Evaluation of Urochloa decumbens cv. Basilisk in Response to Nitrogen Fertilization and Inoculation With Diazotrophic Bacterium
Bibliographic record
Abstract
Nitrogen fertilization provides a great response in pasture productivity and quality but, after applied to the soil, this element undergoes several transformations, what increase its losses. To minimize this problem, a promising alternative currently suggested is diazotrophic bacteria use, which can contribute to a greater use of nitrogen by plants. This study aimed to evaluate the effect of nitrogen doses with and without inoculation of seeds with Azospirillum brasilense on the structural characteristics, chemical composition, and mass production of Urochloa decumbens cv. Basilisk. The experimental design was completely randomized, arranged in a 2 × 5 factorial scheme, with four replications. Treatments consisted of forage seed inoculation or not with Azospirillum and five nitrogen doses (0, 50, 100, 150, and 200 kg ha-1). The variables analyzed were plant height, number of tillers, shoot dry mass (SDM), root dry mass (RDM), SDM/RDM ratio, chlorophyll index, nutrient content in forage shoot, crude protein (CP), neutral detergent fiber (NDF), and nitrogen use efficiency. The inoculation of forage seeds with A. brasilense associated with nitrogen doses up to 100 kg ha-1 contributed positively to dry mass, plant-shoot nutrient content and bromatological composition of U. decumbens cv. Basilisk. The inoculation of seeds of U. decumbens cv. Basilisk, with A. brasiliense, is a viable alternative for partial substitution of nitrogen fertilization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".