Methodology and development of a high-protein plant-based cheese alternative
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Animal-based food products, such as meat and dairy, contribute the most to greenhouse gas emissions in the food sector. This, coupled with the demonstrably worsening climate crisis, means that there needs to be a shift to more sustainable alternatives in the form of plant-based foods. In particular, the plant-based cheese alternative industry is relevant, as the products lack critical functionalities and nutrition compared to their dairy-based counterparts. Waxy starch, plant-protein isolate, and coconut oil were combined to create a novel high-protein (18% w/w) plant-based cheese alternative. We determined that when using native waxy starch, we can enhance its existing viscoelastic properties by modulating gelatinization through adding plant protein and fat. Texture profile analysis indicated that the cheese analogues could reach hardness levels of 15–90N, which allowed samples to be tailored to a broader range of dairy products. We determined that plant proteins and fat can behave as particulate fillers, enhance network strength, and create strategic junction points during starch retrogradation. The degree of melt and stretch of the high-protein plant-based analogues were 2–3 times greater than those observed for commercial plant-based cheese alternatives and significantly more similar to dairy cheese. The rheological melting kinetics saw that the high-protein plant-based cheese alternative displayed more viscous properties with increasing temperature. Tan δ (G”/G’) at 80 °C was used as an indicator for sample meltability where, values ≥1 indicate better melt and more viscous systems. The high-protein plant-based cheese alternative reached Tan δ values upwards to 0.7, whereas commercial plant-based cheese alternatives only reached tan δ values around 0.1. Ultimately, the novel high-protein plant-based cheese alternative demonstrates the use of simple ingredients to form complex food systems.
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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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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