An Overview of Blockchain-Enabled Federated Learning Architectures for Agricultural Applications

Blockchain-based federated learning (BCFL) is emerging as a promising solution to these challenges. Unlike traditional machine learning frameworks, including standard federated learning, BCFL offers a secure framework for distributed analysis of agricultural big data while integrating a transparent reward system via smart contracts. The development of smart agriculture requires data analysis methods that preserve privacy while encouraging collaboration among stakeholders. This review analyses studies (2018-2023) to assess how the integration of blockchain in federated learning (BCFL) addresses this dual challenge. Three key findings emerge: (1) 78% of BCFL implementations improve model auditability while maintaining accuracy > 85% (average difference of -9.2% vs. conventional FL); (2) Reward smart contracts reduce participant dropout rates by 40%; and (3) Only 12% of existing frameworks integrate differential privacy (DP) mechanisms. Our analysis reveals key barriers such as scalability (average latency of 2.7 s/transaction) and the heterogeneity of agricultural devices. Identified future directions include the adoption of lightweight blockchains (IOTA) and hybrid FL-DP protocols. This comprehensive review examines the integration of federated learning and blockchain in the agricultural domain. By analysing current trends, technical challenges, and future perspectives, this work aims to establish a framework for decentralized, secure, and privacy-preserving solutions. Unlike traditional approaches, our analysis highlights the potential of this synergy to optimize distributed agricultural data management, strengthen supply chain traceability, and improve decision-making through collaborative AI models. By identifying existing limitations (latency, scalability, interoperability), we pave the way for future research aimed at making these technologies accessible to farms of various sizes, while ensuring transparency and energy efficiency.