Food safety | Stasiewicz Food Safety Laboratory | Vision: A world where everyone, everywhere is food secure

Salmonellosis Risk Assessment for Comminuted Turkey under Different Specificities of Concentration-based and Virulence-based Final Product Standards

Highlights

More specifically targeting products with risky contamination is efficient
Concentration- and virulence-based standards capture more risk in less products
Genomic clustering more efficiently than serotype identifies risky contamination

Abstract

Prevalence-based performance standards have guided Salmonella control in poultry industry, but concentration- and virulence-based final product standards could target the most risky contamination more specifically. We adapted our previous risk assessment for chicken parts to comminuted turkey to assess the risk in products implicated by different final product standards, incorporating assumptions from FSIS 2024 risk assessments. We simulated the attributable fraction of illnesses from products contaminated over three level thresholds (0.0031 CFU/g, 1 CFU/g, and 10 CFU/g) and/or containing a serotype in three lists (“Top 3 most prevalent higher-virulence serotypes”, “All higher-virulence serotypes”, and “Higher-virulence proportion of each serotype”). Results showed that 87% of illnesses were attributed to the 0.56% of products with Salmonella exceeding 10 CFU/g. Under more specific criteria of level “AND” serotype, 60% of illnesses were attributed to the 0.14% of products contaminated with Salmonella exceeding 10 CFU/g and one of the three most prevalent higher-virulence serotypes. Further, applying genomic-based clustering information, 75% of illnesses were attributed to slightly more products (0.19%) containing Salmonella exceeding 10 CFU/g and higher-virulence proportion of each serotype. Under the less specific standard, however, 99% of illnesses were attributed to the 5.7% of products containing Salmonella exceeding 10 CFU/g “OR” one of the three most prevalent higher-virulence serotypes. Our study demonstrated that most salmonellosis risk is concentrated in comminuted turkey products with high levels of higher-virulence contaminations. Importantly, more specifically targeting those products could efficiently reduce public health risk while minimizing products implicated.

DOI

https://doi.org/10.1016/j.mran.2025.100359

Distillation as an alternative use for deoxynivalenol-contaminated wheat or rye: minimal carryover of deoxynivalenol into distilled spirits

Abstract

Managing deoxynivalenol (DON) risks is crucial for the sustainability of small grain farms. One approach involves profitable utilization of contaminated grain resources, addressing potential losses from food safety concerns. This study explored distillation as a high-value alternative for utilizing DON-contaminated grain. Naturally DON-contaminated rye and wheat were used in two pilot-scale distillation runs involving milling, mashing, fermentation, and distillation. The ground grain, slurry, fermented mash, and post-distillation mash were sampled during process. For the distilled spirit, 29 fractionated samples, each containing 125 ml, were collected starting with the first drop of liquor. The fractionated samples were sequentially combined into 6 pooled samples of up to 5 individual fractions. If a pooled sample had a DON level above the lower limit of quantification, samples of the pool were tested individually. All distillate samples were tested by ELISA with a limit of quantification at 0.05 µg/ml and a limit of detection at 0.01 µg/ml. For both rye and wheat runs, DON levels in all distillate fractions were consistently below 1 µg/ml, reducing from barely quantifiable to below 0.01 µg/ml. The DON levels in ground rye and wheat were 3.62 and 2.69 µg/g, respectively. In the rye distilled spirit, the first pooled sample had a DON level of 0.1 µg/ml, and the first two fractions of that pool had DON levels of 0.1 and 0.06 µg/ml. In the wheat distilled spirit, the first pooled sample had a DON level of 0.05 µg/ml, and the first fraction of that pool had DON level of 0.12 µg/ml. All other distilled spirits had DON levels below 0.01 µg/ml. The results showed that distilled liquor from DON-contaminated rye and wheat contains very low DON levels at most. From a food safety perspective, considering DON-contaminated grain as an ingredient for distilled spirits appears viable.

DOI

https://doi.org/10.1080/19440049.2024.2447063

Risk Assessment Predicts Most of the Salmonellosis Risk in Raw Chicken Parts is Concentrated in Those Few Products with High Levels of High-Virulence Serotypes of Salmonella

Summary of collected USDA-FSIS publicly available datasets used in this project to characterize Salmonella contamination in chicken parts by presence, level, and serotype

Highlights

Chicken parts are rarely contaminated with high Salmonella levels, above 1 CFU/g.
High-virulence serotypes are frequently found in US chicken parts.
Most salmonellosis risk is concentrated in chicken part products above 1 CFU/g.
Most salmonellosis risk is in products with high levels of high-virulence serotypes.

Abstract

Salmonella prevalence declined in U.S. raw poultry products since adopting prevalence-based Salmonella performance standards, but human illnesses did not reduce proportionally. We used Quantitative Microbial Risk Assessment (QMRA) to evaluate public health risks of raw chicken parts contaminated with different levels of all Salmonella and specific high- and low-virulence serotypes. Lognormal Salmonella level distributions were fitted to 2012 USDA-FSIS Baseline parts survey and 2023 USDA-FSIS HACCP verification sampling data. Three different Dose-Response (DR) approaches included (i) a single DR for all serotypes, (ii) DR that reduces Salmonella Kentucky ST152 virulence, and (iii) multiple serotype-specific DR models. All scenarios found risk concentrated in the few products with high Salmonella levels. Using a single DR model with Baseline data (μ = -3.19, σ = 1.29 Log CFU/g), 68% and 37% of illnesses were attributed to the 0.7% and 0.06% of products with >1 and >10 CFU/g Salmonella, respectively. Using distributions from 2023 HACCP data (μ = -5.53, σ = 2.45), 99.8% and 99.0% of illnesses were attributed to the 1.3% and 0.4% of products with >1 and >10 CFU/g Salmonella, respectively. Scenarios with serotype-specific DR models showed more concentrated risk at higher levels. Baseline data showed 92% and 67% and HACCP data showed >99.99% and 99.96% of illnesses attributed to products with >1 and >10 CFU/g Salmonella, respectively. Regarding serotypes using Baseline or HACCP input data, 0.002% and 0.1% of illnesses were attributed to the 0.2% and 0.4% of products with >1 CFU/g of Kentucky ST152, respectively, while 69% and 83% of illnesses were attributed to the 0.3% and 0.6% of products with >1 CFU/g of Enteritidis, Infantis, or Typhimurium, respectively. Therefore, public health risk in chicken parts is concentrated in finished products with high levels and specifically high levels of high-virulence serotypes. Low-virulence serotypes like Kentucky contribute few human cases.

DOI

https://doi.org/10.1016/j.jfp.2024.100304

Simulation Evaluation of Power of Sampling Plans to Detect Cronobacter in Powdered Infant Formula Production

Highlights

Sampling by Codex guidelines detects Cronobacter in a recalled PIF batch profile.
Sampling would not reliably detect Cronobacter in a non-recalled batch profile.
Sampling PIF with stratification is potentially more powerful than random sampling.
Taking more samples, even if smaller, increases the power to detect contamination.

Abstract

Cronobacter is a hazard in Powdered Infant Formula (PIF) products that is hard to detect due to localized and low-level contamination. We adapted a previously published sampling simulation to PIF sampling and benchmarked industry-relevant sampling plans across different numbers of grabs, total sample mass, and sampling patterns. We evaluated performance to detect published Cronobacter contamination profiles for a recalled PIF batch [42% prevalence, −1.8 ± 0.7 log(CFU/g)] and a reference, nonrecalled, PIF batch [1% prevalence, −2.4 ± 0.8 log(CFU/g)]. Simulating a range of numbers of grabs [n = 1–22,000 (representing testing every finished package)] with 300 g total composite mass showed that taking 30 or more grabs detected contamination reliably (<1% median probability to accept the recalled batch). Benchmarking representative sampling plans ([n = 30, mass grab = 10g], [n = 30, m = 25g], [n = 60, m = 25g], [n = 180, m = 25g]) showed that all plans would reject the recalled batch (<1% median probability to accept) but would rarely reject the reference batch (>50% median probability of acceptance, all plans). Overall, (i) systematic or stratified random sampling patterns are equal to or more powerful than random sampling of the same sample size and total sampled mass, and, (ii) taking more samples, even if smaller, can increase the power to detect contamination.

DOI

https://doi.org/10.1016/j.jfp.2023.100115

Spectral kernel sorting based on high-risk visual features associated with mycotoxin contamination reduces aflatoxin and fumonisin contamination in maize from Ghana

Comparison between the previous study (left) that first used this single-kernel optical sorter for mycotoxin remediation (Stasiewicz et al., 2017), and this study (right) which adapted that process to sorting based on rejection of kernels with high-risk features associated with mycotoxin contamination.

Highlights

Visual features associated with mycotoxin risk were used to train a multispectral sorter.
Multispectral sorting reduced aflatoxin and fumonisin levels in maize form Ghana.
Sorting removed about half the total aflatoxin mass, most of the fumonisin mass, and less than one quarter of the maize.

Abstract

Rapid single kernel analysis could enable physical sorting to remove mycotoxins from bulk grains. The purpose of this study was to use visual characteristics previously associated with aflatoxin and fumonisin contamination of maize kernels to calibrate a multi-spectral sorter and then sort mycotoxin contaminated lots. A total of 76 corn samples were collected from poultry farmers in the Dorma-Ahenkro area, Ghana. Paired 400-g subsamples were used for bulk analysis and single kernel sorting. Individual kernels were selected from contaminated samples by 2 levels of stratification: visible high-risk kernels (n = 1000) and visible low risk kernels (n = 1000). High-risk kernels had one or more of 3 features: fluorescence under UV (366 nm) light, mold, or brokenness. Kernels were used to calibrate a multi-spectral sorter (individual wavelengths from 470 to 1070 nm) to remove high-risk kernels. Then, kernel samples were sorted and the reject and accept streams individually ground and tested for aflatoxin and fumonisin contamination using ELISA. Bulk sample levels ranged between 0.78 and 67 ppb aflatoxin and <2.5 × 10⁻³ – 5.7 ppm fumonisin. Classification algorithms to reject visible high-risk spectra were 63% sensitive and 90% specific. After sorting, samples showed a significant aflatoxin reduction (p < 0.001, 73/76 samples reduced, mean reduction 31 ppb, range −9.7 – 67 ppb); all samples showed a significant fumonisin reduction (p < 0.001, mean reduction 1.9 ppm, range 9.3 × 10⁻² – 6.1 ppm). From the accepted stream, 61/76 samples tested <15 ppb aflatoxin, significantly more than the 40/76 prior to sorting (p < 0.001); all accepted samples tested <2 ppm fumonisin concentration compared to only 2/76 prior to sorting. From sorting, average mass rejected was 12% (range 1.2%–36%), and that rejected mass contained an average of 46% of the total aflatoxin (range 4.3%–97%) and 88% of the total fumonisin (range 10%–84%). Visual characteristics associated with mycotoxin contamination can inform classification models which can enable sorting contaminated maize to reduce aflatoxin and fumonisin contamination.

DOI

https://doi.org/10.1016/j.foodcont.2023.109788

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

The scope of the scenarios included. Three contamination patterns, seven systems, and seven sampling plans. Each was evaluated individually to predict the sampling plan power and the effect on total adulterant cells (TACs) that could reach the system endpoint.

Abstract

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.

DOI

https://doi.org/10.1128/aem.00347-23

A Validated Preharvest Sampling Simulation Shows that Sampling Plans with a Larger Number of Randomly Located Samples Perform Better than Typical Sampling Plans in Detecting Representative Point-Source and Widespread Hazards in Leafy Green Fields

Abstract

Commercial leafy greens customers often require a negative preharvest pathogen test, typically by compositing 60 produce sample grabs of 150 to 375 g total mass from lots of various acreages. This study developed a preharvest sampling Monte Carlo simulation, validated it against literature and experimental trials, and used it to suggest improvements to sampling plans. The simulation was validated by outputting six simulated ranges of positive samples that contained the experimental number of positive samples (range, 2 to 139 positives) recovered from six field trials with point source, systematic, and sporadic contamination. We then evaluated the relative performance between simple random, stratified random, or systematic sampling in a 1-acre field to detect point sources of contamination present at 0.3% to 1.7% prevalence. Randomized sampling was optimal because of lower variability in probability of acceptance. Optimized sampling was applied to detect an industry-relevant point source [3 log(CFU/g) over 0.3% of the field] and widespread contamination [−1 to −4 log(CFU/g) over the whole field] by taking 60 to 1,200 sample grabs of 3 g. More samples increased the power of detecting point source contamination, as the median probability of acceptance decreased from 85% with 60 samples to 5% with 1,200 samples. Sampling plans with larger total composite sample mass increased power to detect low-level, widespread contamination, as the median probability of acceptance with −3 log(CFU/g) contamination decreased from 85% with a 150-g total mass to 30% with a 1,200-g total mass. Therefore, preharvest sampling power increases by taking more, smaller samples with randomization, up to the constraints of total grabs and mass feasible or required for a food safety objective.

DOI

https://doi.org/10.1128/aem.01015-22

Perspective: Challenges with product testing in powdered infant formula

Abstract

Right now, many concerned parents are probably thinking, how could Cronobacter sakazakii get through the powdered infant formula (PIF) production system? Shouldn’t a food safety monitoring system find such a serious problem? Aren’t those products tested before arriving on shelves? And the very challenging answer is yes, these products were likely tested with a standardized sampling and testing method consistent with regulatory guidance. In fact, in an official statement, the company said all finished products are tested for Salmonella spp. and Cronobacter sakazakii before they are released, and the product samples the company retained tested negative for the implicated microorganism related to the complaints (Abbott, 2022). This begs the questions, how powerful can the current sampling and testing program be, and is there an end-product testing strategy that would guarantee that this would not happen again? The short answers are that current sampling and testing are not that powerful, and no, testing will not ever guarantee complete safety.

DOI

https://doi.org/10.3168/jds.2022-22374

Literature Review Investigating Intersections between US Foodservice Food Recovery and Safety

Abstract

Food waste is increasingly scrutinized due to the projected need to feed nine billion people in 2050. Food waste squanders many natural resources and occurs at all stages of the food supply chain, but economic and environmental costs are highest at later stages due to value and resource addition throughout the supply chain. Food recovery is the practice of preventing surplus food from being landfill disposed. It provides new opportunities to utilize food otherwise wasted, such as providing it to food insecure populations. Previous research suggests that consumer willingness to waste is higher if there is a perceived food safety risk. Yet, segments of the population act in contrast to conservative food safety risk management advice when food is free or extremely discounted. Therefore, food recovery and food safety may be competing priorities. This narrative review identifies the technical, regulatory, and social context relationships between food recovery and food safety, with a focus on US foodservice settings. The review identifies the additional steps in the foodservice process that stem from food recovery – increased potential for cross-contamination and hazard amplification due to temperature abuse – as well as the potential risk factors, transmission routes, and major hazards involved. This hazard identification step, the initial step in formal risk assessment, could inform strategies to best manage food safety hazards in recovery in foodservice settings. More research is needed to address the insufficient data and unclear regulatory guidelines that are barriers to implementing innovative food recovery practices in US foodservice settings.

DOI

https://doi.org/10.1016/j.resconrec.2020.105304

CRISPR-Based Subtyping Using Whole Genome Sequence Data Does Not Improve Differentiation of Persistent and Sporadic Listeria monocytogenes Strains

Four different cases that illustrate Spacer Patterns (SPs) assignment across the 175 isolates. Boxes with the same pattern are representative of the same spacer. These cases are representative of the model created to distinguish SPs. Case 1 (SP 24): A Spacer Pattern with only one CRISPR array of three spacers (boxes) between four direct repeats (circles). Case 2 (SP 25): A different SP is assigned to this single CRISPR array with five spacers, even though some spacers are shared with SP 1. Case 3 (SP 24–26): Two CRISPR arrays, which are separated by genomic distance (II) for which separate spacers patterns are assigned to each array (and separated by the ‘-’); because the first array matches SP 1, that number is recycled. Case 4 (SP 24-26-27): Three CRISPR arrays, two previously identified and one novel, containing a variety of spacers in each pattern. Spacer pattern numbers start at 24 to indicate these are example patterns and not actual spacer patterns observed in our data.

Abstract

The foodborne pathogen Listeria monocytogenes can persist in food-associated environments for long periods. To identify persistent strains, the subtyping method pulsed-field gel electrophoresis (PFGE) is being replaced by whole genome sequence (WGS)-based subtyping. It was hypothesized that analyzing specific mobile genetic elements, CRISPR (Clustered Regularly Interspaced Short Palindromic Short Repeat) spacer arrays, extracted from WGS data, could differentiate persistent and sporadic isolates within WGS-based clades. To test this hypothesis, 175 L. monocytogenes isolates, previously recovered from retail delis, were analyzed for CRISPR spacers using CRISPRFinder. These isolates represent 23 phylogenetic clades defined by WGS-based single nucleotide polymorphisms and closely related sporadic isolates. In 174/175 (99.4%) of isolates, at least one array with one spacer was identified. Numbers of spacers in a single array ranged from 1 to 28 spacers. Isolates were grouped into 13 spacer patterns (SPs) based on observed variability in the presence or absence of whole spacers. SP variation was consistent with WGS-based clades forming patterns of (i) one SP to one clade, (ii) one SP across many clades, (iii) many SPs within one clade, and (iv) many SPs across many clades. Unfortunately, SPs did not appear to differentiate persistent from sporadic isolates within any WGS-based clade. Overall, these data show that (i) CRISPR arrays are common in WGS data for these food-associated L. monocytogenes and (ii) CRISPR subtyping cannot improve the identification of persistent or sporadic isolates from retail delis. Practical Application: CRISPR spacer arrays are present in L. monocytogenes isolates and CRISPR spacer patterns are consistent with previous subtyping methods. These mobile genetic artifacts cannot improve the differentiation between persistent and sporadic L. monocytogenes isolates, used in this study. While CRISPR-based subtyping has been useful for other pathogens, it is not useful in understanding persistence in L. monocytogenes. Thus, the food safety community might be able to use CRISPRs in other areas, but CRISPRs do not seem likely to improve the differentiation of persistence in L. monocytogenes isolates from retail delis.

DOI

https://doi.org/10.1111/1750-3841.14426