Shading Affects Morphology, Dry-matter Partitioning, and Photosynthetic Response of Greenhouse-grown `Chardonnay' Grapevines
Bibliographic record
Abstract
In order to gain an understanding of the capacity of severely shaded leaves to be productive in dense canopies, the effects of increased shading on morphology, dry-matter partitioning, and whole-plant net carbon exchange rate (NCER) were investigated on greenhouse-grown Vitis vinifera L. `Chardonnay' grapevines. Vines were subjected to whole-plant shading levels of 0%, 54%, 90%, and 99% of direct sun 3 weeks after potting. Data were collected 8 to 10 weeks after potting. Nonlinear regression was used to investigate the relationship of leaf morphological traits and organ dry weights to increased shading. Leaf size was maintained with increased shading to approximately the 90% shading level, while leaf fresh weight, volume, density, and thickness were immediately reduced with increased shading. Root dry weight was most affected by increased shading, and root to shoot ratio was reduced. When nonlinear regressions were produced for light response curves, light compensation point was reduced by approximately 49% by moderate shading, and 61% by severe shading. Shaded leaves approached the asymptote of the light response curve more quickly, and had reduced dark respiration rates, indicating that the morphological compensation responses by the vine allow shaded leaves to use available light more efficiently. However, the long-term ramifications of reduced root growth in the current year on vines with shaded leaves may be significant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".