Growth of Sugar Cane Under Cultivation Flooded at Different Speeds Lowering of the Water Table
Bibliographic record
Abstract
In order to study the effect of downgrade rate of water table in the growth of sugar cane (Saccharum spp, cultivate 867515), an experiment in was carried under randomized block design with factorial arrangement (3 × 5 + 1) and 4 replications, applying the flood irrigation system in 3 stages of development (67, 210 and 300 days after planting - DAP) with 5 downgrade rate of water table (3, 6, 9, 12 and 15 days) and the control (no flood). The plants were grown in soil columns of 240 liters, filled with Yellow Oxisol by 300 days after planting and monitored as the height of the stem, number of leaves, stem diameter, number of internodes, number of tillers, leaf area, growth increment, rate relative growth, leaf area index, leaf area ratio and specific leaf area. The stages of development that the flooding was applied at a rate of lowering of the groundwater level variables influenced the growth of cane sugar. The plants drenched at 210 days after planting for 12 days had higher growth of stem, leaf number, leaf area and leaf area index. Plants exposed to water logging after 67 and 210 days after planting obtain better physiological indices that the witness and those who received the 305 DAP waterlogging. It is recommended that the spacing between drains is estimated to be able to lower the water table, after a reloading project to 30 cm deep in 15 days.
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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".