Comparison of microbial diversity of edible flowers and basil grown with organic versus conventional methods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The consumption and use of edible flowers as food is growing; however, no study has been conducted to evaluate their role in the cause of food-borne illness or in food safety. Recent food-borne outbreaks traced to fresh herbs have raised concern about their processing and handling. Basil, one of the most commonly used fresh herbs, has been identified as a source of food-borne illness. Baseline assessments of microflora were performed, and the microbial diversity between growing methods (organic vs. conventional) was compared. DNA sequencing was used to identify the microbial flora present on fresh edible flower and basil samples. The most predominant species identified were Enterobacter hormaechei (10%), Acinetobacter calcoaceticus (10%), Enterobacter ludwigii (10%), Enterobacter asburiae (6%), and Enterobacter cowanii (6%). Pseudomonas aeruginosa (6%), Salmonella enterica (6%), and Bacillus amyloliquefaciens (2%) were also isolated. Phylogenetic analysis showed that most species of isolated bacteria belonged to the phyla Gammaproteobacteria (81.2%) and Firmicutes (18.8%). Statistical analysis, diversity index for species richness, and lineage-per-time plots showed that for basil, organically grown samples had a higher microbial diversity than conventionally grown samples. Edible flowers and basil are often grown using organic methods and are commonly consumed raw without any washing or cooking, to preserve aesthetic value, but these practices may pose a potential risk for food-borne illness. The baseline assessment, together with phylogenetic and statistical analyses, indicated possible microbial contamination in edible flowers and basil. The use of statistical estimation of molecular diversity based on the 16S rRNA sequences and lineage-per-time plots with phylogenetic analysis well served as a means for comparing microbial diversity in food samples between the growing methods (organic vs. conventional).
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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 | 0.000 |
| 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) | 0.001 | 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 it