Foliar application of strigolactones improves the desiccation tolerance, grain yield and water use efficiency in dryland wheat through modulation of non-hydraulic root signals and antioxidant defense
Bibliographic record
Abstract
Non-hydraulic root signals (nHRS) are affirmed as a unique positive response to soil drying, and play a crucial role in regulating water use efficiency and yield formation in dryland wheat production. Strigolactones (SLs) can enhance plant drought adaptability. However, the question of whether strigolactones enhance grain yield and water use efficiency by regulating nHRS and antioxidant defense systems in dryland wheat remains unanswered. In this study, pot experiments were conducted to investigate the effects of strigolactones on nHRS, antioxidant defense system, and grain yield and water use efficiency in dryland wheat. The results showed that external application of SLs increased drought-induced abscisic acid (ABA) accumulation and activated an earlier trigger of nHRS at 73.4% field capacity (FC), compared to 68.5% FC in the control group (CK). This phenomenon was mechanically associated with the physiological mediation of SLs. The application of SLs significantly enhanced the activities of leaf antioxidant enzymes, reduced ROS production, and mitigated oxidative damage to lipid membrane. Additionally, root biomass, root length density, and root to shoot ratio were increased under strigolactone treatment. Furthermore, exogenous application of SLs significantly increased grain yield by 34.9% under moderate drought stress. Water use efficiency was also increased by 21.5% and 33.3% under moderate and severe drought conditions respectively, compared to the control group (CK). The results suggested that the application of strigolactones triggered earlier drought-sensing mechanism and improved the antioxidant defense ability, thus enhancing grain yield and water use efficiency in dryland wheat production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".