Project Aims
The project focuses on the development of an AI system for managing NPK and pH levels in hydroponic systems to improve cultivation efficiency and sustainability. It includes the creation of deep learning algorithms for spectral data analysis and the accurate determination of NPK concentrations. A decision tree will be implemented to enable automatic adjustment of NPK and pH levels with over 90% accuracy.
Trials with various crops in substrate-free systems will be conducted to evaluate different fertigation schemes. Real-time monitoring and optimization of key nutrients will support plant growth and help control nitrate nitrogen levels. The project also aims to increase the production of bioactive compounds and antioxidants in specialty vegetable crops.
Crop quality and photosynthetic activity will be analyzed under different spectral LED lighting and fertigation regimes, with the goal of increasing crop yield by 15%. The root zone microbiome and microbial activity will be investigated to identify beneficial strains that enhance nutrient uptake.
The project addresses deficiencies in current nutrient measurement technologies, which are often labor-intensive, error-prone, and require frequent calibration. It envisions the development of a fully automated system for continuous and precise nutrient control using advanced spectroscopy and machine learning. The system is expected to reduce labor and operational costs in nutrient management while enabling efficient real-time monitoring.
Finally, the functionality of the AI system will be demonstrated in hydroponic conditions to ensure the scalability and robustness of the solution.
Coordination
Project coordination will be led by Mendel University. Regular online meetings will take place every four months. Annual in-person consortium meetings are planned for 2025, 2026, and 2027. Additional on-demand meetings will be held for scientific staff and technicians as needed.
Mendel University will be responsible for both midterm and final reporting, as well as for dissemination activities. The university will also design and implement cultivation trials. Hahn-Schickard will lead the technical development, while Kyoto University will ensure crop-related tasks. All consortium members will contribute to publications.
Communication and Dissemination
Scientific publications will be made available on the websites of KUAS, Hahn-Schickard, and Mendel University. Research results will be incorporated into student theses, academic papers, and teaching materials. Public outreach activities will communicate the project’s goals and findings beyond the expert community.
A public event will be held at Mendel University for at least 30 specialists. Open-source data will be shared via public databases where appropriate. KUAS will participate in expos and workshops, particularly during the second and third years of the project.
A final project workshop will take place in Japan during the third year, with 30 participants, including invited researchers. Project outcomes will be summarized in a scientific publications and dissemination report, as well as in a public relations and open-source data report.
Key milestones:
Milestone 1: Completion of Small Test Units.
Milestone 2: Deployment of Sensor Platform and AI System.
Milestone 3: Completion of Cultivation Trials and Data Collection.