Liquid Carbon Dioxide Use in the Extraction of Extra Virgin Olive Oil From Olive Paste
Bibliographic record
Abstract
<p>In this study the use of liquid carbon dioxide, CO<sub>2</sub>, for extraction of oil from olive paste (<em>Peranzana cultivar</em>)<strong> </strong>were examined and extracted oil was compared with oils obtained by centrifugation, pressure and use of chemical solvent.</p> <p>It is well known that the use of CO<sub>2</sub> has many advantages: miscibility with a wide range of molecules, food safety, non-flammability, absence of residues in the extract, possibility of total solvent recovery and no production of olive mill waste water that are highly polluting for the environment and require expansive disposal.</p> <p>Samples were subjected to the following analyses: determination of Free Fatty Acids (FFA), Peroxides Value (PV), Spectrophotometric Indices, Fatty Acids Composition (FA), determination of biophenols content and determination of Volatile Organic Compounds (VOCs). All samples showed FFA, PV and ?K values within the limits established by law for extra-virgin olive oil. The use of CO<sub>2</sub> did not catalyze hydrolysis, oxidation and condensation of double bonds. Centrifuged oils and oils extracted with carbon dioxide presented the lowest PV and FFA values. Extraction with liquid carbon dioxide contributed to an increasing of phenolic content with a value of 270.5 mg/kg, a value twice that of the oils extracted with centrifugation (135.3 mg/kg) or pressure methods (173.2 mg/kg). Oil extracted with liquid carbon dioxide showed the greatest amount of t-2-octenal and t-2-heptenal, giving herbaceous and pungent notes. Moreover the presence of aromatic compounds such as limonene, generally absent in olive oils, was only detected in the sample extracted with liquid carbon dioxide.</p>
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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 | 0.004 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".