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)Welcome and Objectives: Set the context for the workshop (10) minutes
Overview of AI in Postharvest Research (10 minutes)
Dr. Carolina Torres, Washington State University, Wenatchee, Washington, United States
Summary: Overview of AI applications, emphasizing data analysis, optimization, and quality assessment and discuss principles for designing experiments that maximize AI potential.Session 1: Analyzing Physical Properties (20 minutes)
Session 1: Analyzing Physical Properties (20 minutes)
Dr. Manuela Zude-Sasse (Liebniz Institute of Agricultural Engineering and Bio-economy)
Summary: Explore non-destructive techniques for fruit assessment.
Session 2: Investigating postharvest chilling injury in horticultural crops using AI-based imaging technology (20 minutes)
Dr. Tie Liu (University of Florida)
Summary: Methods used to predict the appearance of chilling injury in fresh horticultural crops.
Session 3: AI in Molecular Biology (20 minutes)
Dr. Huiting Zhang (Washington State University). Summary: Discuss molecular indicators related to postharvest tree fruit disorders using AI techniques.
Session 4: Remote Sensing and AI (20 minutes)
Dr. Luan Oliveira (University of Georgia). Summary: Explore how remote sensing, combined with AI algorithms, accelerates data processing for fruits and vegetables.
Session 5: Q&A and Group Discussion (20 minutes).
Interactive Session: Encourage participants to ask questions and share experiences. Collaboration Opportunities: Explore potential collaborations among attendees.
Session 6: Recap, Key Takeaways, and Feedback Collection (10 minutes)
