Optimization of the Rheological and Sensory Properties of Stirred Yogurt as Affected by Chemical Composition and Heat Treatment of Buffalo Milk
Why this work is in the frame
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Bibliographic record
Abstract
<p>The effects of fat content and the supplementation of milk with Sodium Caseinates (SCN) and Whey Proteins Concentrates (WPC) on the rheological and sensory properties of stirred yogurt made from buffalo milk were investigated. Whether the heat treatment of the milk affected the rheological behavior and the sensory characteristics of the samples was also evaluated. Principal Component Analysis (PCA) was used to assess in detail the relative contribution of whey proteins, caseins and fat on the rheological properties and sensory characteristics of the samples. Furthermore, it related the instrumental and objective sensory data to consumer perception (hedonic response of non-trained panelists). The objective acidity and white color intensity were positively correlated and increased with increasing casein content. Fat interacted synergistically with caseins to increase all the hedonic attributes, apart from odor. As far as rheological properties are concerned, elastic modulus (G'), instantaneous elasticity (G<sub>g</sub>), retarded elasticity (G<sub>R</sub>) and Newtonian viscosity (?<sub>0</sub>) were positively correlated with increasing casein content. However, tan ? was negatively correlated with the aforesaid attributes and increased with increasing fat content. Whey proteins in the presence of fat determined the magnitude of flow behavior index (n). The lactic acid concentration (%) and the b component of color (yellow color intensity) were affected positively by SCN and WPC addition but in the absence of fat. In all regression equations the effect of process temperature was found to be insignificant. Finally, the consumer-optimized composition of the fat and the added SCN can be used to formulate a marketable product.</p>
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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 | 0.000 | 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) | 0.000 | 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