Pappu Kumar Yadav
Papers
3
Total Citations
5
H-Index
1
About
Pappu Kumar Yadav is a researcher advancing the frontiers of precision agriculture through robotics, computer vision, and 3D phenotyping. His work focuses on developing cost-effective, accessible technologies to democratize smart farming, particularly for small-scale farmers and smallholders. A key contribution is his pioneering use of under-canopy cotton imagery for variety classification, demonstrating that ground-level perspectives can reveal critical insights—such as fruiting behavior and early nutrient deficiencies—that above-canopy methods miss. This work has garnered 3 citations and highlights a novel approach to crop monitoring. Yadav also led the development of a multiaxial modular ground robot that uses an RGB-Depth sensor to estimate soybean phenotypic traits, addressing the need for affordable, task-agnostic platforms. Additionally, he created PhenAI-Bot, an open-access tool for precision 3D phenotyping of pepper varieties in greenhouses, enabling the study of dynamic growth traits like plant height and leaf development across all stages. With over 5 citations across his early-career publications, Yadav’s research is laying the groundwork for scalable, data-driven agriculture that empowers growers worldwide.
Research Focus
Key Achievements
Top Papers
- 1Using under-canopy cotton imagery for cotton variety classification3 citations · 2022
- 2
- 3