Chemical study of vermicomposted agroindustrial wastes
Bibliographic record
Abstract
Purpose The disposal of solid waste is a serious environmental problem for humanity. Vermicomposting is used as one of the methods for recycling of organic waste, resulting in a humified material of great agronomic potential which promotes carbon sequestration when applied to the soil. The aim of this study was to evaluate the chemical characteristics of vermicomposts from cattle manure (CM), orange peel (OP) and filter cake (FC). Methods Three compost piles were set up, 2:1 OP + CM, 3:1 FC + CM and CM. The piles were initially composted for 60 days. Thereafter, earthworms were added to the piles to initiate the vermicomposting process. Results The pH and the organic carbon contents were above the minimum recommended values for organic fertilizers. The N content was below the minimum value but the C/N ratio was in the required range. The C/N values where lower in OP + CM and FC + CM than in CM. Further, the N contents of treatments were different with OP + CM having the highest value. The C/N ratios of the piles were 9.52, 9.62 and 11.03 for OP + CM, FC + CM and CM, respectively, and were lower than the maximum recommended value by the Ministry of Agriculture, Livestock and Food (Ministry of Agriculture 2009). Conclusion Thus, co-vermicomposting of filter cake and orange peel with cattle manure has the potential for application sustainable agriculture.
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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 | 0.001 | 0.001 |
| 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".