ACÚMULO E PARTIÇÃO DE BIOMASSA E MACRONUTRIENTES DE CULTIVARES DE FEIJÃO-VAGEM EM CULTIVO PROTEGIDO FERTIRRIGADO
Bibliographic record
Abstract
For a better management of fertigation in protected cultivation of vegetables such as snap beans, it is important to know the nutritional requirements of the plants. Thus, we aimed to characterize the biomass and nutrients accumulation of bush snap beans genotypes. For that, an experiment was carried out in greenhouse, where the genotypes UEL-1 and Alessa were grown in plastic pots with coarse sand as substrate and fertigation by micro sprinklers. Each ten days, plants were sampled and measured the dry matter and the concentrations of elements such as nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg) and sulfur (S), adjusting their accumulation over time by the gaussian model. The fresh pods yield (kg m-2) was also evaluated. The accumulation of biomass and macronutrients are intensified from 20 days after emergence (DAE), reaching maximum values near 50 DAE. The genotype Alessa presented a higher overall accumulation, while UEL-1 was more productive regarding fresh pods, characterizing such genotype as more efficient for using the macronutrients. For both genotypes, N had the highest accumulation, followed by K, Ca, P, S and Mg.
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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".