Sensory, Microbiological, Biochemical and Physico-chemical Assessment of Freshness and Quality of Fresh Lake Malawi Tilapia (<i>Chambo</i>) Stored in Ice
Bibliographic record
Abstract
Sensory, microbiological, biochemical and physico-chemical methods were used to assess freshness and quality of fresh Lake Malawi Tilapia (Local name: Chambo) to compare their effectiveness and reliability. Fresh Chambo samples were rejected by the sensory panel after 16 days from day of catch with a strong linear correlation (P < 0.01, R 2 = 0.95) between sensory quality scores and storage time in ice. Highest bacterial load of 1.6×10 7 cfu/g, cfu/cm 2 was observed on day 15 coinciding with sensory rejection time. TMA-N and TVB-N for freshly caught fish was 0.7 and 5.1 mg/100g, which increased to 3.4 and 26.4 mg/100g respectively at the time of sensory rejection also correlating with increased bacteria load in the fish. Initial pH of the fresh fish muscle was close to neutral (6.47), and reached its lowest point (5.84) on day 16 which was sensory rejection time. Findings suggest that sensory evaluation is reliable in the absence of the other methods. TMA-N is not a reliable method for assessing freshness quality of Lake Malawi Tilapia due to insignificant readings. pH showed to be a quick freshness indicator with an understanding that muscle pH for live fish is generally neutral and increases as deterioration of the quality of fish progresses in storage. Rejection of fish samples before reaching unacceptable microbial limits in this study, underpins the need for using more than one method for accurate freshness and quality assessments of fresh fish.
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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 | 0.000 |
| 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".