Sensory Acceptability of Buffalo Meat and Beef in Young Consumers
Bibliographic record
Abstract
Background: The aim of this study was to evaluate the sensory acceptability of buffalo meat compared to beef, as well as to evaluate the perception of buffalo meat. Methods: The study was conducted with young meat consumers, who responded to a questionnaire with four sections: 1) sociodemographic aspects, 2) consumer preferences, 3) hedonic acceptability, and 4) perception of buffalo meat consumption. Three 2.5 cm thick steaks (Longissimus thoracis et lumborum) were compared: 1) select beef (slight marbling); 2) select buffalo meat (slight marbling); 3) prime beef (abundant marbling). The samples were evaluated by 76 young meat consumers (non-trained panelists). A seven-point hedonic scale was used to assess appearance, odor, flavor, tenderness, juiciness, and overall acceptability. Results: The results indicated that prime beef presented a better appearance (P=0.0042) and tenderness (P<0.0001) compared to select buffalo and select beef, respectively. Similarly, a higher score was observed in juiciness for prime beef (5.52±0.19 points), but a better score for buffalo meat compared to beef select was identified (4.52±0.18 points vs. 3.86±0.19 points, respectively; P<0.001). Most of the panelists indicated that prior to the study, they had not consumed buffalo meat (89.00%/n=68). However, they noted that buffalo meat was like select beef (71.00%/n=54). The panelist highlighted various reasons why buffalo meat is not commonly consumed, such as there is no information on the buffalo meat (93.42%/n=71), limited availability of buffalo meat products (60.52%/n =46), and unavailability at supermarkets (73.69%/n=56). Conclusions: Buffalo meat can be a good option for young consumers. However, more information about buffalo meat characteristics (chemical, nutritional, sensory properties, and technological quality) and improved marketing channels that ensure the availability of buffalo products are important.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".