Alkali-aided protein extraction from chicken dark meat: Textural properties and color characteristics of recovered proteins
Bibliographic record
Abstract
Textural properties, water-holding capacity, and color characteristics of alkali-extracted chicken dark meat have been studied. Alkali extraction was carried out at 4 different pH values (10.5, 11.0, 11.5, and 12.0). At higher pH of extraction, cooking loss and water loss were found to be significantly decreased (P < 0.05). The lightness (L* value) of the recovered samples treated at higher pH was found to be significantly lower (P < 0.05). Whiteness of uncooked samples also decreased significantly at higher extraction pH values. Protein samples extracted at higher pH values were found to be harder, and the maximum (4,956 g of force) value was shown by samples prepared at pH 11.5. Chewiness values were significantly increased (P < 0.05) for protein samples extracted at pH values of 11.5 and 12.0. Dynamic viscoelastic behavior of samples was assessed in the temperature range of 7 to 100 degrees C. The dynamic viscoelastic behavior of raw chicken dark meat as revealed by storage modulus indicated considerable gel-forming ability. The maximum storage modulus (G') value of 439 kPa was measured at 66.7 degrees C. Storage modulus was found to decrease for the recovered protein samples and be lowest at higher pH values. However, the recovered protein samples did show substantial gel-forming ability when stored with cryoprotectants. Tan delta values denoted 2 clear transitions for raw dark meat; however, only 1 major transition at 50.1 degrees C was evident for pH-treated samples, probably reflecting the loss of collagen in processing. In conclusion, this process of protein recovery may offer the possibility to use the underused poultry resources for preparation of functional foods.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".