Quantitative Descriptive Analysis and Acceptance Testing of Yogurt with no Added Sugar
Bibliographic record
Abstract
This study aimed to evaluate the effect of sucralose added in Greek Yogurt flavored with araticum (Annona crassiflora) and mangaba (Hancornia speciosa) through sensory characterization. The Greek yogurt was prepared with skimmed milk, inoculated starter cultures, filtered and it was supplemented with the appropriate amount of sucralose, added sweetened and pasteurized fruit pulp (araticum or mangaba). The total phenolic compounds and texture were performed and sensory analyses were carried out by Quantitative descriptive analysis (QDA) and acceptance test in storage for 7 and 28 days. The QDA results showed that the main attributes were color, lightness, creaminess, presence of particles, fullness, and aroma. Eighty percent and 85% of the panelists were said they would buy the araticum Greek yogurt and the mangaba Greek yogurt after 7 days of storage, respectively. Additionally, 71% and 77% were said they would buy the araticum Greek yogurt and the mangaba Greek yogurt after storage for 28 days at 4ºC, respectively. The sensory profile and acceptance test results of the Greek yogurts developed indicated no perceptions caused by adding sucralose to the yogurt after storage for different times. The highest concentration of phenolic compounds in the araticum Greek yogurt was perceived by the panelists in aroma and flavor attributes. Changing sucrose to sucralose was not imperceptible under the storage and consumption conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".