A research note: the potential for transfer of <i>Salmonella</i> from irrigation water to tomatoes
Bibliographic record
Abstract
Abstract The transmission of Salmonella Enteritidis from soil to fruit by contaminated irrigated water was studied using 20 patio tomato plants. In order to track the presence of Salmonella in the soil and plants a luminescent strain transformed with the full luxCDABE gene cassette from Photorhabdus luminescens was used. The tomato plants were irrigated every other day by direct application of water containing Salmonella Enteritidis (105 CFU ml−1) to the soil. Samples of soil, stem, leaf and fruit were taken weekly and assayed for Salmonella by plating onto Luria Bertani agar containing 50 µg ml−1 ampicillin. There was a significant difference (P < 0.05) in Salmonella counts from soils sampled during the course of the study. No Salmonella were recovered from the leaf, stem, and fruit samples taken from the tomato plants. This indicates that, under these test conditions, watering with contaminated water directly into the soil does not result in the transmission of Salmonella, and possibly other pathogens, to tomatoes. Copyright © 2004 Society of Chemical Industry
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".