Characterization of the Fermented Milk “Laban” with Sensory Analysis and Instrumental Measurements
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Sensory, chemical, and rheological properties of commercial and traditional laban samples were investigated to characterize this fermented milk. One commercial sample and 14 traditional samples, collected from various geographical locations in Lebanon, were evaluated by a descriptive panel in terms of appearance, color, texture, odor, taste, and after‐taste. Principal component analysis of the sensory data revealed high differences between laban samples. They were separated into 5 distinct groups that were identified by the following sensory characteristics: firm and sour, slimy and sweet, high butter odor, high yogurt odor, and moderate levels for all the descriptors. Six samples, showing different features, were selected from these 15 samples. Physicochemical analyses of acidity, lactose and fat contents, firmness, and apparent viscosity were assessed on these 6 samples. Laban, independently of its origin, displayed higher acidity than yogurt. Commercial laban showed higher acidity and viscosity than traditional samples. Statistical relationships between sensory and instrumental data showed significant correlation between apparent viscosity and smoothness, fat content and butter odor, titratable acidity and sourness, and penetrometry readings and sliminess. Finally, principal component analysis of the instrumental and sensory parameters revealed that both analyses characterized the samples in the same way.
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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 | 0.001 |
| 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 it