Influence of Salt and Millet Treatments during Meat Fish Fermentation in Senegal
Bibliographic record
Abstract
Microbial growth in meat from traditional handled Arius heudelotti fish during fermentation at 25-30°C in Senegal has been determined. Microorganisms involved in fermentation and pathogen microorganisms were analyzed in function of salt and millet addition [1/1 (w/v)]. Total viable microorganisms, lactic acid bacteria, H2S-producing Enterobacteriaceae, staphylococci, fungi and spore-forming bacteria counts in the crude meat fish reached 6.34 ± 0.28, 4.10 ± 0.61, 4.33 ± 0.45, 3.71 ± 0.69, 1.50 ± 0.3 and 1.33 ± 0.58 Log10 CFU/g. H2S-producing bacteria predominated (8.3 ± 0.25 Log10 CFU/g) after 24 h incubation at 25-30°C of untreated meat fish or that immersed in saline [14% NaCl (w/v)]. The pH of raw meat fish was 6.32 ± 0.1. It increased during unsalted fermentation, while it slightly decreased for the saline procedure. Meat fish fermentation in salty water added with NaCl at 80% (w/v), widespread in Senegal, allowed weak acidification in addition to growth inhibition of H2S producing Enterobacteriaceae which dropped to 3.53 ± 0.45 Log10 CFU/g after 24 h of fermentation. The fish fermentation in water added with malted millet flour at 15% (w/v) enabled significant growth of lactic acid bacteria and pH dropping to 4.9 ± 0.19. SH2-producing Enterobacteriaceae, Staphyloccoci and spore-forming bacteria showed a weak growth in the meat fish significantly acidified in millet solution, indicating preservative factor improvement when compared to the abusive salting traditional procedure which is a dietetic concern.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".