISSION Framework Anupam Bhar; Ratnesh Kumar


April 18, 2023 • 3:00pm to 5:00pm • Five Concurrent Sessions

Session 6: AI applications in Crop Yield and MaturityModerator: Brianna Posadas (Virginia Tech)
Name Time Affiliation Title Authors
Chenjiao Tan 3:00-3:20pm University of Florida Optimized Deep Convolutional Neural Network YOLOv5 for Fast and Accurate Cotton Flower Detection on Edge Devices Chenjiao Tan, Changying Li, Huaibo Song
Jasmeet Judge 3:20-3:40pm University of Florida Remote Sensing-Based AI Methods for In-Season Crop Progress Jasmeet Judge and George Worrall
Caleb Lindhorst 3:40-4:00pm Texas A&M University Predicting the Number of Growing Degree Days Until a Cotton Boll is Harvestable Using Deep Learning Caleb M. Lindhorst, Robert G. Hardin IV
Balaji Pokuri 4:00-4:20pm Iowa State University Cloud-Hosting of Agricultural Crop Simulator for Calibration and Management Decision Support Systems Balaji Sesha Srikanth Pokuri, Anupam Bhar, Ratnesh Kumar
Vijaya Joshi 4:20-4:40pm University of Florida Novel Techniques Based on Artificial Intelligence and Earth Observation for Crop Model Parameterization Vijaya Raj Joshi, Glorie Metsa Wowo, Hubert Kanyamahanga, Maria Alexeeva, Isaac Kobby Anni, Keith Alcock, Pierre C. Sibiry Traore, Mihai Surdeanu, Gerrit Hoogenboom
Pankaj Pal 4:40-5:00pm Texas A&M University UAS and AI Driven Digital Twin of Crop Features Pankaj Pal, Mahendra Bhandari, Lei Zhao, Jose Landivar, Francisco Gaona, Juan Landivar


Session 7: AI Application in Precision Farming for Crop Yield Prediction • Moderator: Long He (Pennsylvania State University) & Reza Ehsani (University of California Merced)
Name Time Affiliation Title Authors
Mailson Freire de Oliveira 3:00-3:20pm Auburn University Predicting Peanut Yield Using Satellite Images and Machine Learning Mailson Freire de Oliveira, Brenda Ortiz, Jarlyson Brunno Costa Souza, Franciele Morlin Carneiro, Marina Duarte de Val, Rouverson Pereira da Silva
Rafael Bidese 3:20-3:40pm Auburn University A Novel Mass Flow Sensor using mmWave Radar and Machine Learning Towards a Peanut Yield Monitor Rafael Bidese Puhl, Yin Bao, Christopher Butts, Joseph McIntyre, Timothy McDonald
Mohamed Zeid 3:40-4:00pm Texas A&M University A yield prediction machine learning framework for sorghum using UAS image data Mohammed Zeid, Kevin Nowka, Mahendra Bhandari, Krishna Gadepally, Jose Landivar, Juan Landivar
Jonathan Vance 4:00-4:20pm University of Georgia PYCS: Predict Your CropS With Machine Learning Jonathan Vance, Khaled Rasheed, Ali Missaoui, Fred Maier
Sudhanshu Panda 4:20-4:40pm University of North Georgia Site-Specific Fodder Management Decision Support System Development: Lespedeza Cuneata Biomass Production Analysis with Artificial Neural Network Modeling Approach Dr. Sudhanshu Sekhar Panda, University of North Georgia, Oakwood, GA, USA; Dr. Prahlad Jat, University of North Georgia, Oakwood, GA, USA; Dr. Ajit Kumar Mahapatra, Fort Valley State University, Fort Valley, GA, USA; Dr. Thomas Terrill, Fort Valley State University, Fort Valley, GA, USA; Dr. Aftab Siddique, Fort Valley State University, Fort Valley, GA, USA.
Thanos Gentimis 4:40-5:00pm Louisiana State University Hyperparameter Estimation for Neural Network Architectures in Agriculture-based Structured Data Sets for Yield Prediction Thanos Gentimis, Yinan Yang, Li-Hsiang Lin, Phillip Lanza, Joshua Woodard, Luciano Shiratsuchi, Tri Setiyono


Session 8: AI Applications in Breeding and Phenomics • Moderator: Yin Bao (Auburn University) & Kevin Wang (University of Florida)
Name Time Affiliation Title Authors
Shana McDowell 3:00-3:20pm North Carolina State University Computer Vision to Assess Root Development and Crop Yield Estimates Shana McDowell, Daniela Jones, Michael Kudenov, and Shelly Hunt.
Sudip Kunwar 3:20-3:40pm University of Florida Potential use of UAV-based remote sensing tools for indirect assessment of harvest index and associated complex biomass partitioning traits in wheat Sudip Kunwar, Dr. Md. Ali Babar, Dr. Yiannis Ampatzidis
Jeffrey Vitale 3:40-4:00pm Oklahoma State University The Economic Benefits of Yield and Price Digital Twin Forecasting System for Texas Cotton Producers Dr. Juan Landivar, Texas A&M Corpus Christi Dr. Jeffrey Vitale, Oklahoma State University Dr. Mahendra Bhandari, Texas A&M Corpus Christi Dr. Yuri Calil, Texas A&M Corpus Christi
Jeanette Hariharan 4:00-4:20pm Florida Gulf Coast University An AI-Based Spectral Data Analysis Process for Recognizing Unique Plant Biomarkers and Disease Features Jeanette Hariharan, Yiannis Ampatzidis, Jaafar Abdulridha, Ozgur Batuman
Raul Sebastian Martinez 4:20-4:40pm Texas A&M University Evaluating the Accuracy of Machine Learning Approaches for Multi-environment Cotton Cultivar Yield Prediction Raul Sebastian Martinez, ROBERT G. HARDIN
Yaping Xu 4:40-5:00pm University of Tennessee, Knoxville Nitrogen Content Modeling of Field-Grown Switchgrass (Panicum virgatum) with UAV Datasets and Machine Learning Yaping Xu, Reginald J. Millwood, Mitra Mazarei, C. Neal Stewart Jr.


Session 9: AI Applications in Livestock Management • Moderator: Daniel Morris (Michigan State University)
Name Time Affiliation Title Authors
Luis Tedeschi 3:00-3:20pm Texas A&M University Computer Vision Applied to Beef Cattle Feeding Behavior at Experimental Feedlot Pens Egleu D. M. Mendes, Yalong Pi, Jian Tao, Luis O. Tedeschi
Daniel Morris 3:40-4:00pm Michigan State University Detecting Cage-free Floor Eggs Using a Ceiling-Mounted Camera Daniel Morris, Tessa Grebey, Janice Siegford
Ramviyas Parasuraman 4:00-4:20pm University of Georgia Robot-Centric Broiler Mortality Detection using Deep Learning Ehsan Latif, Ramviyas Parasuraman, Ramana Pidaparti, Brian Fairchild
Lilong Chai 4:20-4:40pm University of Georgia Machine Vision Systems for Monitoring Poultry Welfare Chai, Lilong; Bist, Ramesh; Subedi, Sachin; Yang, Xiao
Ryan Reuter 4:40-5:00pm University of Georgia The Application of AI Algorithms to Optimally Implement Virtual Fencing and Precision Livestock Grazing Dr. Ryan Reuter, Dept. of Animal and Food Sciences, Oklahoma State University Dr. Kevin Wagner, Oklahoma Water Center, Oklahoma State University Dr. Laura Goodman, Dept. of Natural Resources Ecology and Management, Oklahoma State University Dr. Jeffrey D. Vitale, Oklahoma State University


Session 10: PANEL Transform Research to Innovation: Startup Companies, Challenges, and Opportunities • Moderator: Kimberly Morgan (University of Florida)
Name Affiliation Website
Marc Bermejo Satlantis
Matt Donovan Agriculture Intelligence
Bob Pitzer Harvest CROO Robotics
Panos Pardalos University of Florida and

April 19, 2023 • 8:00am to 10:00am • Four Concurrent Sessions

Session 11: Innovations in Academic, Private, and Public Sector to Meet the Needs and Demands of AI • Moderator: Brenda Ortiz (Auburn University)
Name Time Affiliation Title Authors
Thomas Burks 8:00-8:20am University of Florida Creating Parallel SmartAg Systems Certificate Programs for Engineering and Applied Science Graduate Students Thomas Burks, Adam Watson, Quentin Frederick, Kati Migliaccio, Renfu Lu
Jeffrey Vitale 8:20-8:40am Oklahoma State University Jump Starting AI Teaching Curriculum at Oklahoma State University’s Ferguson School of Agriculture Jeffrey Vitale, Department of Agricultural Economics, Oklahoma State University Jeffrey Sadler, Biosystems and Agricultural Engineering Department, Oklahoma State University John Long, Biosystems and Agricultural Engineering Department, Oklahoma State University Ryan Reuter, Animal and Food Sciences, Oklahoma State University
Kati Migliaccio 8:40-9:00am University of Florida AI Across the Curriculum at UF Kati Migliaccio, Jane Southworth
Brian Stucky 9:00-9:20am USDA Catalyzing AI-driven Innovation in the USDA's Agricultural Research Service Brian J. Stucky
Ali Moghimi 9:20-9:40am Univerisity of California Davis Student Assessment in the Era of AI and ChatGPT Ali Moghimi, Shyam Agarwal


Session 12: AI Applications In Pathogen, Pest, Toxin, and Weed Control • Moderator: Charlie Li (University of Florida)
Name Time Affiliation Title Authors
Dong Chen 8:00-8:20am Michigan State University Synthetic Data Augmentation by Diffusion Probabilistic Models for Enhancing Weed Recognition Dong Chen, Xinda Qi, Yu Zheng, Yuzhen Lu, Zhaojian Li
Jiajia Li 8:20-8:40am Michigan State University A Novel Semi-supervised Learning Framework for Multi-class Weed Detection Jiajia Li, Dong Chen, Zhaojian Li
Pawel Petelewicz 8:40-9:00am University of Florida Simulation-based Nozzle Density Optimization for Maximized Efficacy of a Machine-vision Weed Control System for Applications in Turfgrass Settings Paweł Petelewicz, Qiyu Zhou, Marco Schiavon, Arnold W. Schumann, and Nathan S. Boyd
Yuzhen Lu 9:00-9:20am Michigan State University Cross-season Generalization of Deep Learning for Robust Weed Detection Yuzhen Lu; Boyang Deng
Sunaab Kukal 9:20-9:40am University of Georgia Developing a Mathematical Model for Detecting Aflatoxin Hotspots in Peanut Fields Kukal S, Bourlai T, Kermarait R, Peduzzi A, Pilon C, Vellidis G
Lakshay Anand 9:40-10:00am University of Kentucky Predicting Provenance and Grapevine Cultivar Implementing Machine Learning on Vineyard Soil Microbiome Data Lakshay Anand, Carlos Rodriguez Lopez


Session 13: Data Security, Data Privacy and Ownership, and Ethics • Moderators: Ziwen Yu (University of Florida) & Mahendra Bhandari (Texas A&M University AgriLife Center at Corpus Christi)
Name Time Affiliation Title Authors
Ziwen Yu 8:00-8:20am University of Florida Is there a rule to follow for data rights in digital agriculture? -- A review of current industrial practices Ziwen Yu, Daniel Sokol, Yilin Zhuang
Daniel Petti 8:20-8:40am University of Florida Towards a Unified Management Framework for Large-Scale Agricultural Sensing Data Daniel Petti, Changying Li
Biswanath Dari 8:40-9:00am North Carolina A&T ‘Who Owns the Data’: Toward Solving Agriculture’s Data Ownership Challenge Biswanath Dari, John Gottula, Debjani Sihi
Brianna Posadas 9:00-9:20am Virginia Tech User-Centered Design and AI Assurance in Precision Agriculture for Farmers and Policymakers Brianna Posadas, Ayorinde Ogunyiola, Kim Niewolny
Younghoo Cho 9:20-9:40am University of Florida Solving the trust issue in digital commodity market in agriculture: a pathway for blockchain. Younghoo Cho
Ziwen Yu 9:40-10:00am University of Florida A new economic ecosystem brought by digital commodities in agriculture Ziwen Yu


Session 14 Panel: The Human Side of AI/Technology Adoption in Tree Crops: Research and Producer Perspectives  • Moderator: Margarita Velandia (University of Tennessee Knoxville)
Name Time Affiliation Title
Laura Warner 8:00-8:20am University of Florida Theory of Planned Behavior
Margarita Velandia 8:20-8:40am University of Tennessee, Knoxville Factors Correlated with the propensity to use automation
Amy Fulcher 8:40-9:00am University of Tennessee, Knoxville Development and Commercialization of Intelligent spray technology
Todd Gentry, Luke Sepe, and Timothee Sallin 9:00-9:20am Cherry Lake and IMG Overview of Cherry Lake and IMG and consideration for adopting technolgoy
Terry Hines 9:20-9:40am Hale and Hines Nursery Overview of Hale and Hines Nursery and considerations for adopting technology
Panel disucssion with Hao Gan 9:40-10:00am University of Tennessee, Knoxville Panel discussion

April 19 • 1:30pm to 3:30pm • Four Concurrent Sessions

Session 15: AI Applications in Crop Health • Moderator: Jasmeet Judge & Dana Choi (University of Florida)
Name Time Affiliation Title Authors
Christian Lacerda 1:30-1:50pm University of Florida The process of optimizing a cloud based software infrastructure: Agroview, a case of study Christian Lacerda, Lucas Costa, Yiannis Ampatzidis
Antonio de Oliveira Costa Neto 1:50-2:10pm   ACP Detection System on Sticky Traps Images Utilizing Artificial Intelligence Vitor Andrade Gontijo da Cunha, Antonio de Oliveira Costa Neto, Lucas Costa, Yiannis Ampatzidis
Quentin Frederick 2:10-2:30pm University of Florida Classifying Citrus Peel Diseases Using Features Extracted with Shallow Convolution Neural Networks from Hyperspectral Imagery Quentin Frederick, Thomas Burks, Adam Watson, Pappu Kumar Yadav, Jianwei Qin, Moon Kim, and Mark A. Ritenour
Wenhao Liu 2:30-2:50pm University of Florida Mapping citrus orchards utilizing aerial imagery with Agroview and Lidar Wenhao Liu, Yiannis Ampatzidis
Carlos Hernandez 2:50-3:10pm Kansas State University Mapping soybean seed quality from the sky: Use of Remote Sensing Data and Data Analytics for Quantifying Quality in Soybean Seed Crops. Carlos Hernandez, Aaron Prestholt, Peter Kyveryga, Adrian Correndo and Ignacio Ciampitti
Abhisesh Silwal 3:10-3:30pm Carnegie Mellon University, The Robotics Institute An Autonomous Robot System for Precision Weed Management Rohan Deshpande, Abhisesh Silwal, Francisco Yandun, Vinay Vijayakumar, George Kantor, Yiannis Ampatzidis


Session 16: AI Applications in Precision Farming for Crop Management • Moderator: Shirin Ghatrehsamani (Pennsylvania State University)
Name Time Affiliation Title Authors
Juan Landivar 1:30-1:50pm Texas A&M University Digital Twins for Agriculture: Enabling Technology for In-season Precision Crop Management Juan A. Landivar, Mahendra Bhandari, Pankaj Pal, Lei Zhao, Jury Calil, Jose Landivar, Francisco Gaona
Lucas Costa 1:50-2:10pm University of Florida Building reliability: development of a prototype to production for a smart citrus tree sprayer using sensor fusion and artificial intelligence Lucas Costa, Yiannis Ampatzidis
Vinay Vijayakumar 2:10-2:30pm University of Florida Specialty crop-specific robotic precision smart sprayer based on machine vision and PWM-controlled spraying system. Vinay Vijayakumar, Yiannis Ampatzidis, Abhisesh Silwal, George Kantor
Xiaofei Li 2:30-2:50pm Mississippi State University Economic Evaluation of Variable Rate Application using On-Farm Precision Experimentation Data Xiaofei Li (Mississippi State University)
Fitsum Teshome 2:50-3:10pm University of Florida Unmanned Aerial Vehicle (UAV)-based Imaging and Artificial Intelligence (AI) Modeling for Plant Phenotyping Fitsum T. Teshome and Haimanote K. Bayabil
Congliang Zhou 3:10-3:30pm University of Florida A smartphone application for mapping the populations of two-spotted spider mites in strawberry Congliang Zhou, Won Suk Lee, Xue Zhou, Shuhao Zhang, Alireza Pourreza


Session 17: AI and Robotics in Agriculture • Moderator: Henry Medeiros (University of Florida) & Stavros Vougioukas (Univeristy of California Davis)
Name Time Affiliation Title Authors
Xue Zhou 1:30-1:50pm University of Florida AI-based Inspection System for Mechanical Strawberry Harvesters Xue Zhou, Yiannis Ampatzidis, Won Suk Lee, Shinsuke Agehara, John K. Schueller, Carl Crane
Zhengkun Li 1:50-2:10pm University of Florida Semantic mapping and localization of a ground robot for automated phenotyping and visual navigation Zhengkun Li, Changying Li
Juan Villacres 2:10-2:30pm University of California Davis Assessment of apple detection performance of a multi-camera system Juan Villacres, Stavros Vougioukas (PI)
Long He 2:30-2:50pm Pennsylvania State University Artificial Intelligence (AI) for Robotic Apple Crop Load Management Long He, Magni Hussain, Xinyang Mu, Paul Heinemann
Byron Hernandez 2:50-3:10pm University of Florida The adoption of multi-object tracking techniques in agriculture. Insights and case study in lettuce tracking. Byron Hernandez and Henry Medeiros.
Konstantinos Karydis 3:10-3:30pm University of California Riverside Perceptual and Informative Planning in Orchards with Autonomous Mobile Agricultural Robots Dimitris Chatziparaschis, Azin Shamshirgaran, Caio Mucchiani, Elia Scudiero, Stefano Carpin, Konstantinos Karydis


Session 18: Climate-smart AI-enhanced Technologies for Agriculture and Ecosystem Services • Moderator: Young Gu Her and Clyde Fraisse (University of Florida)
Name Time Affiliation Title Authors
John Gottula 1:30-1:50pm SAS Indoor Ag Forecasting John Gottula and Jay Laramore
Jaafar Abdulridha 1:50-2:10pm University of Minnesota Twin Cities Early Detection of Stress in Greenhouse-Grown Industrial Hemp Plants by Hyperspectral Imaging Jaafar Abdulridha, Ce Yang, An Min, Colin Jones, Thomas Michaels, Quinton Krueger, Robert Barnes, and T.J. Velte
Jai Hong Lee 2:10-2:30pm South Carolina State University Soil Erosion Variability, Teleconnectivity, and Predictability over the United States Associated with Large-scale Climate Variations using AI Cluster Analysis Jai Hong Lee, Saidi Siuhi
John Upchurch 2:30-2:50pm University of Florida Applications of Remote Sensing and Machine Learning to Ecosystem Service Metrics John Upchurch, G. Simon, P. Chand, A. Lippert, D. Alabi, W. Eum, J. Harling, H. Mahajan, A. Sharma, Z. Tian, V. Vignesh, L. Zotarelli, J. Dubeux, A. Zare, and J. Harley
Pappu Yadav 2:50-3:10pm University of Florida Studying the effects of discrete wavelet transform on deep learning-based image classification of E.coli concentration levels Pappu Kumar Yadav, Thomas Burks, Quentin Frederick, Jianwei Qin, Moon Kim, and Mark A. Ritenour
Nikolaos Tziolas 3:10-3:30pm   Deep learning architecture employing Earth Observation data for soil mapping Nikolaos Tziolas, Nikolaos Tsakiridis, Elli Kalopesa, Uta Heiden, Klara Dvorakova, Pablo d’Angelo, Simone Zepp, Bas van Wesemael