Volatile Compounds, Profiles of Virgin Olive Oils Produced In the Eastern Morocco: Oxidative Stability and Sensory Defects
Bibliographic record
Abstract
Studies on flavor profiles of virgin olive oil (VOO) are becoming more and more numerous. The VOO aromas are determined by a mixture of chemicals in olive oil, which influence its quality. Various studies around the world have shown that the volatile compounds in VOO depend on the climate, cultivation and process. The present work is a first approach to compare volatile profiles of VOO largely produced in eastern of Morocco after 6 months of storage at ambient temperature in darkness. Oxidative stability measured by Rancimat method at 101C was also determined. VOO volatile profiles were examined using the solid-phase micro extraction fibre method (SPME) in conjunction with gas chromatography/mass spectrometer (GC/ MS). 84 volatile compounds were identified; they belong to various chemical classes, such as aldehydes, alcohols, esters, ketones, carboxylic acids and hydrocarbons. The main volatile compounds present in olive oil samples were compounds with 6 carbon atoms (C6) such as Hexanal, (E)-hex-2-enal, Z-3-Hexen-1-ol and 1-Hexanol. Ethanol and Z-3, 7-dimethyl-1, 3, 6-octatriene, methyl acetate and ethyl acetate were also found. In general, these compounds have been identified in all VOO analyzed samples. The chemical compositions of the analyzed virgin olive oil headspaces evidenced that the most representative compounds In Isly and Kenine were carboxylic acids accounted for 59.24%-49.7% respectively, whereas the volatile fraction of the oil from Achajara almoubaraka showed significantly higher amounts of the alcohols (46%). Concerning oxidative stability, Isly and Kenine OO, have lower stability values compared to Achajara almoubaraka. Their potential oxidative susceptibility is therefore much higher than Achajara almoubaraka.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".