Biochemical and physiological response of borage to seed priming and water deficit: antioxidant enzymes, osmolytes, photosynthetic pigments, and fluorescence parameters
Bibliographic record
Abstract
Aim of study: To investigate the general response patterns of the borage plant to water fluctuations from a biochemical and physiological perspective. Area of study: East Azerbaijan Province of Iran during the period 2012 and 2013. Material and methods: The study investigated the effects of irrigation (after 60, 90, 120 and 150 mm evaporation) and priming (unprimed, and primed seeds with water, 1% KNO3 and 1% KH2PO4) on the antioxidant enzymes, osmolytes, photosynthetic pigments, and fluorescence parameters of borage using a split-plot experimental design. Main results: The statistical analyses showed no effect of seed priming on all evaluated traits other than than extracellular superoxide dismutase SOD3 activity where it was significantly enhanced by seed pretreatment with 1% KNO3 and 1% KH2PO4. However, irrigations after 120 and 150 mm evaporation increased Cu/Zn-superoxide dismutase (SOD1), SOD2, and SOD3, soluble sugars, and initial fluorescence (F0). The mean contents of Ch a, Ch b, and Ch a+Ch b under mild, moderate and severe water deficit were significantly higher than those under normal irrigation. Severe drought stress gave the highest carotenoids content and quantum yield baseline parameter (F0/Fm) of borage leaves. However, water limitation decreased Chl a/Chl b ratio, maximum primary yield of photosystem II (Fv/F0), and maximum quantum yield of photosystem II (Fv/Fm). Research highlights: Based on these findings, it is postulated that the increase in soluble sugars and SOD activity under stress, and the accumulation of carotenoids under severe water limitation indirectly enhance the tolerance of borage plants 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) | 0.000 | 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".