Effect of chilling and salinity stress on photosynthetic performance and ultrastructure of chloroplast in faba beans (Vicia faba L.) leaves
Bibliographic record
Abstract
Abstract Chilling (Ch) and salinity (S) are challenging stresses affecting plant physiology, growth, and productivity. The current study investigated the effects of these two stresses, singly and in combination, on photosynthetic performance and ultrastructure of chloroplast of faba beans (Vicia faba L. Cv. Aspani). Plants were exposed to 3 °C and 120 mM NaCl for 16 h in an optimized soil mixture (sand:clay 2:1) under optimized conditions. Results showed that both Ch and S significantly reduced photosynthetic rates, Fv/Fm, chlorophyll content, stomatal index, and stomatal conductance. Chilling caused changes in chloroplast ultrastructure (swelling, ruptured envelopes, and shrunk lamellae), while salinity caused more deformation of the thylakoid membrane and disorganization of the grana structure. However, there was an antagonistic effect between Ch x S. The tolerance of plant to 120 mM NaCl, in the present study, was improved by exposure to Ch which rather allowed the maintenance of chloroplast ultrastructure and morphology of stomata. Moreover, using SEM and TEM gave an effective insight of the ultrastructural damage in plant cells under stress and helps to consider the underlying mechanisms of stress effects. Our results suggest that Ch mitigates the noxious effect of S on the photosynthetic performance of Vicia faba plants.
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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".