Shaping the Deep Tech Revolution in Agriculture 2025

The seasonality of agricultural production critically limits year- round research and development, hindering innovation. To address this, the University of Florida Institute of Food and Agricultural Sciences has developed digital twins.24 The university created a virtual replica of a strawberry field that details every row, leaf and berry. This digital twin enables continuous simulation of strawberry growth, effectively overcoming real-world seasonal constraints. Such a simulation will allow the training of AI models for robotics on synthetic images generated by the digital twin, eliminating the need for expensive and time-consuming real-world data collection. AI tools trained on such digital twins achieved 92% accuracy in fruit detection, and estimated fruit diameter with only 1.2 millimetres of error, which is sufficient for commercial grading. This approach can significantly speed up innovation, encouraging the development of complementary use cases.CASE STUDY 7 Digital twins for training AI models – University of Florida Climate change is the greatest threat to global food security, and the Centre for Nature and Climate plays a vital role in helping the world manage these risks. We continuously track and champion innovations that can accelerate this mission. Today, it is encouraging to see how deep tech is reshaping possibilities and accelerating climate action. For instance, we are seeing examples where AI is being used to forecast weather extremes, remote sensing to monitor crop stress, IoT to optimize water use, and biotechnology to build resilience. By equipping agriculture with these tools, we can safeguard harvests, secure livelihoods and restore ecosystems for generations to come. Sebastian Buckup, Managing Director, Centre for Nature and Climate Use case 5: Controlled environment cultivation Technology convergence Machine learning, edge IoT systems; can also be converged with renewable energy systems to improve their environmental performance Description Includes systems such as greenhouses, vertical farms and net houses that create optimized microclimates for crop production, insulating agriculture from erratic rainfall, temperature fluctuations and extreme weather events. These systems allow precise control over variables such as humidity, light and temperature, thereby stabilizing and increasing yields and enabling year-round production. They also allow production near consumption centres, reducing logistics emissions and losses. Shaping the Deep-Tech Revolution in Agriculture 29