Consequences of Drought Stress Encountered During Seedling Stage on Physiology and Yield of Cultivated Cotton
Bibliographic record
Abstract
Survival of living organisms depends on the availability of water resources required for agriculture. In the current scenario of limited water resources, it is our priority to maximise the yield potential of crops with a minimum supply of available water. In this study, we evaluated seven cultivated varieties of Gossypium hirsutum (FH-114, FH-152, FH-326, FH-492, FH-942, VH-327 and FH-NOOR) for their tolerance, yield potential and fibre quality under water shortages. We also studied the effect of drought stress on osmoregulation, chlorophyll content, antioxidant (peroxidase and catalase) activity, lipid peroxidation and secondary metabolite accumulation in the varieties under study. It was revealed that three varieties (FH-114, FH-152 and VH-327) exhibited a lower stress susceptibility index and more tolerance to drought stress. All the varieties demonstrated enhanced proline and malondialdehyde content, but no significant change in chlorophyll content was observed under limited water supply. Antioxidant activity offered by catalase and phenolic content was enhanced in FH-492 whilst peroxidase activity increased in FH-114 and FH-326. Phenolic content was highest in FH-942 and decreased significantly in the remaining varieties. Ginning outturn of the cotton varieties increased in VH-327 (19.8%) and FH-326 (3.7%), was not affected in FH-114 and FH-492 and was reduced in FH-152, FH-942 and FH-NOOR. All cotton varieties tested showed an increase in micronaire thickness when exposed to drought stress as early as the seedling stage. This study highlights the evaluation and screening of cotton varieties for their response to drought stress in terms of yield and fibre quality when exposed to water shortages during plant development and can help in devising irrigation plans.
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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) | 0.000 | 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 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".