Effect of Watering Regimes and Water Quantity on the Early Seedling Growth of Picralimanitida (Stapf)
Bibliographic record
Abstract
<!--[if gte mso 9]> Normal 0 7.8 ? 0 2 false false false EN-US ZH-CN X-NONE MicrosoftInternetExplorer4 <![endif]--> Competing land use pattern has necessitated planting of useful forest trees on marginal lands with varying water status. A study was conducted on the effect of watering regimes and water quantity on seedlings growth of P. nitida. Seedlings were raised from seeds, transplanted in polythene bags and subjected to watering at full capacity daily, once in 3 days, 5 days; 20 ml daily, 3 days, 5 days; 15 ml daily, 3 days, 5 days; 10 ml daily, 3 days, 5 days; and flooding. The growth traits assessed were plant height, collar diameter, number of leaves; shoot, root and leaf dry weights as well as leaf area. The effect of watering regime and water quantity were significant (P ? 0.05) on quantitative morphological parameters of seedlings. Total dry weight and root dry weight were lower in both water-stressed and waterlogging than well-watered conditions, but the lowest values were obtained under flooding. However, specific leaf area (SLA) and leaf area ratio (LAR) were higher in water-stressed conditions than well-watered conditions. Relative growth rate of seedlings is related more to the net assimilation rate values than LAR and SLA. Also, root/shoot ratio was highest under daily full capacity watering. Thus, daily watering at full capacity with water availability or 15-20 ml of water per seedling during scarcity is recommended for raising P. nitida seedlings. <!--[if gte mso 9]>
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".