Microbiological Survey of Wheat Flour Sold at Retail in Canada, 2018 to 2019
Bibliographic record
Abstract
ABSTRACT: Following two O121 Shiga toxin-producing Escherichia coli (STEC) outbreaks linked to wheat flour, this study was conducted to gain baseline information on the occurrence of bacterial pathogens and levels of indicator organisms in wheat flour in Canada. A total of 347 prepackaged wheat flour samples were analyzed for Salmonella species, STEC, Listeria monocytogenes, aerobic colony count (ACC), total coliforms, and Escherichia coli. Salmonella spp. and O157 STEC were not detected in any of the samples. L. monocytogenes was identified in two samples (0.6%) at levels below the limit of detection (<0.7 log CFU/g). Non-O157 STEC were isolated from six samples (1.7%) and were characterized for the presence of STEC virulence genes: stx1, stx2, and their subtypes, eae, hlyA, and aggR. One O103:H25 STEC isolate carried virulence genes (stx1a+eae) that are known to be capable of causing diarrhea and/or bloody diarrhea in humans. Of the five remaining non-O157 STEC isolates, four carried single stx2a or stx2c genes and were considered to have the potential of causing diarrhea. The remaining non-O157 STEC isolate (stx2), while not a priority non-O157 STEC, was not available for sequencing; thus, its potential to cause illness is unknown. ACC, total coliforms, and E. coli were detected (≥0.48 log CFU/g) in 98.8, 72.6, and 0.6% of the flour samples. The mean counts of ACC were greater in whole wheat flour compared with the other flour types tested (P < 0.001). The results of this study suggest that the occurrence of O157 STEC and Salmonella is low but that the occurrence of non-O157 STEC in wheat flour with the potential to cause human illness of diarrhea is relatively common. Therefore, the consumption of raw flour could increase the likelihood of STEC infections. Further research is merited for potential risk mitigation strategies within the food production system and with consumers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".