Fitomassa de girassol cultivado sob adubação nitrogenada e níveis de água disponível no solo
Bibliographic record
Abstract
Nitrogen is the most required nutrient by plants to assume exerting important functions in the vegetable metabolism. In sunflower crop, its deficiency causes nutritional disorder, being the nutrient that most limits the yield. Besides, the lack of water limits the growth and yield of plants. Therefore, the study was conducted at the experimental area of Department of Agricultural Engineering, University of Campina Grande, in the period March to June 2010, aiming to evaluate the dry matter of sunflower cv EMBRAPA 122/V-2000 subjected to nitrogen levels (0; 60; 80 e 100 kg ha-1) and levels of available soil water (55; 70; 85; e 100%). The experimental design was completely randomized in factorial analysis (4 x 4) with three replications totaling 48 experimental units. The sunflower plants were grown in pots with 35 L capacity containing Luvisol (Alfisol) and kept under daily irrigation. At harvest the following variables were evaluated: Fresh and dry biomass of shoot, stem and leaves, and from these, the water content in the shoot. Nitrogen fertilization did not influence the production of fresh and dry biomass of sunflower cv EMBRAPA 122/V-2000, except the dry stem. All variables increased linearly as a function of available soil water. The interaction between dose 80 kg N ha-1 and the level of 100% of available soil water was adequate for the best results in the production of biomass.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".