Leafy Green Farm-to-Customer Process Model Predicts Product Testing Is Most Effective at Detecting Contamination When Conducted Early in the System before Effective Interventions.

Commercial leafy green supply chains often are required to have test and reject (sampling) plans for specific microbial adulterants at primary production or finished product packing for market access. To better understand the impact of this type of sampling, this study simulated the effect of sampling (from preharvest to consumer) and processing interventions (such as produce wash with antimicrobial chemistry) on the microbial adulterant load reaching the system endpoint (customer). This study simulated seven leafy green systems, an optimal system (all interventions), a suboptimal system (no interventions), and five systems where single interventions were removed to represent single process failures, resulting in 147 total scenarios. The all-interventions scenario resulted in a 3.4 log reduction (95% confidence interval [CI], 3.3 to 3.6) of the total adulterant cells that reached the system endpoint (endpoint TACs). The most effective single interventions were washing, prewashing, and preharvest holding, 1.3 (95% CI, 1.2 to 1.5), 1.3 (95% CI, 1.2 to 1.4), and 0.80 (95% CI, 0.73 to 0.90) log reduction to endpoint TACs, respectively. The factor sensitivity analysis suggests that sampling plans that happen before effective processing interventions (preharvest, harvest, and receiving) were most effective at reducing endpoint TACs, ranging between 0.05 and 0.66 log additional reduction compared to systems with no sampling. In contrast, sampling postprocessing (finished product) did not provide meaningful additional reductions to the endpoint TACs (0 to 0.04 log reduction). The model suggests that sampling used to detect contamination was most effective earlier in the system before effective interventions. Effective interventions reduce undetected contamination levels and prevalence, reducing a sampling plan's ability to detect contamination. This study addresses the industry and academic need to understand the effect of test-and-reject sampling within a farm-to-customer food safety system. The model developed looks at product sampling beyond the preharvest stage by assessing sampling at multiple stages. This study shows that individual interventions and combined interventions substantially reduce the total adulterant cells reaching the system endpoint. When effective interventions occur during processing, sampling at earlier stages (preharvest, harvest, receiving) has more power to detect incoming contamination than postprocessing sampling, as prevalence and contamination levels are lower. This study reiterates that effective food safety interventions are crucial for food safety. When product sampling is used to test and reject a lot as a preventive control, it may detect critically high incoming contamination. However, if contamination levels and prevalence are low, typical sampling plans will fail to detect contamination.