Microbiological Quality and Sensory Aspects of Greek Yoghurt With the Addition of Carambola Jam (Averrhoa carambola)
Bibliographic record
Abstract
The search for nutritious and practical foods during consumption is one of the challenges of the food industry and Greek yogurt with added fruit meets these needs. Therefore, the aim was to prepare Greek yogurt with the addition of different concentrations of carambola jam, as well as to analyze its microbiological quality and its sensory acceptance. Three formulations of Greek type yoghurts were prepared with the addition of different concentrations of star fruit jam F1 (10), F2 (15) and F3 (20)%, respectively, where they were subjected to microbiological analysis (coliforms at 45 °C, Estaf. coag.positiva (UFC/g) and Salmonella sp.) and sensory analysis, being analyzed the index of sensory acceptance and the intention to buy. The three formulations produced showed excellent microbiological results, that is, all the results obtained are within the standards established by current legislation. With regard to sensory analysis, the formulation F1 (10%) presented the highest acceptance rate in all sensory attributes, with higher values of AI above 85% and with purchase intention close to “certainly would buy the product”. Therefore, the yogurts elaborated in this research have the ideal microbiological safety for consumption, without compromising the consumer’s health and with excellent sensory acceptance
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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".