Verte and Romaine lettuce varieties (<i>Lactuca sativa</i>) show differential responses to high NaCl concentrations
Bibliographic record
Abstract
Abstract In this study, we report on the relationship between individual antioxidant carotenoids, phenolic fractions, and flavonoids and attenuating NaCl toxicity in two contrasting varieties of lettuce (Lactuca sativa L., var. Verte and Romaine), as a means of developing more precise targets for lettuce breeding. In seedling leaves, carotenoid levels increased under NaCl stress in Verte, but remained unchanged in Romaine. Chlorogenic acid (CGA), a soluble polyphenol abundantly present in leaves, was the only phenolic acid that accumulated significantly in both varieties and was predominant under salinity. Remarkably, CGA was more prominent in Verte than Romaine at moderate salinity levels (100 mM). Foliar flavonoid levels were also differentially increased in both seedling types grown under 100 mM NaCl, but dropped significantly in both varieties under 200 mM NaCl. Germination, which was overall more salt‐resistant in Romaine, was significantly increased under salt stress by application of low dosage (10–6 to10–5 M) of CGA to Verte, but not to Romaine. These results suggest that CGA is involved in modulating NaCl‐induced oxidative‐stress responses during seed germination in Verte.
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 | 0.000 |
| 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 | 0.001 |
| 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".