The adaptability of soybean photosynthesis to midday high-light duration through CEF-NPQ coupling regulation
Bibliographic record
Abstract
Fluctuating light (FL) conditions particularly the diurnal alternation between shaded and high-light periods are intrinsic to intercropping systems and impose substantial regulatory challenges on crop photosynthesis. However, the cultivar-specific mechanisms underlying adaptation to such dynamic light environments remain largely unexplored. Here, we examined how the duration of midday high-light exposure modulates the coordination between cyclic electron flow (CEF) and non-photochemical quenching (NPQ) in two soybean cultivars grown under simulated intercropping light regimes. Plants were exposed to morning shade followed by either short (T30) or prolonged (T150, T200) midday high-light treatments. All treatments triggered common photoprotective responses, including increased energy dissipation (DIo/CSm, +18.7-22.3%) and reduced electron transport efficiency (ETo/CSm, -14.2-17.5%). Yet, the cultivars exhibited distinct photoregulatory strategies depending on light duration. The light-adapted cultivar ND12 rapidly established a proton gradient (ΔpH; 34.8% faster) and sustained higher PSII efficiency (ETRII, +41.5%) under brief high-light exposure, indicating a preemptive ΔpH priming mechanism. In contrast, the light-sensitive GX7 required extended high-light duration (T200) to induce CEF (+60.5%) and plastoquinone pool expansion (+22.0%), suggesting a delayed, duration-dependent adjustment strategy. These cultivar-specific responses ultimately enhanced photosynthetic performance by 34.8-52.4% under FL conditions. Our findings offer mechanistic insights into how midday light duration shapes genotype-dependent photosynthetic regulation, providing a physiological basis for optimizing light utilization in intercropping systems.
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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".