Effect of saturated and unsaturated fat on the physical properties of plant-based cheese
Bibliographic record
Abstract
In many plant-based meat and dairy alternatives, coconut oil is frequently used to replicate the textural and structural properties of animal fats due to its high saturated fat content. Concerns about the health implications of saturated fat and the sustainability of coconut oil call for an exploration into alternative fat combinations in plant-based foods. The effects of saturated fatty acid (SFA) content on plant-based cheese physical characteristics were evaluated through five different ratios of coconut oil (CO) to sunflower oil (SO): 100%, 90%, 75%, 60%, 50%, 40%, 25%, 10%, and 0%. As determined through texture profile analysis, the hardness of the cheeses after setting at 5°C for 24h increased with increasing amounts of coconut oil due to the increasing solid fat content providing additional firmness. The samples with 100% coconut oil displayed satisfactory melt and stretch; however, the melt and stretch values were matched by adding as little as 25% sunflower oil. The melt and stretch values did not continue to increase with increasing saturated fat content but instead remained constant with increasing coconut oil addition. Rheological analysis of the cheeses during a temperature ramp from 20 to 95°C was assessed where the tanδ value at 95°C was used as a measure of cheese melt, where values ≥ 1 indicated a better melt. The 0% coconut oil cheese had the lowest tanδ (G″/G′) value of 0.3, whereas the addition of 25% coconut oil into the cheese resulted in the tanδ increasing to values greater than 0.5. The 25% CO cheese sample also achieved a more similar complex viscosity (η*) to that of dairy cheese than all samples but the 75% CO cheese. Therefore, there is an opportunity to decrease the amount of coconut oil in plant-based cheese systems while maintaining good functional properties and improving the sustainability and health benefits of the final product. • Dairy cheese is mimicked by plant-based cheese using plant protein and waxy starch. • Starch gelatinization and retrogradation are modulated through heated mixing. • New product with better melt, stretch, and nutrition than commercial products. • Plant-based cheese can match the mechanical properties of conventional dairy cheese.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".