Reducing product nonconformity through QMRA: A risk-based management approach for Listeria monocytogenes in a Taiwanese alfalfa sprout supply chain

Abstract

This study used a quantitative microbial risk assessment framework and developed a risk-based management approach aimed at reducing product nonconformity. The applicability of this approach was demonstrated in a case study of a Taiwanese alfalfa sprout supply chain, focusing on Listeria monocytogenes control. Primary data on cross-contamination rates and time-temperature profiles were obtained. Initial bacterial counts, prevalence, and growth models were derived from secondary data. Cross-contamination experiments indicated that rates of microbial transfer were 0.72 %-12.77 % from sprouts to contact surfaces and were 31.31 %-63.44 % from contact surfaces to sprouts. At baseline, the nonconformity rate (likelihood of exceeding 100 colony-forming units/g) was 1.74 x 10(-3) per package of sprouts. Sensitivity analysis indicated that the top three factors influencing this rate were, in order of importance, transportation temperature, initial bacterial count, and storage temperature. Best-case scenario analysis revealed that combined control measures-for example, maintaining temperatures at <= 7 degrees C during storage and transportation and reducing initial contamination (e.g., through supplier verification and seed decontamination) to <0.5 log colony-forming units/g-minimized the nonconformity rate to a negligible level. Our findings may aid food safety managers in developing data-driven, risk-based management systems to effectively control microbial hazards and improve product safety and quality.