Organizer: Thanos Gentimis
Three main objectives of the multistate are:
This will be a great opportunity to introduce new members, talk about some collaborative efforts and organize the annual meeting this summer in Louisiana.
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.
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:
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Dr. Max TeplitskiChief 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. |
Panelists:
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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’. |
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Aaron HutchinsonPresident & 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. |
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Martha MontoyaCEO, 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. |
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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. |
Moderator: Joby Sherrod, Director of Agronomy ALICO Incorporated
Description: COMING SOON
Panel Organizer:
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Joby SherrodDirector of Agronomy, |
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. |
Panelists:
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Scott BerdenUS 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 KellyVantage Southeast/Trimble |
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Greg LandAerobotics |
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Kyle NortonEverglades 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. |
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Steve Seamon National Marketing Manager, Helena Agri-Enterprises |
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| 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 |
| Session 6: AI applications in Crop Yield and Maturity • Moderator: 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 | https://satlantis.com/ |
| Matt Donovan | Agriculture Intelligence | https://www.agroview.ai/ |
| Bob Pitzer | Harvest CROO Robotics | https://www.harvestcroorobotics.com/ |
| Panos Pardalos | University of Florida | |
| 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 |
| 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 | |
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