Shaping the Deep Tech Revolution in Agriculture 2025

2. Climate change and intensifying weather extremes To de-risk agriculture from changing climate patterns and intensifying weather extremes, use cases must enable predictive adaptation, localized risk mitigation and climate-resilient decision-making. Technologies should also support the development and deployment of resilient crop varieties, optimize resource use under stress conditions and enable decentralized, rapid-response mechanisms to climate events at farm and regional levels. Use case 3: Climate-resilient crop varieties Technology convergence CRISPR, AI-guided trait selection, phenotyping platforms Description Climate-resilient crop varieties are genetically enhanced crops designed to withstand environmental stresses and offset the risks of climate change. These stresses can include droughts, pest attacks and other weather-related contingencies. By improving tolerance to climate change while stabilizing or increasing yields, these varieties help stabilize production and food supply, especially in vulnerable regions. Use case 4: Agricultural digital twins Technology convergence Satellite-enabled remote sensing, machine learning, IoTenabled data capture and quantum computing (depending on the complexity of scenario modelling) Description The use case includes the creation of dynamic, data-driven virtual models that mirror real-world agricultural systems. The scope of these models can vary from small farms to entire regions. These twins integrate real-time and historical data with climate models to simulate how crops, soils and ecosystems respond to extreme weather, shifting patterns and management interventions. By simulating scenarios, they can be used to optimize resource usage and plan Infrastructure, enabling long-term adaptive planning. Shaping the Deep-Tech Revolution in Agriculture 28