Characterization of volatile compounds of Daucus crinitusDesf. Headspace Solid Phase Microextraction as alternative technique to Hydrodistillation
Bibliographic record
Abstract
BACKGROUND: Traditionally, the essential oil of aromatic herbs is obtained using hydrodistillation (HD). Because the emitted volatile fraction plays a fundamental role in a plant's life, various novel techniques have been developed for its extraction from plants. Among these, headspace solid phase microextraction (HS-SPME) can be used to obtain a rapid fingerprint of a plant's headspace. Daucus crinitus Desf. is a wild plant that grows along the west coast of Algeria. Only a single study has dealt with the chemical composition of the aerial part oils of Algerian D. crinitus, in which isochavicol isobutyrate (39.0%), octyl acetate (12.3%), and β-caryophyllene (5.4%) were identified. Using GC-RI and GC-MS analysis, the essential oils and the volatiles extracted from separated organs of D. crinitus Desf. were studied using HS-SPME. RESULTS: GC-RI and GC-MS analysis identified 72 and 79 components in oils extracted using HD and in the volatile fractions extracted using SPME, respectively. Two types of essential oils were produced by the plant: the root oils had aliphatic compounds as the main component (87.0%-90.1%), and the aerial part oils had phenylpropanoids as the main component (43.1%-88.6%). HS-SPME analysis showed a more precise distribution of compounds in the organs studied: oxygenated aliphatic compounds were well represented in the roots (44.3%-84.0%), hydrocarbon aliphatic compounds were in the leaves and stems (22.2%-87.9%), and phenylpropanoids were in the flowers and umbels (47.9%-64.2%). Moreover, HS-SPME allowed the occurrence of isochavicol (29.6 - 34.7%) as main component in D. crinitus leaves, but it was not detected in the oils, probably because of its solubility in water. CONCLUSIONS: This study demonstrates that HD and HS-SPME modes could be complimentary extraction techniques in order to obtain the complete characterization of plant volatiles.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".