Conventional and Ultra-fast Analysis Exposing the Harvest Date Impact on Lebanese Olive Oil: The Soury Variety
Bibliographic record
Abstract
The impact of harvest period on the quality parameters, polyphenols, fatty acids, sterols, and volatile compounds of Lebanese olive oil from the Soury variety was investigated in this study. Two groups of olive oil were compared, each with a specific harvest date. HD1 was harvested in October, whereas HD2 was picked in November. The analysis of both olive oil categories showed that HD2 witnessed a significant increase in all quality parameters except K270 and a decrease in total polyphenol content from 138 mg/mL to 44 mg/mL. Oleic and linoleic acids had an inverse relation, where the former decreased and the latter increased with the harvest date’s advancement. Palmitic acid in both groups was higher than the standards set for extra virgin olive oil. The relative amount of β -Sitosterol was mainly found to decrease, while those of stigmasterol, ∆5,24 -stigmastadienol, ∆7 -stigmastenol, and ∆7 -avenasterol increased with delaying harvest time. As for the volatile compounds, principle component analysis was used on the flash GC data to differentiate HD1 from HD2. Ethanol was found mostly characterizing HD2, whereas HD1 was influenced by 1-hexanol and (E,E)-2,4-decadienal. It can be concluded that the Soury variety should be harvested early, and a delay would result in the declassification of Lebanese olive oil quality from extra virgin to virgin olive oil.
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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".