Quantitative and Qualitative Study of Phenolic Compounds Involved in Germination Inhibition of Wheat under Water Deficit
Bibliographic record
Abstract
In the aim to study the contribution of phenolic compounds in the inhibition of seeds germination of wheat (Triticum aestivum L.) under water deficit, we have forwarded quantitatively and qualitatively the change of the phenolic compounds levels in the seeds of two varieties (Achtar and Tigre) submitted to water stress induced by PEG-6000 during the germination stage. The results revealed significant differences between the stress intensity and duration and the polyphenol content. Some germination traits were significantly correlated with water stress and polyphenols in the both varieties studied. The polyphenol content in Tigre was much higher than those noted in Achtar. Analysis of phenolic extracts by HPLC showed the dominance of hydroxycinnamic derivatives (97.2% and 94.5% in Tigre and Achtar, respectively). Regarding phenolic acid, the ferulic acid was the most dominant, and seemed to be related mainly to the inhibition of germination. Quantitatively, the Achtar variety was characterized by the presence of acid sinapic which was absent in Tigre variety. Furthermore, the water deficit appeared to stimulate the induction of salicylic acid accumulation in both varieties.
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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) | 0.000 | 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 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".