Comparative Evaluation of Regenerative Capacity of Different Adsorbents and Filters for Degraded Frying Oil
Bibliographic record
Abstract
The quality of degraded frying oil using Magnasol and Filtrite adsorbents was evaluated. Level of adsorbents (1%, 2% and 3%), treatment duration (2min, 5min and 8min) and temperature (60°C and 160°C) were the processing variables considered. The maximum improvement was up to an extent of 7.0% to 8.8%, 15.2% to 18%, 11.7% to 14.6% and 4.5% to 5.9% for capacitance (C), viscosity (μ), photometric colour index (PCI) and free fatty acids (FFAs), respectively. Specific gravity (γ) and colour parameters (L*, a*, b* and ΔE*) showed no significant difference due to treatments. The interaction of temperature and adsorbent level showed a more pronounced effect. The use of an adsorbent with different filters in a device, used at the food service establishment to filter oil under high-pressure, improved oil quality except for FFAs. The maximum reduction in C, γ, PCI and FFAs varied between 5.1% to 42.6%, 7.4% to 33.3%, 7.8% to 62.7% and 0.5% to 4.4%, respectively, depending upon filtration treatment. Colour parameters and γ were not affected. Polishing of oil by circulating it through the device for up to 30min also provided improvement in γ, C, μ, PCI and FFAs in the ranges of 0.18–0.40%, 19.3–27.2%, 16.0–23.7%, 28.7–42.9% and 1.1–2.2%, respectively. The combination of active and passive filtration systems has good prospects for oil quality improvement.
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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 | 0.000 |
| 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".