Functional properties of oleogels and emulsion gels as adipose tissue mimetics
Bibliographic record
Abstract
The demand for plant-based meat analogues continues to rise as consumers seek sustainable and healthier dietary choices. Currently, plant-based meat analogue manufacturers focus heavily on protein quality and content. At present, there is an emphasis on converting globular plant proteins to more meat-like, fibrous structures, while the fat portion of plant-based meat alternatives is not given adequate attention and remains subpar. To replicate the textural and sensory attributes of animal-based meat, the development of adipose tissue mimetics is essential, as adipose tissue is the primary fat store for meat. This narrative review investigates the concept of adipose tissue and explores various methods for creating adipose tissue mimetics using oleogel or emulsion gels. Adipose tissue is made up of an extracellular matrix which contains animal fat. Since the fat in animals is not “free,” adipose tissue retains its structural integrity after cooking, which contributes to its high resilience and ability to sustain its shape. Popular methods in creating adipose tissue mimetics, including the use of oleogels and emulsion gels, are discussed with examples from recent years, as well as examples of other, less common methods. Strengths and limitations of the various methods employed for creation of adipose tissue mimetics are carefully considered. Emulsion gels were able to maintain their solid-like behaviour even at elevated temperatures. Emulsion gels used more label-friendly gelling materials compared to oleogels which used the non-label-friendly ethylcellulose. Oleogels were however able to achieve the same oil content as well as hardness of adipose tissue in some samples. Both types of gels offered a customizable lipid profile, the ability to partially mimic TPA results of animal adipose tissue, and utilized plant-based sustainable and health-conscious ingredients. Based on this review, areas that need improvement include textural and rheological qualities like hardness, oil retention upon heating, preserving meat-like sensory properties in plant-based meat analogues, and finding consumer friendly ingredients. • There is an increasing demand for plant-based meat analogues for environmental and health purposes. • An improvement in plant-based meat analogues is needed in order to satisfy consumers. • An adipose tissue mimetic is needed to improve the fat portion of plant-based meat analogues. • A good adipose tissue mimetic could greatly improve the consumer acceptability of plant-based meat analogues. • Current research does not provide an adequate method for producing adipose tissue mimetics.
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How this classification was reachedexpand
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 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".