A governance-first framework integrates artificial intelligence and blockchain to advance sustainable and inclusive horticultural value chains

Résumé

Horticultural value chains face persistent agronomic challenges including production inefficiencies, postharvest losses, poor resource management, and limited supply-chain transparency, particularly in smallholder-dominated systems across the Global South. These constraints undermine agricultural productivity, market access, and the long-term sustainability of horticultural farming. Despite growing research interest in digital agriculture, artificial intelligence (AI) and blockchain technology are increasingly explored together, including in emerging integrated AI-blockchain-IoT architectures for agricultural traceability. However, these existing integrations remain predominantly technology-centric, prioritizing traceability, automation, and data verification, without an explicit governance, equity, or data-sovereignty architecture designed specifically for smallholder-dominated horticultural production and distribution systems. This study proposes a comprehensive conceptual framework that integrates AI’s predictive and decision-support capabilities with blockchain’s data integrity, traceability, and automation features to enhance sustainability, inclusivity, and governance in horticultural value chains. Drawing on an integrative review of peer-reviewed sources identified through Scopus, Web of Science, IEEE Xplore, ScienceDirect, and Google Scholar, and grounded in the Technology-Organisation-Environment (TOE) framework, Sociotechnical Systems Theory, and Sustainable Digital Transformation Theory, the study addresses the agronomic, governance, and equity dimensions of digital transformation in horticulture. The framework is structured around five interlinked operational layers, data collection, AI-driven analytics and decision-making, blockchain validation and traceability, smart contracts and decision support, and user interface and stakeholder feedback, all operating within a governance architecture and ethical design layer that functions as a structural precondition for the framework rather than a downstream feature. This governing layer embeds algorithmic transparency, data sovereignty through community-governed data cooperatives, and inclusive digital access for smallholder farmers as non-negotiable design principles. The framework explicitly aligns with Sustainable Development Goals 2, 9, 10, 12, 13, and 16, and includes a three-phase empirical validation pathway comprising expert Delphi elicitation, simulation modeling, and pilot implementation in horticultural cooperatives. The integration of AI and blockchain within an institutionally governed, equity-oriented architecture represents a paradigm shift from technology-first to governance-first digital transformation in horticulture, providing a theoretically robust and practically actionable foundation for future research, systems design, and policy development, with direct application to resource-constrained smallholder systems in sub-Saharan Africa and comparable Global South contexts.

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