Production of Arugula Under Doses of Bokashi Fermented Compound
Bibliographic record
Abstract
Fermented composts are made from animal, plant and or/mineral materials. The fermentation process can be accomplished through the action of microorganisms collected from soils, plant litter and/or baker’s yeast. This study aimed to evaluate arugula (Eruca sativa) yields with application of different doses of bokashi-type fermented compost. The experimental design consisted of randomized blocks with five treatments (0, 100, 200, 300, 400 g m-2) and four replications. Fermentation of the compost occurred in ten days, and in this period the compost mass was turned up twice a day during the first three days and daily during the seven next days. The fertilizer was incorporated three days before planting into a 0-5 cm deep layer. The methods used for data analysis were ANOVA and regression analysis at 5% probability level. The variables examined were: number of leaves, plant height, dry and fresh weight of roots and shoots. The use of bokashi at the rate of 300 g m-2 resulted in better agronomic performance, demonstrating to be a viable alternative for the production of arugula under local edaphoclimatic conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".