J.-P. Da Costa

Papers

Total Citations

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About

J.-P. Da Costa is a researcher at the forefront of precision horticulture and agricultural robotics, with a focus on integrating computer vision and automation to solve critical challenges in crop management. His work centers on the development of intelligent systems for disease detection and sustainable weed control, directly addressing the need for reduced chemical inputs in modern agriculture. A key contribution is his research on the automatic diagnosis of multi-symptom grape vine diseases using computer vision, a project that demonstrates the potential of machine learning to identify complex plant pathologies from visual symptoms, with his 2023 paper on this topic garnering 3 citations. Complementing this, Da Costa has also advanced mechanical weeding technology through the BIPBIP system, an automated intra-row weeding solution that combines mechanical action with precise control to eliminate weeds without herbicides. Presented at the prestigious ISHS XXXI International Horticultural Congress, these works highlight his commitment to translating cutting-edge technology into practical, field-deployable tools. Da Costa’s research is particularly notable for its interdisciplinary approach, merging robotics, image analysis, and horticultural science to create scalable solutions that promise to enhance crop health and yield while promoting environmental sustainability.