AI-integrated models for assessing agricultural resilience

2026-07-08

AI Summary

Agricultural supply chains are highly vulnerable to multiple disturbances due to the deep coupling of biophysical and economic systems, necessitating interdisciplinary and interactive assessment tools. This study presents the first integrative framework that deeply fuses the Global Trade Analysis Project (GTAP) economic model with the Agricultural Production Systems sIMulator (APSIM) through artificial intelligence, resulting in an interactive analytical platform supporting natural language queries. The platform substantially enhances cross-domain modeling capabilities, enabling policymakers and market participants to efficiently evaluate the compound impacts of disruptions on agricultural supply chain resilience and coupled socio-economic–ecological systems. By bridging economic and biophysical modeling through AI-driven interactivity, this work offers an innovative intelligent decision-support system for managing complex agricultural systems under uncertainty.

Abstract

Agricultural supply chains are vulnerable to disruptions through linked biophysical and economic systems. We develop an AI-powered tool that integrates economic models (GTAP) with biophysical models (APSIM) to analyze supply chain shocks, enabling policymakers and market participants to assess cross-disciplinary impacts through queries and responses written in natural language.

Problem

• agricultural resilience
• supply chain shocks
• biophysical-economic systems
• AI-integrated models
• cross-disciplinary impacts

Innovation

• AI-integrated modeling
• agricultural resilience
• GTAP-APSIM integration
• natural language interface
• supply chain shock analysis