Effect of Inoculum Size on The Composting of Greenhouse Tomato Plant Trimmings
Bibliographic record
Abstract
A laboratory-scale bioreactor was used to investigate the influence of inoculum size on the composting process of tomato remains-wood shavings mixture. Urea (as a nitrogen source) was added to correct the initial C: N ratio (30: 1). The average temperature in each bioreactor was strongly influenced by the size of inoculum. Maximum temperature of each mixture correlated with the reduction of Volatile solids (VS), total carbon (TC) and Total Kjeldahl Nitrogen (TKN). Volatile solids losses were in the range of 16.9-44.7 %, while total carbon losses were in the range of 9.4-28.4 % and TKN losses were in the range of 3.4-25.4 %. Neither the nitrogen nor the moisture content were limiting factors as the C: N ratio remained in the range of 28: 1 to 29: 1 and the moisture content remained within the optimum ranged of 57-61%. Carbon availability appeared to be the limiting factor in these set of experiments. Since wood shavings, which made 65% of the total mixture, contain no bioavailable carbon, another bulking agent should be considered. The addition of another source of readily available carbon to the tomato should also be investigated.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".