Identifying and managing false codling moth in roses in Ethiopia
The horticultural sector is key to Ethiopia’s economy, contributing to foreign exchange revenue and employment. But the rose-cut flower is of significance due to its increasing demand, market growth, and Ethiopia’s ability to dominate production thanks to its favourable conditions. However, the false codling moth, a major pest, is threatening the quality and marketability of rose-cut flowers, jeopardising the growing horticulture industry and Ethiopia’s export markets. And due to its persistent presence, quarantine restrictions are resulting in high costs and lower profits. To address this problem, CABI is seeking to strengthen the capacity of Ethiopian horticulture authorities, associations and member farms to help improve compliance.
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.