Autonomous, AI-driven crop management based on electrophysiological plant signals
The project focuses on the practical development and validation of innovative biosensors and AI software that analyze electrophysiological signals from plants for the early detection of stressors. By enabling direct, real-time feedback from the plant, growers can implement more targeted, efficient, and sustainable cultivation interventions. This contributes to higher yields, reduced resource use, and a future-proof, data-driven agriculture and horticulture sector.
Peelkroon
Zachtfruit Schalkwijk
Medegefinancierd door de Europese Unie
See how crops respond, optimise products and practices, and make more confident decisions, based on plant data, not guesswork.
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