Biometric and Bromatological Characteristics of Brachiaria Inoculated With Azospirillum brasilense Associated With Nitrogen Fertilization
Bibliographic record
Abstract
The objective of this study was to evaluate the biometric and bromatological characteristics of Urochloa ruziziensis in due to inoculation times with Azospirillum brasilense in the presence or absence of nitrogen fertilization. To do so it was used a randomized blocks design, with factorial scheme 4 × 2, where the first factor consisted the inoculation periods: control; A. brasilense in the seed; A. brasilense at tillering (aerial) and A. brasilense seed + foliar. The second factor constituted in the presence or absence of nitrogen (1000 mg dm³). Evaluations were made in the first, second and third cut, being evaluated the plant height, number of tillers per plant, leaves dry mass, culm+sheath dry mass; crude protein content, neutral detergent fiber and acid detergent fiber. The use of nitrogen fertilization increased the productive and bromatological parameters in the crop of U. ruziziensis, however, the use of A. brasilense increased only the height of plants, not influencing the other productive characteristics and the bromatological parameters. It is concluded that the use of A. brasilense, regardless the period it was made, presents inconclusive results for biometric and bromatological characteristics of plants of Urochloa ruziziensis in need of further studies, on the other hand, the nitrogen fertilization brings positive effects over the evaluated parameters on U. ruziziensis.
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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".