Background

The cultivation of high-quality medicinal plants is essential for developing new treatments and healthcare products. However, acquiring such plants comes with significant challenges for European companies, mainly because they are dependent on international supply chains. These supply chains are vulnerable to geopolitical, economic, and environmental disruptions. Vertical farming may be part of the solution. It offers a promising approach becoming more resilient and gaining greater independence from international suppliers.

Project Content & Aims

Despite its potential, vertical farming has yet to be widely adopted. The main reason for being underrepresented in European agriculture are high initial investment costs, which constitute a particularly significant hurdle for small and medium-sized enterprises (SMEs). The lack of established best practices and insufficient collaboration among producers, universities, and regulators only add to the problem. The Sapphire initiative aims to tackle these challenges. It proposes a collaborative framework to improve the performance of scalable vertical farming units. The project’s focus is on the needs of farmers and SMEs in the medicinal plant sector.

The Sapphire initiative aims to use deep learning (DL) techniques to analyse cultivation data and optimize critical growth parameters, supporting precise and reliable production. The solution is designed to be adaptable, allowing different clients to tailor their operations to their individual needs. The project’s primary objectives are:

• Develop a scalable franchise for industrial medicinal plant cultivation and
• establish a framework for federated learning (i.e., machine learning in which data stays with the individual providers rather than being centralized) and data altruism (i.e., data is voluntarily shared among different providers for mutual benefit). This framework aims to drive innovation while complying with relevant regulations.

Methods

Smart Plant Monitoring: Advanced sensors and imaging systems continuously track plant health, growth, and environmental conditions, providing real-time insights into crop performance.

AI-Powered Growth Prediction & Optimization: Artificial intelligence analyses plant and environmental data to predict growth outcomes, optimize cultivation strategies, and support better decision-making throughout the cultivation process.

Secure Federated Learning Network: Production sites collaborate by sharing AI model improvements instead of raw data. This ensures data privacy while enabling collective learning and continuous model improvement.

Sustainable Solution: Data-driven optimisation helps improve water, energy, and fertiliser efficiency.

Scalable: The platform can be adapted to different crops and farming setups and scaled up for future expansion.

Validated in Real Farming Environments: The technology is tested and refined in operational vertical farms to demonstrate its practical applicability and make its benefits tangible to participants before large-scale deployment.

Partners

Funding