Visual inspection of surface sanitation: Defining the conditions that enhance the human threshold for detection of food residues

Daeschel, Devin; Rana, Yadwinder Singh; Chen, Long; Cai, Shiyu; Dando, Robin; Snyder, Abigail B.

doi:10.1016/j.foodcont.2023.109691

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…However, after a 2 log CFU contamination breach, dry wiping still resulted in a 64% reduction in the number of contaminated units, which could be meaningful in reducing downstream human exposure to Salmonella. Mechanical dry cleaning methods such as wiping, brushing, and scraping generally offer limited removal of microbial contamination, but can produce visibly clean surfaces [47] that pass ATP tests [48]. As such they are not currently recognized as a validated sanitation method [12], though they are still important sanitation activities for maintaining a hygienic dry processing environment.…”

Section: Dry Wiping With a Towel Modestly Reduced The Prevalence And ...mentioning

confidence: 99%

A Simulation Model to Quantify the Efficacy of Dry Cleaning Interventions on a Contaminated Milk Powder Line

Daeschel,

Chen,

Zoellner

et al. 2024

Preprint

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Outbreaks ofSalmonellaand other pathogens associated with low moisture foods have been caused by cross-contamination from the processing environment into product. We used Monte Carlo simulations to model the impact of hypothetical cross-contamination scenarios ofSalmonellafrom production equipment into milk powder. Model outputs include the quantity and extent of contaminated product from a production line, which can be useful for comparing the efficacy of different cleaning interventions. We also modeled the cross-contamination of potential dry cleaning surrogates to see how they responded to cleaning interventions in comparison toSalmonella. Input parameters for the model included log reductions from wiping an inoculated surface with a dry towel and transfer coefficients from an inoculated surface into milk powder that were measured experimentally and fitted to probability distributions. After a 2 log CFU contamination breach, the number of consumer size milk powder units (300 g) contaminated withSalmonellawas 72 [24, 96] (median [p5, p95] across 1000 simulation iterations). The average concentration ofSalmonellawithin contaminated units was -2.33 log CFU/g [-2.46, -1.86]. Wiping with a dry towel reduced the number of contaminated units to 26 [12, 64]. After product flushing with 150 kg of milk powder, the number of contaminated units dropped to 0 [0, 41].E. faeciumwas the most appropriate surrogate forSalmonellatransfer from surface to milk powder, whileL. innocuawas a more appropriate surrogate for the dry towel wiping intervention. These results suggest that product flushing, and to a lesser degree dry wiping, may be effective interventions in reducing contaminated milk powder product after a contamination breach. Further, simulation modeling is a useful tool for evaluatingSalmonelladry transfer surrogates for their use in dry cleaning validation and modeling applications.IMPORTANCEThis work demonstrates the utility ofin silicomodeling as a decision support tool that can 1) estimate the cross-contamination ofSalmonellainto milk powder under different processing scenarios, 2) compare the efficacy of different cleaning interventions and 3) help inform surrogate selection for the dry transfer ofSalmonellain modeling and cleaning validation applications. The model presented here contributes to the risk-benefit analysis of tradeoffs associated with dry cleaning in low moisture food environments. For example, the model can be applied to estimate the efficacy of cleaning interventions like product flushing at a lower resource cost than experimental trials in a processing line. The model presented here also provides a more interpretable metric for choosing appropriateSalmonellasurrogates for dry cleaning validation.

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Section: Dry Wiping With a Towel Modestly Reduced The Prevalence And ...mentioning

confidence: 99%

A Simulation Model to Quantify the Efficacy of Dry Cleaning Interventions on a Contaminated Milk Powder Line

Daeschel,

Chen,

Zoellner

et al. 2024

Preprint

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“…Moreover, depending on the product, the inspection process might include pure visual inspection, another sensorial inspection such as tactile inspection, or a combination. Evidence from various industries suggested that a combination of visual and tactile inspection improved respondent detection [82,85].…”

Section: Human Inspectionmentioning

confidence: 99%

An Assessment of Human Inspection and Deep Learning for Defect Identification in Floral Wreaths

Caballero-Ramirez,

Baez-Lopez,

Limon-Romero

et al. 2023

Horticulturae

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Quality assurance through visual inspection plays a pivotal role in agriculture. In recent years, deep learning techniques (DL) have demonstrated promising results in object recognition. Despite this progress, few studies have focused on assessing human visual inspection and DL for defect identification. This study aims to evaluate visual human inspection and the suitability of using DL for defect identification in products of the floriculture industry. We used a sample of defective and correct decorative wreaths to conduct an attribute agreement analysis between inspectors and quality standards. Additionally, we computed the precision, accuracy, and Kappa statistics. For the DL approach, a dataset of wreath images was curated for training and testing the performance of YOLOv4-tiny, YOLOv5, YOLOv8, and ResNet50 models for defect identification. When assessing five classes, inspectors showed an overall precision of 92.4% and an accuracy of 97%, just below the precision of 93.8% obtained using YOLOv8 and YOLOv5 with accuracies of 99.9% and 99.8%, respectively. With a Kappa value of 0.941, our findings reveal an adequate agreement between inspectors and the standard. The results evidence that the models presented a similar performance to humans in terms of precision and accuracy, highlighting the suitability of DL in assisting humans with defect identification in artisanal-made products from floriculture. Therefore, by assisting humans with digital technologies, organizations can embrace the full potential of Industry 4.0, making the inspection process more intelligent and reliable.

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Multi-length Scale Approach to Investigate Cleaning of Food-Derived Deposits Adhered to Hard Surfaces: Mixtures of Starch, Whey Protein, and Lard

Sáenz-Espinar,

Arroyo-Camarena,

Vicaria

et al. 2024

Food Bioprocess Technol

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Fouling, the accumulation of undesirable material on manufacturing equipment surfaces, poses a pervasive challenge in industrial processes. In the food industry, the complex interactions among these compounds can give rise to stubborn deposits that deviate from conventional cleaning protocols. In this work, the forces and removal mechanisms of model fouling agents composed of mixtures of starch, whey protein, and lard deposited on solid surfaces of relevant industrial interest (i.e. stainless steel, aluminium, and PTFE) are investigated using a multi-length scale approach, involving milli-manipulation and a lab-simulated Clean-In-Place (CIP) system. The forces involved in the removal process, the types of failure observed when the deposits are subjected to shear stress (adhesive, mixed, or cohesive), and the performance of the CIP system are systematically analysed as a function of the cleaning treatments applied. For stainless steel surfaces, alkaline treatment seems to facilitate the cleaning of lard and starch deposits, while the whey foulant removal tends to be more effective using hot water under the conditions tested. Hot water is effective for stainless steel and PTFE surfaces, reducing the mechanical shear stress required, while the alkaline treatment demonstrated superior efficacy for aluminium surfaces. These findings emphasise the importance of customising cleaning protocols for CIP optimisation.

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Visual inspection of surface sanitation: Defining the conditions that enhance the human threshold for detection of food residues

Cited by 4 publications

References 24 publications

A Simulation Model to Quantify the Efficacy of Dry Cleaning Interventions on a Contaminated Milk Powder Line

A Simulation Model to Quantify the Efficacy of Dry Cleaning Interventions on a Contaminated Milk Powder Line

An Assessment of Human Inspection and Deep Learning for Defect Identification in Floral Wreaths

Multi-length Scale Approach to Investigate Cleaning of Food-Derived Deposits Adhered to Hard Surfaces: Mixtures of Starch, Whey Protein, and Lard

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