Light‐induced systemic signalling down‐regulates photosynthetic performance of soybean leaves with different directional effects
Bibliographic record
Abstract
Abstract When plants are exposed to a heterogeneous environment, photosynthesis of leaves is not only determined by their local condition, but also by certain signals from other parts of the same plant, termed systemic regulation. Our present study was conducted to investigate the effects of light‐dependent systemic regulation on the photosynthetic performance of soybean (Glycine max L. Merr.) under heterogeneous light conditions. Soybean plants were treated with heterogeneous light. Then gas exchange characteristics were measured to evaluate the photosynthetic performance of leaves. Parameters related to photosynthetic pigments, chlorophyll fluorescence, Rubisco and photosynthates were examined to study the mechanisms of light‐dependent systemic regulation on photosynthesis. Light‐induced systemic signalling by illuminated leaves reduced the Pn of both upper and lower non‐illuminated leaves on the same soybean plant. The decrease in gs and increase in Ci in these non‐illuminated leaves indicated restriction of carbon assimilation, which was further verified by the decline in content and activity of Rubisco. However, the activation state of Rubisco decreased only in upper non‐illuminated leaves. Quantum efficiency of PSII (ΦPSII) and ETR also decreased only in upper non‐illuminated leaves. Moreover, the effects of light‐induced systemic signalling on carbohydrate content were also detectable only in upper non‐illuminated leaves. Light‐induced systemic signalling by illuminated leaves restricts carbon assimilation and down‐regulates photosynthetic performance of non‐illuminated leaves within a soybean plant. However, effects of such systemic regulation differed when regulated in upward or downward direction.
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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".