Seasonal water-heat-salt dynamics in coastal salinized fields: impacts on cotton photosynthesis and yield
Bibliographic record
Abstract
Introduction: Soil moisture, temperature, and salinity critically constrain cotton production in saline soils. Understanding how cotton photosynthetic characteristics and yield respond to seasonal water-heat-salt dynamics is essential for improving management practices in these challenging environments. Methods: A two-year field study (2015-2016) was conducted comparing cotton growth, photosynthetic characteristics, and yield in mildly, moderately, and severely salinized fields. Seasonal soil water-salt dynamics in the 0-200 cm layer were monitored. Results: seasonal rainfall and temperature fluctuations significantly influenced soil water-salt dynamics in the 0-140 cm layer. During spring (April-May), drought maintained soil salinity above 3 g/kg, while low temperatures delayed cotton germination by over a day. In rainy season (July-August), rainfall leached salts from topsoil (0-40 cm), reducing salinity to below 5 g/kg and alleviating salt stress. Mildly saline fields exhibited superior photosynthetic performance, with leaf area index, chlorophyll content, and canopy photosynthetic rate being 1.2-1.5 times higher than in moderate/severe fields. These fields also showed extended "source-sink" organ development periods (16-28 days for "source," 4-24 days for "sink") and 13.8%-18.8% greater boll weight, ultimately achieving a seed cotton yield of 3,303 kg/ha-34.3%-120.7% higher than yields from moderate/severe fields. Discussion: Our results indicate that excessive soil salinity primarily impairs photosynthetic capacity and disrupts photosynthate allocation to bolls. Strategic interventions like drip irrigation could mitigate salt stress while improving photosynthetic efficiency and yield, providing practical solutions for cotton cultivation in saline fields.
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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".