Development of a standards-based traceability system for the U.S. grain and feed supply chain

Traceability in the U.S. grain and feed supply chain is complicated by commingling and re-division of grain lots across the supply chain. Present traceability practices support the regulatory “one step forward, one step backward” approach, but fails to identify the multiple interactions among farmer, elevator, processor, end-user, and consumer. Several regulatory agencies in the United States and worldwide have set rules and requirements for the implementation of traceability in the food supply chain. This dissertation used a template-method approach to develop guidance templates for facilitating traceability objectives throughout the grain supply chain. Also, a glossary of terminology related to traceability in the grain supply chain was developed to create a standardized understanding among grain traceability participants. Next, a system design modeling approach was used to simplify multiple networks in a grain supply chain example that identifies critical traceability events and key data elements for achieving one or more traceability objectives. The model uses ArgoUML, which is web-based unified modeling software that models informational elements (or attributes) in a way that can be easily converted to software programs. Finally, the vulnerability of the traceability system was evaluated determining how and when the traceability of a grain supply chain system gets affected. A vulnerability analysis model identifies, quantifies, and prioritizes various factors responsible for reducing the efficacy of a system. Vulnerability analysis measures system attributes (data) related to (i) frequency of occurrence; (ii) degree of impact of occurrence; and (iii) likelihood of detection. The vulnerability method can be used as a standard method for evaluating how and when traceability would fail and such an analysis would highlight processes that may compromise traceability in a bulk grain supply chain