気候レジリエントな食品安全のためのデジタルトランスフォーメーション

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:AI/MLと気候リスク管理の統合事例として、食品サプライチェーンのレジリエンス研究に示唆。

🏢実務担当者:食品安全と気候適応のためのデジタル技術導入の具体的ケーススタディを提供。

🏛政策担当者:規制と産業支援のための行動課題（プライバシー、データ標準、SME向け金融）を提示。

Climate change is reshaping the risk landscape for food safety, intensifying biological and chemical hazards through rising temperatures, extreme weather events, and ecosystem disruptions. This chapter argues that a digital transformation, anchored in Industry 4.0 tools, provides the foundation for climate-resilient food safety. We first synthesise pathways by which climate drivers elevate risks across plant and animal health, mycotoxins and algal toxins, chemical contamination, and loss of food sources. We then detail how AI/ML, IoT sensor networks, remote sensing, big data analytics, and blockchain can strengthen the classical risk-analysis cycle (assessment, management, communication) via continuous monitoring, predictive early warning, and end-to-end traceability. Three case studies illustrate operational value: (1) Bühler's Merlin AI optical sorting to detect climate-induced seed defects and contaminants; (2) AgriDigital's blockchain and smart contracts to stabilise drought-stressed grain supply chains, de-risk payments, and expand access to finance; and (3) Cainiao's IoT-enabled cold-chain control to maintain integrity during heatwaves. Cross-cutting lessons emphasise the benefits of integrating technologies (IoT, AI, and blockchain), embedding interoperable data standards, and coupling predictive analytics with automated responses. We conclude with an action agenda for regulators and industry, including privacy-by-design governance, shared metrics, blended finance for SMEs, and capacity building, to scale resilient, data-driven systems that safeguard public health as climate pressures intensify.

• openalex https://doi.org/10.1002/9781394362660.ch22first seen 2026-08-23 04:38:40