# A Survey of Blockchain Applications for Management in Agriculture and Livestock Internet of Things
## 1 Introduction
These include situations requiring rapid decision-making, unified command, or efficient resource allocation, such as food safety management, disease outbreak control, or government subsidy distribution. For instance, in the management of specific agricultural products subject to strict government oversight, centralized systems may already offer efficient and reliable solutions. Introducing blockchain in such contexts could lead to unnecessary complexity and resource allocation challenges. Future research should focus on delineating the specific conditions under which blockchain technology is either beneficial or redundant in agricultural and livestock systems. 1. Providing a Comprehensive Background for Novices  
Before delving into the latest research findings, this paper systematically introduces the foundational concepts of IoT applications in agriculture and livestock, as well as blockchain technology. In contrast to existing overviews that primarily address either IoT or blockchain in isolation, our approach integrates insights from multiple recent studies to underscore how prior work has laid the groundwork for linking these two domains. This dual overview enables readers--especially those new to the field--to quickly understand how IoT and blockchain function within agricultural and livestock management. Consequently, our work serves as an accessible starting point for researchers aiming to explore these areas in depth. 2. Highlighting the Challenges and Motivations for Integrating Blockchain into Agricultural and Livestock IoT  
We thoroughly examine the current challenges in agricultural and livestock IoT, including data security vulnerabilities, transparency issues, and reliability concerns. Building on the findings from prior research that has identified these pain points in various IoT-driven agri-food supply chains, we correlate them with the inherent attributes of blockchain (such as immutability, decentralized data storage, and trust enhancement). Therefore, we illuminate the motivations and advantages of combining blockchain with IoT in this domain. This explicit linkage to earlier studies clarifies how the recognized blockchain features can address the specific gaps highlighted by previous authors, thereby explaining how blockchain can specifically tackle core pain points of agriculture and livestock management. 3. Presenting a Novel Classification Scheme for Blockchain Applications in Agriculture and Livestock IoT  
Unlike most existing review articles that primarily focus on broad integration or a single aspect (e.g., traceability), we draw upon multiple recent investigations (published within the past 3-5 years) to formulate a more comprehensive classification strategy. Through this in-depth analysis of recent studies, we categorize the applications of blockchain in agricultural and livestock IoT into four key themes--data storage and management, supply chain traceability, smart contract implementation, and security and trust assurance. By consolidating the diverse findings of these studies, we extend the existing classifications and highlight the multifaceted roles of blockchain in meeting the varied requirements of modern agriculture and livestock systems. This approach provides researchers and practitioners with clear directions for future exploration and application. 4. Analyzing Existing Research Gaps and Proposing Future Directions  
Based on our extensive review, we summarize the critical open issues--ranging from regulatory challenges to system scalability--and discuss how they may affect the successful integration of blockchain in agriculture and livestock IoT. By synthesizing the unresolved topics raised in earlier works, such as the lack of standardized protocols or difficulties in large-scale implementation, we propose promising future research paths, including the design of domain-specific consensus mechanisms, the synergy between centralized and decentralized systems, and the potential coupling of AI-driven analytics with blockchain.