Developing sustainable business models using Earth Observation for climate adaptation
Increasing climate-related risks including extreme heat, drought and the high prevalence of pests and diseases puts agricultural and food systems under constant pressure. While new data and technologies, such as Earth Observation (EO), can help predict and prevent threats, it is not readily available. This project aims to close this gap by delivering a multi-service, multi-user platform that supports collaborative data sharing and application. The system will help to meet the challenges of adaptive agriculture, integrating data sets that address the exposure, hazards and vulnerability of individual commodity supply chains to climate-driven risks. CABI is leading on developing sustainable business and governance models, and a maize use case in Kenya that will help to understand user needs and challenges that EO data and analytics can help address.
Generative AI for Agriculture Advisory
Generative Artificial Intelligence (GenAI) technology offers enormous potential by addressing information asymmetries and rapidly advancing research. In the agriculture sector, it can localize digital advisory messages and increase the accessibility of such messages to reduce the digital divide compared to traditional, non-AI communication methods. Using natural language processing (NLP) and large language models (LLMs) offers new potential to disseminate complex scientific information more widely, in local dialects and through various formats, transforming accessibility. This project will explore the potential to deliver advisories based on CABI’s highly curated and expert-validated resources to plant doctors and other agriculture advisors via Generative AI chatbot technology, and the data governance and licensing necessary to ensure the quality of such advisories.
Wheat Blast: Earth observation and climate forecasts for risk management
Wheat Blast (Magnaporthe oryzae Triticum or ‘MOT’) is a plant disease of global concern, threatening crop production and biosecurity. Known to favour humid, warmer climates, the disease is a severe problem in Bangladesh and South America. However, the consequences of climate change pose the risk of the disease infecting other wheat-growing areas. Coupled with its ability to spread rapidly through the air and seeds, Wheat Blast’s devastating effects and limited control options are leading to heavy yield losses and it is now a threat to global food security. This project brings together a project consortium, formed of experts in Earth observation, remote sensing, pest and disease modelling, datasets and information dissemination to produce Wheat Blast risk maps and actionable advice as part of a framework. The framework will be used by key stakeholders as part of a targeted management approach to the disease.
Enabling FAIR data sharing and responsible data use
This project focuses on enabling FAIR data across agricultural development investments by turning principles into practice. CABI supports partners to make data more findable, accessible, interoperable and reusable through measurable FAIR assessments, domain-specific guidance and trusted data access frameworks. By embedding governance into programme design and funding decisions, and clarifying what “AI-ready” data requires, the project strengthens data ecosystems, improving data reuse, reducing duplication and increasing the value of development investments.