Early warning AI agent for pest, disease, and weed in Viet Nam

This activity aligns strategically with the CGIAR Sustainable Farming Science Program, specifically contributing to Area of Work 4: Plant Health and Mycotoxin Safe Crops. In response to the 2025 implementation plan's mandate for improved high-throughput, cost-effective monitoring tools, this project...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Soonho, Liu, Yanyan
Formato: Informe técnico
Lenguaje:Inglés
Publicado: CGIAR System Organization 2025
Materias:
Acceso en línea:https://hdl.handle.net/10568/179929
Descripción
Sumario:This activity aligns strategically with the CGIAR Sustainable Farming Science Program, specifically contributing to Area of Work 4: Plant Health and Mycotoxin Safe Crops. In response to the 2025 implementation plan's mandate for improved high-throughput, cost-effective monitoring tools, this project addresses a critical surveillance gap in Vietnam’s agricultural sector. Transboundary pests, diseases, and weeds pose significant threats to national food security and export value chains. While traditional physical surveillance methods are accurate, they remain resource-intensive and geographically constrained. Consequently, vital early warning signals, which often surface in local news and digital media prior to official scientific confirmation, are frequently missed, leading to delayed responses. To bridge this intelligence gap, the activity is developing an automated media monitoring tool powered by an AI architecture hosted on the Google Cloud Platform. Utilizing the Google Agent Development Kit and Gemini 2.5 Pro Large Language Models, the system functions as a digital analyst that automates the retrieval and synthesis of biosecurity information via Google Search. A distinguishing feature of this solution is its visual-first, designed to democratize access to complex data. By allowing users to identify threats through high-resolution images rather than requiring knowledge of scientific names, and by enabling conversation in local Vietnamese, the tool will empower a broad spectrum of stakeholders from local extension officers to national partners to access real-time, actionable insights. The foundation of this system is a comprehensive "Target Watchlist" constructed by synthesizing international data from the EPPO Global Database with Vietnam's National Technical Regulation on Phytosanitary Requirements (QCVN 01-192:2020/BNNPTNT). This dataset ensures the monitoring is economically relevant by filtering for pests affecting Vietnam's primary staple, industrial, and export fruit crops. Currently in active development, the project is moving toward a 2026 roadmap that includes rigorous ground-truthing of data with domain specialists and expanding the solution's geographic scope to India. By integrating management intelligence from trusted platforms such as Digital Green, PlantVillage, and Plantix, the agent will evolve from a detection tool into a comprehensive early warning platform for pests, diseases, and weeds.