Performance of Visual Inspection, ATP, and Microbial Analysis in Evaluating Cleaning and Sanitizing of Surfaces in an...

Effective cleaning and sanitizing (C&S) of food contact surfaces (FCSs) is critical for minimizing microbial contamination risks in fresh produce environments. This study evaluated the performance of visual inspection, ATP bioluminescence, and microbial analysis as verification tools for C&S procedures in an avocado packing plant, based on surface conditions before and after sanitation. Cleanliness was classified using a four-level visual scale, from 1 (cleanest) to 4 (dirtiest). ATP levels were measured via bioluminescence. Microbial analysis included the quantification of mesophilic aerobic bacteria, Enterobacteriaceae, and yeasts and molds, as well as the qualitative detection of Listeria spp. Surface temperatures ranged from 17 °C to 30.9 °C, and relative humidity from 54.3% to 97.0%. Brushes and receiving crates showed the highest visual scores after C&S; however, receiving crates exhibited minimal improvement compared to pre-C&S levels. ATP levels ranged from 2.6 ± 0.7 to 3.8 ± 1.0 log₁₀ relative light units (RLU)/100 cm², with no significant reductions observed. Microbial counts showed inconsistent decreases, and no surface achieved the expected 3-log reduction. Listeria spp. was detected on 14% and 13% of FCS before and after C&S, respectively. Noncontact surfaces, especially drains, also remained contaminated. Notably, the verification tools often produced contradictory results. In some surfaces, visual inspection and microbial indicators suggested effective C&S, while ATP readings showed no significant change. In others, only visual improvements were detected, with no corroborating reduction in ATP or microbial levels. These inconsistencies underscore the limitations of relying on a single method and highlight the importance of using complementary tools in a sequential verification approach. A decision tree (Fig. 4) is proposed to guide the integration of these tools and improve hygiene monitoring strategies in produce packing environments.