The horticulture industry continuously seeks innovative solutions to enhance crop yield, quality, and predictability. In January 2024, Koidra, a supplier of intelligent automation, and Delphy, a global consultancy and research specialist in horticulture, explored the combination of their hierarchical and autonomous decision-making models to improve the management of high-tech cucumber cultivation under LED lights.
The trial utilized Delphy's Quality Management System (QMS) to set daily targets (such as DLI and 24-hour temperature) and Priva's Connext for actuator adjustments. The latter half of the trial integrated Koidra's KoPilot technology to automate environmental control decisions every five minutes, thus creating a seamlessly integrated, autonomous system.
According to Linda Nooren, a researcher at Delphy Improvement Centre, "The collaboration between Delphy, Priva's Connext, and Koidra enabled full-automated control of the greenhouse climate, light, and irrigation. We had valuable discussions about the climate, usage, and differences with practice between crop advisors, growers, suppliers, and Koidra."
Unfortunately, the crop had a difficult start due to late planting. However, following the integration of Koidra's autonomous growing controls, the crop developed positively, resulting in consistent weekly production, good fruit filling, and excellent average weight from that period onwards. The cucumber production in the period of Koidra's autonomous growing is almost equivalent to the predictions based on Delphy's QMS.
Methodology
The trial was structured around a three-tier decision-making model. Firstly around Delphy's Quality Management System (QMS) - Provided weekly recommendations for daily targets, focusing on long-term growth strategies. Secondly, around Koidra's KoPilot - Adjusted environmental control setpoints in real-time (every 5 minutes) to optimize conditions based on QMS recommendations and ongoing environmental feedback. And lastly, around Priva's Connext - Executed the actuator adjustments determined by KoPilot.
Overall Results
The integration of these systems demonstrated robust performance and reliability, ensuring seamless communication between the software layers. The system proactively managed environmental conditions to eliminate water condensation on leaves, thus preventing diseases such as mildew, a common challenge in cucumber cultivation.
"The success of this trial underscores the importance of integrated decision-making systems in greenhouse agriculture. Koidra's KoPilot effectively utilized the strategic insights from Delphy's QMS and the control capabilities from Priva's Connext to drive superior crop production and predictability by optimizing real-time adjustments to the growing environment. Together we explored and built effective feedback systems to improve the control performance," Linda Nooren highlighted.
Implications for future agricultural practices
Increasing crop production and prediction capabilities is key to maximizing the value of greenhouse production, especially given the rising variability in external climate conditions negatively impacting crop growth. The results suggest that similar integrative approaches could be effectively applied to other crops and growing conditions, paving the way for more widespread adoption of intelligent automation in agriculture.
Conclusion
This trial marks a significant achievement in greenhouse horticulture, showcasing the benefits of hierarchical decision-making models. The collaboration between Koidra, Delphy, and Priva not only led to good crop performance but also highlighted the importance of synergy between high-level decision-making tools and precise operational control systems. As we continue to refine these technologies, the potential for optimizing agricultural productivity and sustainability becomes increasingly attainable.
For more information:
Koidra
[email protected]
www.koidra.ai
Priva
[email protected]
www.priva.com
Delphy