Involvement of abscisic acid metabolites and the oxidative status of barley genotypes in response to drought
Bibliographic record
Abstract
Thameur, A., Ferchichi, A. and López-Carbonell, M. 2014. Involvement of abscisic acid metabolites and the oxidative status of barley genotypes in response to drought. Can. J. Plant Sci. 94: 1481–1490. Endogenous concentrations of free abscisic acid (ABA), abscisic acid glucosyl ester (ABAGE), phaseic acid (PA), dihydrophaseic acid (DPA) and 7′-hydroxy ABA (7′-OH ABA) were analysed by means of a LC–MS/MS system in five genotypes of barley (Hordeum vulgare L.) grown under well-watered and drought stress conditions. For this purpose a drought treatment was conducted using genotypes: ‘Ardahoui’, ‘Manel’, ‘Pakistan’, ‘Rihane’ and ‘Roho’. Our results show that free and conjugated ABA levels increased in all genotypes grown under water stress, except in Manel genotype, in which ABAGE levels were the lowest. In contrast, genotypes Ardhaoui and Roho showed the highest ABA and ABAGE levels. Nevertheless, drought Rihane plants showed the maximum ability to increase the endogenous ABA concentrations. PA, DPA and 7′-OH ABA increased also in all drought genotypes, especially in the leaves of Manel and Roho genotypes, while the highest ability to increase the endogenous PA content corresponded to genotypes Ardahoui and Pakistan. To evaluate the plant oxidative status, some antioxidant compounds were analysed. Under drought conditions, small changes in some of them were seen. Among the genotypes studied, Manel was the only one which did not show increases in malondialdehyde (MDA) and, in parallel, showed a decrease in ABAGE content. These results provide us valuable information and contribute to the knowledge of the different responses of these genotypes to drought stress.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".