Development and Yield of Irrigated Sugarcane as Affected by Nitrogen Sources and Rate in Brazilian Cerrado Oxisol
Bibliographic record
Abstract
Sugarcane is the most promising crop among renewable biofuels producers and one of the countries that produces the most green matter per unit area, whose greater limitations to productivity are mainly related to the adequate availability of water and mineral nutrients, in particular nitrogen (N). Based on the hypothesis that the source and the availability of nitrogen influence the growth, development and yield of irrigated sugarcane in the cerrado region. The objective of this study was evaluate the biometric variables and yield of irrigated sugarcane, in the cane-plant cycle, as affected by source and nitrogen rate. The soil utilized was an Oxisol (Rhodic Hapludox), cerrado (savannah) phase. The experiment was carried out at Farm of the Raízen Mill, located in the municipality of Jataí, Goias State, Brazil. The variety IACSP95-5000 was used in a randomized block design, analyzed in a split-split-plot scheme, with three replicates. The treatments were four N rates (0, 60, 120 and 180 kg ha-1); two fertilizer sources (urea and ammonium nitrate). The factors evaluated were in the plots of four doses of N (0, 60, 120 and 180 kg ha-1). In the subplot two sources of N (urea and ammonium nitrate) and as sub-subplot were represented by four evaluation periods (210, 250, 290 and 330 days after the planting-DAP). The irrigation was by sprinkling, in a central pivot. The evaluated variables were: plant height, stalk diameter, total number of leaf, leaf area, number of industrializable tillers, stalk yield, pointer yield and total recoverable sugars. The highest stalk yield, pointer yield and total recoverable sugars occurred at the average dose of 143.61 kg ha-1 of N, with an average increase of 25.87%.
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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".