Root morphology, growth, and physiology in Begonia (<i>Malus</i> × <i>micromalus</i>) grown in copper hydroxide containers
Bibliographic record
Abstract
A major concern with container seedlings is root circling and deformation that will affect post-planting performance and stability. To improve root quality, 3-year-old Begonia ( Malus × micromalus) plants were grown in the containers treated on interior surfaces with different concentrations of copper hydroxide (Cu(OH)2) (0, 40, 80, 120, 160, and 200 g L−1) for 1 year. Compared with the standard container control (SC) and carrier asphalt container control (AC), the number of terminal lateral roots and lateral root volume were increased by 21% and 13% at 80 and 120 g L−1 Cu(OH)2 but decreased by 8% and 10% at 200 g L−1 Cu(OH)2. Only 80 g L−1 Cu(OH)2 increased the plant height and root weight, while other concentrations of Cu(OH)2 resulted in the declines. Phosphorus and potassium were improved with lower concentrations of Cu(OH)2 but decreased with 160 and 200 g L−1 Cu(OH)2. No significant difference in the concentrations of soluble protein and sugars in leaves was observed between Cu(OH)2 treatments and the controls. AC decreased nitrogen concentration in leaves by 12% over the SC across the whole growing season and increased taproot diameter by 17%. Our results indicate that 80 g L−1 Cu(OH)2 was the optimum concentration for root pruning and the maintenance of physiological function. Disadvantages in growth and physiology gradually showed up with increased concentrations.
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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".