Development of a Blockchain-Based System for Livestock Traceability and Certification

Thesis Abstract

The integrity and transparency of livestock traceability and certification systems remain critical challenges in the modern animal production sector, particularly amid increasing concerns over food safety, disease management, and fraud prevention. Current manual and paper-based systems often suffer from inaccuracies, inefficiencies, and vulnerabilities to fraud, which undermine consumer trust and hinder regulatory enforcement. This study aims to develop a secure, decentralized, and transparent blockchain-based system to enhance livestock traceability and certification processes. The specific objectives include designing a blockchain architecture tailored for livestock data management, developing a prototype application, evaluating its usability and reliability, and assessing its impact on stakeholders’ confidence in certification authenticity. A mixed-methods research design was employed, integrating qualitative and quantitative approaches. The quantitative component involved a survey of 300 livestock farmers, veterinary officers, and certification bodies across a geographically defined region, selected through stratified random sampling to ensure diverse representation. The qualitative component comprised focus group discussions and semi-structured interviews with key stakeholders to gather insights into existing challenges and expectations. Data collection instruments included structured questionnaires, interview guides, and system usability questionnaires, all validated through expert review and pilot testing to ensure content validity and reliability, with Cronbach’s alpha coefficients exceeding 0. Eight mathematical models and analytical frameworks were applied in the study, notably descriptive statistics, thematic analysis for qualitative data, and blockchain performance metrics such as transaction throughput and security assessments. Key findings are anticipated to demonstrate that the proposed blockchain system significantly improves traceability accuracy, reduces processing times, and enhances stakeholder confidence compared to traditional systems. Specifically, blockchain’s inherent features—immutability, transparency, and decentralization—are expected to address current vulnerabilities, leading to a measurable increase in certification authenticity and traceability auditability. The system is projected to achieve a transaction throughput of over 200 transactions per second while maintaining high data security standards, verified through security analysis using cryptographic techniques. This research contributes to knowledge by providing a comprehensive framework for integrating blockchain technology into livestock management systems, extending existing literature on digital traceability solutions in agriculture. The study advances the theoretical understanding of technology adoption in livestock certification by applying the Unified Theory of Acceptance and Use of Technology (UTAUT) model and Diffusion of Innovations theory to evaluate stakeholder acceptance and behavior change mechanisms. Furthermore, the research highlights best practices for designing user-centric blockchain applications tailored for rural contexts, emphasizing scalability, usability, and cost-effectiveness. The study concludes that blockchain technology holds significant promise for transforming livestock certification processes, improving transparency, reducing fraud, and fostering greater consumer confidence. Recommendations include deploying the prototype across larger geographical areas, integrating smart contract capabilities to automate certification processes, and conducting longitudinal studies to evaluate long-term impacts on supply chain integrity. The findings are intended to inform policymakers, technology developers, and livestock industry stakeholders about the feasibility and benefits of adopting blockchain solutions for sustainable livestock management. Future research should explore blockchain interoperability with existing agro-food systems and investigate socio-economic effects of digital transformation in rural livestock economies.