Physicochemical and sensory characteristics of commercial, frozen, dry, and wet-aged Hanwoo sirloins
Bibliographic record
Abstract
Objective: The objective of this study was to evaluate the physicochemical, sensory and taste characteristics of commercial, frozen, dry, and wet aged Hanwoo sirloin. Methods: Grade 2 sirloin from 6 Hanwoo steers (about 30 months old) were obtained after 5 days postmortem. Samples assigned into the following four groups commercial beef (CON), frozen beef (HF/40 days in -18°C freezer), wet-aged beef (HW/21 days), and dry-aged beef (HD/40 days) were stored in a 80±5% relative humidity cooler at 1 °C. Results: The HF group showed a significantly higher cooking loss and expressible drip with significantly higher pH compared to other groups. In addition, protein and fat contents in the HD group were higher than those in other groups (p < 0.05). The shear forces in the HW and HD groups were significantly lower than those in the CON group. The HD group had significantly higher omega-3 and polyunsaturated fatty acids compared with other groups. Glutamic acid levels in the HD group were significantly higher compared with those in other groups. Electronic tongue analysis revealed that sourness of the HD group was lower than that of other groups, whereas the HD group showed significantly higher umami, richness, and saltiness compared to other groups (p < 0.05). Sensory test results revealed that the HW group had significantly higher tenderness, while the HD group had significantly higher chewiness, juiciness, and overall acceptability scores. Conclusion: These results suggest that both wet- and dry-aging treatments can effectively improve sensory characteristics, and dry-aging was much more useful to enhance umami tastes and meat quality of 2 grade Hanwoo sirloins.
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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".