Shade Inhibits Leaf Size by Controlling Cell Proliferation and Enlargement in Soybean
Bibliographic record
Abstract
To gain more insight into the physiological function of shade and how shade affects leaf size, we investigated the growth, leaf anatomical structure, hormones and genes expressions in soybean. Soybean seeds were sown in plastic pots and were allowed to germinate and grow for 30 days under shade or full sunlight conditions. Shade treated plants showed significantly increase on stem length and petiole length, and decrease on stem diameters, shoot biomass and its partition to leaf also were significantly lower than that in full sunlight. Smaller and thinner on shade treated leaves than corresponding leaves on full sunlight plants. The decreased leaf size caused by shade was largely attributable to cell proliferation in young leaves and both cell proliferation and enlargement in old leaves. Shade induced the expression of a set of genes related to cell proliferation and/or enlargement, but depended on the developmental stage of leaf. Shade significantly increased the auxin and gibberellin content, and significantly decreased the cytokinin content in young, middle and old leaves. Taken together, these results indicated that shade inhibited leaf size by controlling cell proliferation and enlargement, auxin, gibberellin and cytokinin may play important roles in this process.
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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) | 0.000 | 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".