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
The generation, collection, storage, use and sharing of data can be time-consuming and expensive. Often, effort is duplicated, or the potential value of data is lost because the data cannot be found, accessed, used, or reused. Not all the Bill & Melinda Gates Foundation’s data-rich work has met its potential because data has not been shared or assets have not been used in new contexts. The foundation is committed to unlocking the full value of data in agriculture and food systems through open and interoperable data ecosystems. In this project, CABI will address constraints in realizing the value of data in the foundation’s investments by increasing the capacity and capability of Program Officers, grantees and national systems to initiate and manage change processes towards FAIR (findable, accessible, interoperable and reusable) and responsible data management.