Yield Response of Upland Rice as Influenced by Enhanced-Efficiency Nitrogen Fertilizers in the Brazilian Cerrado
Bibliographic record
Abstract
Nitrogen (N) fertilizers have their use efficiency adversely affected by the rate and source of N. A two-year field experiment was conducted to examine the yield response of upland rice by using NBPT (urease inhibitor), PCU (polymer-coated urea) and uncoated urea under different N application rates. It was hypothesized that either NPBT or PCU may result in increased yield components of upland rice when compared to conventional urea. The experiment was set up in a randomized block design in a 3 × 4 + 1 factorial scheme, with four replicates. Treatments comprised three sources (conventional uncoated urea, NBPT-treated urea, and polymer-coated urea) and four rates (30, 60, 90 and 120 kg ha-1) of N, in addition to a control treatment (no fertilizer application). Nitrogen fertilizers were applied in two split doses: 50% at the seedling stage, and 50% at the tillering stage (~80 days after planting). The results revealed that the use of enhanced-efficiency N sources increased the productivity and plant height of upland rice crop when compared to conventional urea. As compared to when it is untreated or polymner-coated, treating urea with NBPT resulted in increased 100-grain weight.
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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".