Enhancing the quality and lipid stability of chicken nuggets using natural antioxidants
Bibliographic record
Abstract
BACKGROUND: Current day consumers prefer natural antioxidants to synthetic antioxidants because they are more active. However, the activity generally depends on the specific condition and composition of food. The aim of this study was to investigate the effect of wheat germ oil and α-lipoic acid on the quality characteristics, antioxidant status, fatty acid profile, and sensory attributes of chicken nuggets. METHODS: Six types of diets were prepared for feeding the chickens to evaluate the quality of nuggets made from the leg meat of these experimental animals. These included control, diet enriched with wheat germ oil (WGO), which is a rich natural source of α-tocopherol (AT), diet with added AT or α-lipoic acid (ALA), diet with a combination of either ALA and WGO (ALA + WGO) or ALA and synthetic AT (ALA + AT). ALA has great synergism with synthetic as well as natural AT (WGO). RESULTS: The diet with WGO and ALA showed the best potential with respect to both antioxidant activity and total phenolic content. HPLC results revealed that the chicken nuggets made from WGO + ALA group showed maximum deposition of AT and ALA. The stability of the nuggets from control group was found to be significantly lower than that of nuggets from the WGO + ALA group. Total fatty acid content too was higher in the nuggets from this group. The poly unsaturated fatty acids (PUFA) were found to be higher in the nuggets from the groups fed with a combination of natural and synthetic antioxidants. CONCLUSION: It is concluded that the combination of natural and synthetic antioxidants in the animal feed exerts a synergistic effect in enhancing the stability and quality of chicken nuggets.
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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".