Impact of antimicrobial treatments on sprouting alfalfa seed contaminated with Salmonella enterica
Bibliographic record
Abstract
Consumption of alfalfa sprouts has increased worldwide due to the nutritional value and health benefits of sprouts. However, alfalfa sprouts contaminated with Salmonella enterica (S. enterica) have been the source of many foodborne outbreaks in Europe and North America. Antimicrobial treatments for sprouted seeds are recommended by the Canadian Food Inspection Agency but the influence of different antimicrobial sanitation seed treatments on the behaviour of S. enterica during seed germination remains unclear. The goals of this study were (1) to investigate the ability of S. enterica to grow on sprouting alfalfa seeds after three different sanitation seed treatments to reduce microbial load, and (2) to understand how colonization by S. enterica and different antimicrobial treatments affect metabolites released by sprouting alfalfa seed. Alfalfa seeds inoculated with five strains of S. enterica were subject to three different seed treatments: (1) sodium hypochlorite (NaClO), (2) hydrogen peroxide (H₂O₂), and (3) an organic treatment involving a hot water dip, treatment with H₂O₂ and acetic acid. The disinfected seeds were sprouted to identify the growth characteristics of S. enterica after sanitation stress (n = 3). The populations of all five S. enterica strains which were present at <10 CFU/g immediately after sanitation treatment increased to 4 - 8 log CFU/g after 6 days of germination. After 6 days of germination, most S. enterica strains recovered from sprouts germinated from seeds treated with H₂O₂ or the organic treatment were lower than those recovered from sprouts germinated from seeds treated with NaClO. Additionally, metabolites were identified by rinsing seeds after 24 hours of germination (n = 4). Almost all of the 535 identified compounds were affected by the application of antimicrobial treatments. Specifically, the NaClO treatment diminished the levels of metabolites on uninoculated, S. enterica Agona and Typhimurium colonized sprouting seed by almost half, possibly via oxidative destruction. The organic treatment increased and decreased similar numbers of metabolites, around 30% of all detected metabolites. This study provided new insight on the ecology of S. enterica on germinating seeds, an important consideration in the development of better strategies to lessen the risk associated with sprouted vegetables.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".