Effect of Glucosamine and Ascorbic Acid Addition on Beef Burger Textural and Sensory Attributes
Bibliographic record
Abstract
Aside from the possible health benefit of dietary consumption of glucosamine (GlcN), studies have also reported its flavour enhancing properties in varying food products. However, the impact of its inclusion on other quality attributes of meat products has been under-assessed. The present study examined the effect of the addition of ascorbic acid (0.1%) and varying levels of GlcN (0.75, 1.5 and 3.0%) on colour stability, textural as well as sensory attributes of beef burger. Except for L * (lightness) value, significant interaction ( p <0.01) between storage time and added ingredient was observed for all colour parameters ( a* ; redness, b* ; yellowness, chroma, and hue angle) in beef burger. Generally, although ascorbic acid preserved the colour attributes of beef burgers during storage, addition of GlcN resulted in the deterioration of these colour parameters. Whereas the present result did not confirm any flavour enhancing attributes of GlcN compared to control, GlcN improved beef burger’s yield and reduced product cook loss. However, level of GlcN above 1.5% resulted in significant flavour and textural deterioration (p<0.05), leading to decline in consumer acceptability of beef burger. This study showed that a moderate level of glucosamine could be used in meat products as a functional ingredient with some additional technological benefits and limited impact on sensory attributes. Ascorbic acid adequately protected the colour of beef burger during refrigerated storage.
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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".