Study of the Nutritional Increase in Organic Composts Obtained by Aerobic Biostabilization in the Management of Food Wastes
Bibliographic record
Abstract
Composting is a sustainable alternative regarding an environmentally appropriate management of the organic fraction contained in the municipal solid wastes. To minimize nitrogen losses during the biostabilization process, due to ammonia volatilization, the present study aimed to evaluate the composting technique combined with the possible precipitation of struvite (MgNH4PO4.6H2O). A mixture containing food wastes was subjected to different experimental composting conditions with synthetic chemicals of magnesium and phosphorus—0.020 mol kg-1 (EXPI) and 1.8 mol kg-1 (EXPII), in addition to the control treatment (CONT). Experiments were carried out in closed systems, under forced aeration, over a period time of 56 days. In general, the addition of synthetic chemicals provided a nutritional increase in the organic composts obtained at the end of the experimental period in both conditions (EXPI and EXPII) compared to the treatment CONT. It was observed a total nitrogen conservation of about 21% and 122% in samples of composts obtained under the conditions EXPI and EXPII, respectively. Germination tests of lettuce seeds (Lactuca sativa) were also carried out to evaluate the agricultural applicability of the composts obtained in comparison with a commercial substrate (COM). A germination index with an average value of 87% was reached with the use of 100% of the compost obtained under the condition of greater conservation of total nitrogen (EXPII). Finally, the strategy considered for the conservation of nutrients in organic composts showed technical feasibility, indicating the formation of struvite and/or its analogues in the products obtained.
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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 | 0.001 | 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 | 0.000 | 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".