スマートフードシステム：食品安全と栄養のための人工知能・ブロックチェーン・デジタル技術に関する批判的レビュー
Smart Food Systems: A Critical Review of Artificial Intelligence, Blockchain, and Digital Technologies for Food Safety and Nutrition (原題)
Toheeb Olaniyi Falakin, J. Omotosho, Sophia Amaka Okoh
🤖 gxceed AI 要約
日本語
AI・ブロックチェーン・IoTを食品安全、トレーサビリティ、栄養管理に応用する研究を批判的にレビューした論文。技術的性能の向上と実際の安全・栄養アウトカムを結びつける証拠は限定的だと指摘する。データ信頼性、相互運用性、コスト、サイバーセキュリティ、デジタル格差などの課題を整理し、6機能からなる統合デジタルインテリジェンス枠組みを提案する。
English
A critical narrative review of AI, blockchain, IoT and related digital technologies across food safety, traceability, quality assurance and nutritional monitoring. It finds applications fragmented and evidence linking technical performance to measurable safety or nutrition outcomes limited, flagging data reliability, interoperability, cost, cybersecurity and equity gaps. The authors propose a six-function Integrated Digital Intelligence Framework (sense, integrate, analyse, verify, act, evaluate) and call for multisite validation and standardised reporting.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
食品トレーサビリティやサプライチェーンのデジタル化は、Scope 3排出量の把握や食品ロス削減とも接続しうるが、本稿は環境・気候開示よりも公衆衛生・栄養に焦点を置く。日本の食品企業・小売のESG対応に直接資する知見は限定的。
In the global GX context
Digital traceability and supply-chain transparency are increasingly relevant to Scope 3 accounting and CSRD/ISSB supply-chain disclosure, but this review centres on food safety and nutrition rather than climate or environmental metrics. It offers a useful caution that digital adoption alone does not equal verified outcomes — a lesson transferable to ESG data assurance debates.
👥 読者別の含意
🔬研究者:AI・ブロックチェーンの食品応用における実証ギャップと評価枠組みの必要性を整理する参考になる。
🏢実務担当者:食品サプライチェーンのデジタル化投資を検討する際、技術導入と成果検証を分けて評価する視点を提供する。
🏛政策担当者:食品安全・栄養政策におけるデジタル技術の標準化と公平なアクセス確保の論点を提示する。
📄 Abstract（原文）
Food safety hazards, persistent nutritional inequalities, and increasingly complex supply chains continue to challenge global food systems. Artificial intelligence (AI), blockchain, the Internet of Things (IoT), and related digital technologies offer new opportunities to strengthen food monitoring, traceability, quality assurance, and nutritional management. However, applications remain fragmented, and evidence linking improved technical performance to measurable food safety and nutritional outcomes is limited. This critical narrative review examines the applications, complementary functions, and practical limitations of these technologies across modern food systems, with particular attention to predictive contamination detection, automated quality assessment, supply chain transparency, nutritional monitoring, and decision support. The review identifies recurring challenges related to data reliability, limited external validation, interoperability, implementation costs, cybersecurity, and unequal access to digital infrastructure. It further distinguishes technological capabilities demonstrated under controlled conditions from sustained improvements in food safety, dietary quality, and public health in operational settings. To address these challenges, the review proposes an Integrated Digital Intelligence Framework organized around six interconnected functions (sense, integrate, analyse, verify, act, and evaluate) that links digital information and predictive intelligence with coordinated interventions, institutional accountability, and outcome evaluation. Priorities for future research include prospective multisite validation, comparative effectiveness studies against conventional systems, standardised reporting, cost-effectiveness analysis, and equity-focused implementation. Meaningful digital transformation of food systems requires moving beyond technological adoption toward integrated, evidence-based approaches that demonstrably improve food safety, nutrition, accessibility, and accountability.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.56557/jafsat/2026/v13i411261first seen 2026-10-29 05:43:04 · last seen 2026-11-05 06:15:01
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