Session A: Understanding the role, advantages, limitations, and gaps in sensor development, networking, integration, fusion, and applications in PA
- Dr. Jason Hallstrom, National Science Foundation, USA, NSF Investments in the Future of Precision Agriculture
- Prof. Steven Mirsky, US Department of Agriculture, USA, Operationalizing Precision Sustainable Agriculture
- Dr. Victor Alchanatis, Agricultural Research Organization (ARO), Israel, Integration of Artificial Intelligence and Sensing for Precision Farming
- Prof. Avital Bechar, ARO, Israel, Agricultural Robots and AI for Precision Agriculture
- Dr. Yafit Cohen, ARO, Israel, Big Data in Area-Wide and In-Field Scales
- Dr. Iftach Klapp, ARO, Israel, Enhancement of Low-Cost Sensing Devices for Precision Agriculture
Session B (Part 1): Defining the benefits of using big data and AI/ML to maximize the impact and applicability of PA and to support decisions for sustainable agriculture
- Prof. James Krogmeier, Purdue University, USA, Networking and Computing Infrastructure for Large Scale Agricultural Testbeds Supporting the IoT4Ag Engineering Research Center
- Dr. Brian Needelman, University of Maryland, USA, Integrating Topographic and Soil Survey Analyses into Predictions of Cover Crop Performance in Precision Sustainable Agriculture Models
- Dr. Yael Salzer, Agricultural Research Organization (ARO), Israel, Towards Informed Postharvest Logistic Management Systems to Reduce Food Loss, and Other Challenges
- Dr. Ariel Shabtay, ARO, Israel, Integrating Biomarkers into the Electronic-Sensors based PLF Tool Box
- Dr. Shai Sela, Agmatix, Israel, Harnessing Data Standards to Accelerate Collaborative Agronomic Big Data Research
Session B (Part 2): Defining the benefits of using big data and AI/ML to maximize the impact and applicability of PA and to support decisions for sustainable agriculture
- Prof. Dorivar A. Ruiz Diaz, Kansas State University, USA, Decision Support Tools for Farmers: Field Data Collection Challenges and Opportunities through Multidisciplinary Collaboration
- Prof. Taejoon Kim, University of Kansas, USA, Predicting In-Season Soil Mineral Nitrogen in Corn Production Using Generative Deep Learning Model
- Dr. Offer Rozenstein, Agricultural Research Organization, Israel, Data-Driven Estimation of Actual Evapotranspiration to Support Irrigation Management: Testing Two Novel Methods based on an Unoccupied Aerial Vehicle and an Artificial Neural Network
- Prof Yeal Edan, Ben Gurion University of the Negev (BGU), Israel, AgRobotics in the Era of IoT & AI for Sustainable PA
- Prof. Tal Svoray, BGU, Israel, A Machine Learning and Geoinformatics Water Erosion Approach in Agricultural Catchments
Session C (Part 1): Understanding big data advantages and limitations in key agricultural contexts: livestock farming, fertilization, irrigation, orchard management, site-specific weed management, pest management, and disease detection
- Dr. X. Carol Song Purdue University, USA, GeoEDF: A Framework for Designing and Executing Reproducible Geospatial Research Workflows in Science Gateways
- Prof. Raj Khosla, Kansas State University, USA, Artificial Intelligence for Agricultural Sustainability
- Prof. Uri Yermiyahu, Agricultural Research Organization (ARO), Israel, Reforming Crops’ Mineral Diagnostics by Chemometrics to Sustenance the Empirical Requirements of Decision Support Tools in Farming
- Dr. Yael Laor, ARO, Israel, Introduction to the Model Farm for Sustainable Agriculture, Newe Ya'ar, Volcani Institute
- Dr. Ehud Strobach, ARO, Israel, Seasonal Predictions of Crop Yield under Changing Climate Conditions: The Coupled Crop-Climate Modeling Approach
Session C (Part 2): Understanding big data advantages and limitations in key agricultural contexts: livestock farming, fertilization, irrigation, orchard management, site-specific weed management, pest management, and disease detection
- Prof. Won Suk (Daniel) Lee, University of Florida, USA, Specialty Crop Production in using Artificial Intelligence in Florida, USA
- Prof. Dharmendra Saraswat, Purdue University, USA, Unmanned Aerial Systems for Plant-Stress Identification and Monitoring
- Dr. Tarin Paz-Kagan, Ben Gurion University, Israel, Advances in Agricultural Unmanned Aerial Vehicles - Focus on Sensing Applications
- Dr. Ran Lati, Agricultural Research Organization (ARO), Israel, Early Sub-Soil Detection of Broomrape Infestation Using Spectral Data
- Dr. Or Sperling, ARO, Israel, Modeling The Cost of Deficit Irrigation
- Dr. Shahar Baram, ARO, Israel, Using Remote Sensing to Close the Yield Gap in Almond Orchards
Session D: Developing an AI system for early detection of yield problems in agriculture: Innovative research at the confluence of AI /ML, big data, and PA
- Prof. George Vellidis, University of Georgia, USA, Big Data, IoT, and AI Applications to Solve Agricultural Problems in the Southeastern USA: Three Case Studies
- Dr. Lizhi Wang, Iowa State University, USA, A Digital Twin Framework for Precision Agriculture
- Prof. Naftali Lazarovitch, Ben Gurion University of the Negev (BGU), Israel, Improving Fertigation Scheduling by Combining Continuous Monitoring and Numerical Modeling of the Root Zone
- Dr. Assaf Chen, MIGAL, Israel, Early Detection of White Mold Disease in Field Crops via Remote Sensing and Machine Learning
- Dr. Anna Brook, University of Haifa Israel, Multisource Remote Sensing Sensors/Platforms Integration and Synergy in Smart and Sustainable Agriculture
- Prof. Charlie Messina, University of Florida, USA, Emergence Agriculture: Concept for Managing Complexity in Maize Production
Session E: Investigation and evaluation of the influence of AI/ML in current and future PA contexts
- Prof. Ioannis (Yiannis) Ampatzidis, University of Florida, USA, AI-Enhanced Technologies for Precision Management of Specialty Crops
- Prof. Glen Rains, University of Georgia, USA, AI, Data Analytics and Precision Tools for Intelligent and Climate-Resilient Agriculture Systems
- Dr. Fadi Kizel, Technion- Israel Institute of Technology (Technion), Israel, AI-Based Muti-Sensor Data Fusion for Spatially Enhanced Spectral Mapping Products
- Prof. Eyal Ben-Dor, Tel Aviv University, Israel, Precision Agriculture: The Pedosphere under a Spectral Binocular
- Prof. Gilad Ravid, Ben Gurion University, Israel, Exploring Date Collection Methods and Investigating the Emergence of Macrophomina Phaseolina in Cotton Fields: A Comprehensive Study in Agricultural Decision Support Systems
- Prof. Raphael Linker, Technion, Israel, Predicting Nitrogen Content in Citrus Orchards Canopy using UAV and Satellites Data
Session F: Summarizing existing gaps in PA surrounding IoT/AI/ML and brainstorming ways to overcome them