Physiological Limitations to Photosynthetic Carbon Assimilation in Cotton under Water Stress
Bibliographic record
Abstract
Water stress may reduce leaf net photosynthetic carbon assimilation (AN) through both stomatal effects, which reduce the leaf internal CO2 concentration (Ci), and nonstomatal effects, which result in reduced AN at a given level of Ci However, the leaf gas exchange techniques used to calculate Ci are susceptible to important artifacts when applied to water‐stressed leaves, making such Ci estimates unreliable. As an alternative to Ci, the CO2 concentration in the chloroplast (CC) can be calculated from simultaneous measurements of AN from gas exchange measurements, and the thylakoid electron flux from chlorophyll fluorometry. This permits diffusional effects (stomatal plus mesophyll limitations to CO2 diffusion) to be differentiated from chloroplast‐level effects. We used this method to investigate physiological restrictions to photosynthesis in leaves of water stressed cotton (Gossypium hirsutum L.) plants in a series of greenhouse experiments. A null‐balance lysimeter was used to slowly induce four distinct levels of water stress. Combined leaf gas exchange/chlorophyll fluorescence measurements differentiated the treatments more effectively than gas exchange measurements alone. All treatments reduced CC, but only the two most severe stress treatments significantly increased nondiffusional restrictions, detectable as a reduction in the slope of AN on CC In a second experiment, recovery of leaf photosynthesis was determined 24 and 48 h after relief of a severe stress by rewatering. Recovery of the AN/CC relationship was substantial but incomplete after 24 h and did not recover further by 48 h after rewatering, indicating lasting chloroplast‐level injury as a result of the stress. Similar experiments should be conducted under field conditions to determine if water stress results in irreversible chloroplast‐level injury in field‐grown cotton.
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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 | 0.001 |
| 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".