Peter Kryger Jensen
Papers
1
Total Citations
33
H-Index
1
About
Peter Kryger Jensen is a leading researcher in precision agriculture and weed science, with a primary focus on developing intelligent systems for reducing herbicide use in arable crops. His most-cited work, the "Dicotyledon Weed Quantification Algorithm for Selective Herbicide Application in Maize Crops" (2016, 33 citations), addresses the pressing economic and regulatory challenges posed by EU legislation on herbicide leaching. By leveraging high-resolution imaging, Jensen pioneered a computer vision algorithm capable of accurately quantifying dicotyledonous weeds in real-time, enabling site-specific herbicide application rather than blanket spraying. This contribution directly supports sustainable farming by minimizing chemical runoff and reducing costs for growers. His research bridges agronomy, sensor technology, and machine learning, offering practical solutions for integrated weed management. Jensen’s work has been instrumental in advancing the precision agriculture movement, demonstrating how targeted interventions can maintain crop yields while protecting environmental health. His algorithm remains a foundational reference for researchers developing autonomous weed control systems in maize and other row crops.
Research Focus
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- 1