<i>S-</i>Alk(en)yl- <scp>l</scp>-cysteine Sulfoxides and Relative Pungency Measurements of Photosynthetic and Nonphotosynthetic Tissues of <i>Allium porrum</i>
Bibliographic record
Abstract
Three standard assays for pyruvate gave equivalent measurements of relative pungency for two leek cultivars ( 'Tadorna' and 'Ramona'). Background pyruvate levels varied depending on the assay used, ranging from 0.4 (lactate dehydrogenase) to 1.5 (high-performance liquid chromatography, HPLC) micromol g(-1) fresh weight (FW) on average. The relative pungencies of the two leek cultivars were also compared to total concentrations of the S-alk(en)yl-L-cysteine sulfoxides (RCSOs). The average ratio of EPy to total RCSOs was 10.9, indicating that standard pungency assays underestimate the levels of RCSOs in the tissue. A detailed analysis of 'Tadorna' leaves showed that total RCSO concentrations decreased acropetally. Profiles were composed of (-/+)-methyl-, (-/+)-ethyl-, (+)-propyl-, and (+)-1-propenyl-L-cysteine sulfoxide (MCSO, ECSO, PCSO, and 1-PeCSO, respectively). (+)-PCSO was the most prominent in green (2.4 mg g (-1) FW), yellow (5.5 mg g (-1) FW), and white (3.8 mg g (-1) FW) tissues. The prop(en)yl-L-cysteine sulfoxide derivatives were dominant in tissues that had photosynthetic capacity. The (+)-MCSO levels were high in the bulb (3.6 mg g (-1) FW). Interestingly, detectable levels of (-/+)-ECSO were measured in the leaves ( approximately 0.5 mg g (-1) FW). RCSO profiles of the different tissue regions were similar, but more (+)-PCSO and (+)-1-PeCSO were detected in the bulb. In general, mature upper leaf tissues had lower levels of total RCSOs. Overall, mild extraction methods and a low-temperature HPLC protocol (preferably with long retention times) achieved adequate compound separation and resolution of the diastereomers.
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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) | 0.000 | 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 | 0.001 |
| 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".