All Treatment Parameters Affect Environmental Surface Sanitation Efficacy, but Their Relative Importance Depends on the Microbial Target

Abstract

Environmental sanitation in food manufacturing plants promotes food safety and product microbial quality. However, the development of experimental models remains a challenge due to the complex nature of commercial cleaning processes, which include spraying water and sanitizer on equipment and structural surfaces within manufacturing space. Although simple in execution, the physical driving forces are difficult to simulate in a controlled laboratory environment. Here, we present a bench-scale bioreactor system which mimics the flow conditions in environmental sanitation programs. We applied computational fluid dynamic (CFD) simulations to obtain fluid flow parameters that better approximate and predict industrial outcomes. According to the CFD model, the local wall shear stress achieved on the target surface ranged from 0.015 to 5.00 Pa. Sanitation efficacy on six types of environmental surface materials (hydrophobicity, 57.59 to 88.61°; roughness, 2.2 to 11.9 μm) against two different microbial targets, the bacterial pathogen Listeria monocytogenes and Exophiala species spoilage fungi, were evaluated using the bench-scale bioreactor system. The relative reduction ranged from 0.0 to 0.82 for Exophiala spp., which corresponded to a 0.0 to 2.21 log CFU/coupon reduction, and the relative reduction ranged from 0.0 to 0.93 in L. monocytogenes which corresponded to a 0.0 to 6.19 log CFU/coupon reduction. Although most treatment parameters were considered statistically significant against either L. monocytogenes or Exophiala spp., contact time was ranked as the most important predictor for L. monocytogenes reduction. Shear stress contributed the most to Exophiala spp. removal on stainless steel and Buna-N rubber, while contact time was the most important factor on HDPE (high-density polyethylene), cement, and epoxy.IMPORTANCE Commercial food manufacturers commonly employ a single sanitation program that addresses both bacterial pathogen and fungal spoilage microbiota, despite the fact that the two microbial targets respond differently to various environmental sanitation conditions. Comparison of outcome-based clusters of treatment combinations may facilitate the development of compensatory sanitation regimes where longer contact time or greater force are applied so that lower sanitizer concentrations can be used. Determination of microbiological outcomes related to sanitation program efficacy against a panel of treatment conditions allows food processors to balance tradeoffs between quality and safety with cost and waste stream management, as appropriate for their facility.

Keywords: computational fluid dynamics; food safety; sanitation; spoilage.

FIG 1

Surface material characterization and corresponding cell attachment. Surface material, laser micrographs (A, left), and images (A, right), (B) roughness (μm), and (C) hydrophobicity (degree). Initial counts of Listeria monocytogenes (D) and Exophiala spp. (E). Scanning electron microscopy images of a L. monocytogenes monoculture (F), an Exophiala spp. monoculture (G), and coculture on stainless steel coupon with a smooth/2B finish (H). Magnifications: ×10,000 (F and G), ×3,500 (H). The limit of detection is at 0.35 log CFU/coupon (dashed line). *, P < 0.05.

FIG 2

Evaluation of bench-scale sanitation bioreactor treatments. (A) Velocity distribution on the bottom of the vessel at the steady state. Black squares indicate the location of the coupons. White blocks indicate the location of the impeller (obtained from Fan et al. [64]). (B) The wall shear stress distribution along the center line on the bottom plane of the stirring beaker, and the blue bands indicate the location of the sample coupons (obtained from Fan et al. [64]). (C) Absolute survivor counts under the most and least intense treatment levels. Comparison of untreated control coupons (LM_0 and BY_0) and survivors following the least intense (LM– and BY–) treatment combination (0.6 ml/liter sanitizer at 50 rpm for 30 s at 23.9°C) and survivors following the most intense (LM+ and BY+) treatment combination (2.4 ml/liter sanitizer at 900 rpm for 5 min at 23.9°C). LM, L. monocytogenes survivor counts; BY, black yeast (i.e., Exophiala spp.) survivor counts. *, P < 0.05; **, P < 0.01; ***, P < 0.001. The limit of detection is at 0.35 log CFU/coupon (dashed line). (D) Estimated wall shear stress magnitude (Pa) of the stirred vessel from CFD simulations under various temperature and impeller rotational velocity combinations.

FIG 3

Relative reduction (ΔN/N₀ ratio) of L. monocytogenes (A) and Exophiala spp. (B) after sanitation. Columns represent surface material; rows represent treatment combinations.

FIG 4

Change in adjusted R² value when the variable was last added to the four-way interaction L. monocytogenes (A) and Exophiala sp. (B) models on various surfaces.