Abstracts

Abstract submission is now closed.

Abstract Deadline: Jan 12th, 2026
Notification of Acceptance: Early February 2026
Final Program Posted: February 2026

All submitted abstracts should be written in English. Abstracts (500 words max) will be peer-reviewed by the program committee. At least one author must be registered for the conference to present. 

Submission Topic Areas

• Plants & Crops
  • Spanning molecular, genetic, and field-level research in agricultural crops. Includes plant breeding, phenotyping, precision agriculture, crop management, pest and disease detection, and yield prediction. Also covers perennial production systems such as orchards, vineyards, and fruit or nut trees. Applications may include sensing technologies, IoT, remote sensing, and AI modeling approaches such as generative AI for simulation and prediction.
• Animals & Livestock
  • Covering cellular to production-scale research in agricultural animal systems. Includes genetics, health monitoring, nutrition, welfare, and production efficiency. Encompasses precision livestock farming, AI-enabled sensing, automation, and real-time stress and disease monitoring and management across species such as poultry, swine, beef, dairy, and aquaculture. Applications may leverage IoT devices, computer vision, and AI methods, including generative AI for data augmentation and simulation.
• Soils, Water, Air & Environment
  • Focusing on soil, water and air resources within agricultural systems. Includes soil health, nutrient and water management, hydrology, and conservation practices. Encompasses AI for precision irrigation, environmental monitoring, and resource-use efficiency. Approaches may include sensors, IoT networks, remote sensing, and AI modeling such as surrogate and generative models for predicting responses to weather extremes and variability.
• Food, Postharvest & Supply Chains
  • Highlighting agricultural outputs beyond the farm gate. Includes AI for food quality, safety, processing, packaging, and distribution. Applications span foreign object detection, shelf-life prediction, food fraud prevention, logistics optimization, cold-chain management, and traceability from farm to consumer. This category also covers AI in aquaculture postharvest and processing systems.
• AI Systems & Integrative Approaches
  • Emphasizing cross-cutting tools and methods that advance multiple areas of agriculture. Includes robotics, automation, computer vision, digital twins, decision-support systems, and data-driven modeling. Topics may address machine learning methods, data integration, socioeconomics, adoption, workforce development, and policy. Also includes responsible AI practices such as ethics, governance, and transparency.
• Cross-Cutting Topics (Extension, Education, Workforce Development, Policy)
  • For submissions that do not clearly fit into the categories above. Examples include but are not limited to: Extension and Outreach – research on the social science of stakeholder engagement, technology adoption, and decision-support tool implementation. Education and Workforce Development – teaching innovations, student learning outcomes, training in agricultural AI, and interdisciplinary curriculum design. Policy, Economics, and Social Systems – studies on policy frameworks, ethics, governance, adoption barriers, or broader societal implications of agricultural AI.

For additional guidance, see the Evaluation Rubric of 2026 AI in Agriculture Conference Presentation Abstracts. All abstracts will be peer-reviewed by the program committee. Authors will be notified of acceptance in February. Outstanding student submissions will be considered for student presentation awards.