Pioneering Agricultural Digital Twin: structural modeling and growth prediction framework for 3D virtual plants

• Project/Area Number: 25K09378
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 41050:Environmental agriculture-related
• Research Institution: Kyushu University
• Principal Investigator: FELDMAN Alexander・Davan 九州大学, 理学研究院, 博士研究員 (10999345)
• Co-Investigator(Kenkyū-buntansha): 野下 浩司 九州大学, 理学研究院, 助教 (10758494) ; 王 浩舟 東京大学, 大学院農学生命科学研究科(農学部), 特任研究員 (60994788)
• Project Period (FY): 2025-04-01 – 2029-03-31
• Project Status: Granted (Fiscal Year 2025)
• Budget Amount: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000); Fiscal Year 2028: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000); Fiscal Year 2027: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000); Fiscal Year 2026: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000); Fiscal Year 2025: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
• Keywords: digital twin / plant phenotyping / smart agriculture

Outline of Research at the Start

This research is organized into three subgoals. Subgoal 1 is to enhance 3D scanning and reconstruction techniques. Subgoal 2 focuses on extracting and parameterizing phenotypic traits from the detailed 3D models. Subgoal 3 involves applying machine learning models to predict plant growth.