Chemical Characterization of Soil with Superficial Application of Avian Bed in Succession to Canola Cultivation
Bibliographic record
Abstract
Additions of poultry manure can promote improvements in the conditioning of the biological, physical and chemical properties of the soil. Thus, the present study aimed to evaluate soil chemical attributes through the superficial application of linear doses of chicken litter. The experimental design was a randomized block design, with 4 replicates and 7 treatments: T1: Witness (without application of avian bed), T2: 1 Mg ha-1, T3: 2 Mg ha-1, T4: 4 Mg ha-1, T5: 8 Mg ha-1, T6: 16 Mg ha-1, T7: 32 Mg ha-1 avian bed. The results indicate that the application of avian bed doses has an influence on K+ results, where intermediate doses as 12 and 18 ton ha-1 have higher results in potassium content in the analyzed soil. The doses of aviary bed alter the total organic carbon content. It can be said that higher doses of avian bed result in higher values of phosphorus and calcium. The calcium contents were higher than the magnesium content, potential acidity (H+ + Al3+) and Sulfur had a similar behavior to that of Calcium and Magnesium, a negative quadratic behavior. The values for pH measured did not vary greatly in relation to the doses of poultry bed applied and from the statistical data it was possible to determine that only pHCaCl2 had a significant difference. All other chemical attributes analyzed were not significantly influenced by the addition of the organic fertilizer when compared to the control, regardless of the application form in the soil.
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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".