Papers
4
Total Citations
211
H-Index
4
About
Abbas Atefi is a leading researcher at the intersection of agricultural science and robotics, specializing in high-throughput plant phenotyping and precision agriculture. His work addresses a critical bottleneck in modern crop breeding: the need for rapid, accurate, and non-destructive measurement of plant traits. Atefi’s most influential contribution is his comprehensive review on robotic technologies for plant phenotyping (2021, 143 citations), which has become a foundational reference for the field. He has pioneered in vivo robotic phenotyping methods, demonstrating the first human-like robotic system to measure leaf traits in maize and sorghum under greenhouse conditions (38 citations). Atefi further advanced the field by developing robotic detection and grasping techniques for stem diameter measurement—a key proxy for plant biomass and health (24 citations). His recent work employs deep learning for strawberry runner recognition (2024), directly supporting the development of robotic solutions for labor-intensive tasks in California’s strawberry industry. Through these innovations, Atefi is transforming traditional, manual phenotyping into automated, data-rich processes, enabling breeders to accelerate crop improvement for global food security.
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