Corn Hybrids Response to Nitrogen Rates at Multiple Locations in Brazilian Amazon
Bibliographic record
Abstract
Among the nutritional requirements of corn crop, nitrogen (N) is the element required in greater quantity and, directly responsible for increase or decrease in grain production. The aims of study were to evaluate the effects of applied N rates in topdressing in development and production of corn in Brazilian Amazon. The experiments were installed on 20 January 2014 (Capitão Poço city) and 24 January 2014 (Paragominas city). The experimental design was a randomized block design in a 5 × 2 factorial scheme, consisting of five N rates of topdressing applications (0; 40; 80; 120; and 160 kg ha-1 of N) and two corn double hybrids (AL-Avaré; and AL-Bandeirante), with four replicates. The evaluations of vegetative development components (plant height, height of ear insertion, and leaf area index) were carried out at time of male flowering stage, while evaluations of grain yield components (number of grains per row, grain yield, and harvest index) carried out during the harvest period. The corn hybrids, AL-Avaré and AL-Bandeirante, independent of experimental site, showed the highest technical efficiency between the rates of 80 to 120 kg ha-1 of N. Based on the information obtained in regression analysis verified that Paragominas experiment showed greater vegetative development (plant height, LAI, ear height, number of grains per row, ear length) and higher grain yield compared to corn developed in Capitão Poço experiment.
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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) | 0.001 | 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".