Stefano Delbono
Papers
1
Total Citations
55
H-Index
1
About
Stefano Delbono is a leading researcher in precision agriculture and high-throughput plant phenotyping, with a particular focus on integrating unmanned aerial vehicles (UAVs) and advanced remote sensing into crop science. His most-cited work, a 2017 study on UAV-based phenotyping to discriminate barley vigour using visible and near-infrared vegetation indices (55 citations), has become a foundational reference in the field. This research demonstrated how drone-mounted sensors can assess plant traits with a speed and precision unattainable through traditional manual methods, effectively bridging the gap between genomics and field performance. Delbono’s contributions are pivotal in enabling breeders to non-destructively monitor large populations, accelerating the selection of resilient crop varieties. His work has been widely adopted by agricultural scientists and technologists seeking to automate and scale phenotypic data collection. By pioneering the application of vegetation indices from UAV imagery, Delbono has helped establish a new paradigm in plant breeding—one that leverages robotics, imaging, and data analytics to meet the global demand for sustainable food production.
Research Focus
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Top Papers
- 1