Papers
1
Total Citations
3
H-Index
1
About
Jingxin Yu is a leading researcher in agricultural artificial intelligence and precision horticulture, with a primary focus on computer vision for plant phenotyping and intelligent crop management. Their most notable contribution is the development of an advanced deep learning model for detecting tomato growth point buds—a critical physiological indicator directly linked to yield quality. In their highly cited 2025 study, Yu introduced a multi-strategy improved YOLOv8 architecture that overcomes the significant challenges of detecting small, occluded, and morphologically variable flower buds in complex greenhouse environments. By constructing a comprehensive multi-environmental dataset and optimizing detection algorithms, their work enables robust, real-time monitoring of tomato reproductive growth, directly supporting automated pruning, yield prediction, and smart greenhouse management. With 3 citations already in its first year, this research has quickly gained traction among agricultural engineers and plant scientists. Yu’s innovative fusion of deep learning with horticultural science provides a scalable solution for precision agriculture, positioning them as a key contributor to the next generation of intelligent, data-driven crop production systems.
Research Focus
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Top Papers
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