Analysis of Volatile Organic Compounds in Olive Oil of ‘<i>Koroneiki</i>’ with Different Maturity Indices by GC-IMS
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Bibliographic record
Abstract
This study aims to determine the optimal harvest period of olives by distinguishing the olive oils with different fruit maturity indices (MIs). Gas chromatography ion-mobility spectrometry (GC-IMS) technology was employed to qualitatively and differently analyze the volatile organic compounds (VOCs) of olive oil extracted from eight MIs of 'Koroneiki' olive fruits, harvested in Longnan City, Gansu Province, China. The results showed that 40 signal peaks were isolated in the eight olive oils with different MIs, and 33 VOCs were identified. These include alcohols (7 kinds), esters (7 kinds), aldehydes (6 kinds), ketones (5 kinds), acids (2 kinds), olefins (2 kinds), and other compounds (4). A total of 20 differential markers for key flavors, with variable importance in the projection (VIP) > 1, were screened out by orthogonal partial least squares - discriminant analysis (OPLS-DA). The results showed that the olive oil samples of the 7th maturity index (QJ7), QJ8, and QJ5, QJ6 have significant differences from the other four olive oils. This suggests that olive oils with different maturity indices can be effectively distinguished.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it