Marcel Mooij
Papers
1
Total Citations
44
H-Index
1
About
Marcel Mooij is a leading researcher at the intersection of agricultural robotics, computer vision, and high-throughput phenotyping. His work focuses on developing automated systems that can reliably measure plant traits in real-world production environments, bridging the gap between controlled laboratory settings and operational greenhouses. Mooij’s most cited paper, “Automatic Phenotyping of Tomatoes in Production Greenhouses Using Robotics and Computer Vision: From Theory to Practice” (2021, 44 citations), exemplifies his commitment to practical, deployable solutions. In this work, he demonstrates how robotic platforms and advanced image analysis can accurately assess tomato traits—such as fruit size, color, and yield—directly within commercial greenhouses. This contribution is critical for both breeders, who rely on precise phenotypic data to estimate genetic value and select promising varieties, and growers, who need timely yield predictions for crop management. By tackling the challenges of variable lighting, occlusions, and dynamic plant growth, Mooij has helped move agricultural phenotyping from proof-of-concept to actionable tools. His research continues to shape the future of precision agriculture, enabling data-driven decisions that improve crop productivity and sustainability.
Research Focus
Key Achievements
Top Papers
- 1