Using Canola Oil Organogels as Fat Replacement in Liver Pâté
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Bibliographic record
Abstract
Five canola oil organogel formulations were used to replace pork fat in pâtés to increase unsaturated fat content, and to determine their effects on texture and sensory properties. While pâtés made with canola oil were softer than the control pork fat product at room temperature, pâtés made with gelled canola oil (organogel pâtés) had similar hardness values to the control. Back extrusion results (also a measure of spreadability) showed that pâté made with canola oil only was softer than the control at 4 °C, but the pâtés made with organogels were similar to the control. Organogel pâtés were perceived to have similar sensory hardness, oiliness, and juiciness as the control. Pâtés made with organogels showed higher oil loss, over time, compared to control; however, pâtés made with organogels containing glycerol monostearate showed lower oil loss after 24 hr (P < 0.05) compared to the other organogel treatments. Light microscopy showed that fat globule size was notably larger in pâtés made with organogels than in the pork fat and the canola oil control pâtés. The color of organogel pâtés was darker compared to pâtés made with pork fat or canola oil only. Sensory data showed that all fat replaced pâtés had very similar flavor profiles. Overall, organogel pâtés showed comparable textural, physical, and sensory properties to the traditional pâté made with pork fat, while reducing the saturated fat content by 60%. PRACTICAL APPLICATION: Use of vegetable oil in highly emulsified liver pâté has been shown to be possible via the use of organogels prepared with ethylcellulose. This has been a challenge because some of the meat proteins are heat denatured prior to the emulsification process. Overall, the use of organogels, with specific hardness and oil retention values, is possible as demonstrated in this publication.
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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