Explore cutting-edge techniques, tools, and strategies to integrate artificial intelligence (AI) into postharvest research. Learn how AI can enhance data analysis, optimize storage conditions, and improve quality assessment for fruits and vegetables. During this workshop, we’ll delve into organizing datasets, determining the number of variables, and understanding their types. Join us to stay ahead in the rapidly evolving field of postharvest science. Join us for this dynamic workshop, where experts share insights, foster collaboration, and propel postharvest science into the future! 🌱
The goal of this workshop is to empower researchers, practitioners, and industry professionals with the knowledge and tools needed to revolutionize postharvest practices. By integrating artificial intelligence (AI) and non-destructive technologies, we aim to achieve the following objectives: 1. Enhanced Quality Control 2. Efficient Resource Management 3. Scientific Advancements 4. Sustainable Practices 5. Industry Transformation
Coordinator(s)- Randolph Beaudry, Michigan State University, Horticulture, East Lansing, Michigan, United States
- Angelos Deltsidis, University of Georgia, Horticulture, Tifton, GA, United States
Moderator(s)- Angelos Deltsidis, University of Georgia, Horticulture, Tifton, GA, United States
Speaker/Participant(s)- Carolina Torres, Washington State University, Wenatchee, Washington, United States
Introduction (10 minutes) Welcome and Objectives (10 mins)
Summary: Overview of AI applications, emphasizing data analysis, optimization, and quality assessment and discuss principles for designing experiments that maximize AI potential. - Luan Oliveira, University of Georgia, Tifton, Georgia, United States
Remote Sensing and AI (20 mins)
Summary: Explore how remote sensing, combined with AI algorithms, accelerates data processing for fruits and vegetables. - Pavlos Tsouvaltzis, Southwest Florida Research and Education Center, University of Florida, United States
Non-Destructive Technologies (20 mins)
Summary: Delve into advanced non-destructive methods for assessing vegetable crop physiology, quality, and safety. - Loren Honaas, USDA ARS TFRL, United States
AI in Molecular Biology (20 mins)
Summary: Discuss molecular indicators related to postharvest tree fruit disorders using AI techniques.
