Anne‐Katrin Mahlein
Papers
11
Total Citations
453
H-Index
7
About
Anne-Katrin Mahlein is a leading researcher at the intersection of plant pathology, remote sensing, and precision agriculture, whose work has fundamentally advanced how scientists detect, quantify, and manage plant diseases using cutting-edge digital technologies. Her research spans hyperspectral sensing, 3D laser scanning, machine learning, and robotics, making her a central figure in the emerging field of digital plant pathology. Mahlein's early influential work on 3D laser-scanned point clouds for plant phenotyping (186 citations) demonstrated how high-resolution spatial data could be used to classify plant organs and monitor growth, establishing a methodological foundation still widely referenced today. Her 2019 paper on hyperspectral sensors for disease resistance phenotyping (105 citations) underscored the critical need to integrate phytopathology, sensor technology, and machine learning into seamless workflows. Her contribution to standardizing scientific language through a phytopathometry glossary (67 citations) reflects her commitment to disciplinary rigor and cross-field communication. More recently, Mahlein has championed smart digital technologies and AI-driven tools for sustainable crop production and plant disease management, addressing urgent global challenges including climate change and food security. Her body of work reflects both scientific depth and a strong translational vision, bridging laboratory innovation with real-world agricultural application.
Research Focus
Key Achievements
Top Papers
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- 6Special Issue: Digital Plant Pathology for Precision Agriculture11 citations · 2022
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- 9A Generalized Concept for Clustering Capabilities of Weeding Robots2 citations · 2025
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