Effect of Incorporation of whey Protein Concentrate on Quality Characteristic of Buffalo Meat Emulsion Sausage
Bibliographic record
Abstract
Incorporation of whey protein concentrate (WPC) at a level of 1, 2, 3 and 4% in buffalo meat was investigated for production, quality characteristic of emulsion sausage (ES). Quality of emulsion sausage was evaluated in terms physicochemical characteristics like moisture content, pH, protein content, water holding capacity (WHC), Extract release volume (ERV), microbiological characteristics like total plat count (TPC) and Yeast and mold count, and sensory characteristic including instrumental colour measurement. It was found that moisture content, protein content, ERV and WHC were significantly (P<0.05) increased in emulsion sausage as result of incorporation of 1-4% of WPC. Addition of 1-2% WPC decreased the pH. However 3-4% addition of WPC caused no change in pH and it remained comparable the pH of the control sample. TPC of ES was found in range of 6.23-6.37 log cfu/g. Emulsion sausage incorporated with whey protein concentrate was acceptable to the panelist. The numerical value of ‘L’ for the samples in fresh condition found in the range of 29.50%- 33.25%. Thus sample had 33.25 % of maximum lightness as compared to 66.75% darkness. The sample of fresh emulsion sausages was greyish brown colour in appearance.
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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) | 0.000 | 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) | 0.001 | 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".