Tomohiro Sakamoto

Ehime University

Papers

1

Total Citations

7

H-Index

1

About

Tomohiro Sakamoto is a leading researcher at the intersection of agricultural science and artificial intelligence, specializing in precision horticulture and the "speaking plant approach" (SPA). His work focuses on developing non-invasive, deep learning-based methods to quantify plant growth, particularly through daily stem elongation measurement. In a landmark 2022 study, Sakamoto demonstrated the practical deployment of this technology in two commercial tomato greenhouses, bridging the gap between skilled farmers’ visual intuition and data-driven crop management. By translating subtle growth patterns into actionable numerical indices, his research enables real-time monitoring of plant health and stress, reducing reliance on subjective observation. Although his most-cited paper has garnered 7 citations to date, its impact is growing rapidly within the agri-tech community, as it provides a scalable framework for automated growth assessment. Sakamoto’s contributions are pivotal for advancing smart farming, offering a pathway to optimize irrigation, lighting, and harvesting schedules. His work exemplifies how AI can empower growers to make precise, evidence-based decisions, ultimately enhancing yield and sustainability in controlled-environment agriculture.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Practical use of Deep Learning-Based Daily Stem Elongation Measurement of Tomato Plants in Two Commercial Greenhouses
7 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Ehime University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago