Performance Characterization of a Locally Developed Fish Smoke-Drying Kiln for Charcoal and Briquette
Bibliographic record
Abstract
Performance characterization of a locally developed fish smoke-drying kiln (10 kg capacity) was conducted using charcoal and briquette as fuel materials. Samples of fresh African Catfish (Clarias gariepinus) weighing1.03±0.24 kg, charcoal of tropical hardwood (Anthonotha macophylla) and briquette produced from a combination of saw dust, rice husk, coconut husk and palm kernel shell were procured and used for the study. A completely randomized design (CRD) with three replicates was employed for this study and LSD among treatment means determined at p ≤ 0.05. Data was collected on moisture content of smoked-dried fish, smoke-drying time, drying rate, energy expended, specific fuel consumption and energy efficiency of kiln. Results showed that the energy efficiency of kiln was 97.02% and 98.45% and specific fuel consumption was 2.57 and 4.20 for charcoal and briquette, respectively. The energy expended by charcoal and briquette fuel materials were 206 MJ and 249.6 MJ, respectively. The energy expended, energy efficiency and specific fuel consumption were higher for briquette than charcoal. The use of charcoal offered higher moisture removal and drying rate for smoke-drying process than briquette but no significant difference was observed. Conversely, using briquette fuel material required almost two extra hours to smoke-dry 1kg of catfish sample compared to using charcoal. Breakeven with charcoal as main fuel material for custom hiring of the smoke-drying kiln occurs at 952 hours vis-à-vis 998 hours when briquette is used. Economically, briquette compares closely with charcoal, and could be considered a good alternative fuel material for smoke-drying of fish. Future research should conduct organoleptic assessment on fish smoked with charcoal and briquette to ascertain consumer acceptability of the final produce.
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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 | 0.000 |
| 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) | 0.000 | 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".