Essential oil content, yield, and components from the herb, leaf, and stem of curly-leafed parsley at three harvest days
Bibliographic record
Abstract
Parsley (Petroselium crispum L.) is commonly used for its flavor, desired nutritional contents, and other health benefits. However, since the profile of a recently introduced curly-leafed parsley cultivar in Egypt has not been studied, an experiment was conducted to compare three harvest dates in terms of the weight, essential oil (EO) content and yield, and the concentrations of major components in the whole herb, leaf, and stem parts. The results showed that the highest herb and leaf yields were obtained from the second harvest, but the first harvest gave the highest stem yield. The highest EO content and yield were obtained from the first harvest. The major EO components obtained from the three parts were β-phellandrene, α-terpinolene, 1,3,8-p-menthatriene, myristicin, and elemicin. The highest concentrations of α-terpinolene, myristicin, and elemicin were obtained from the whole herb; but the highest β-phellandrene and 1,3,8-p-menthatriene were obtained from the leaf and the stem. The findings revealed that the yield, EO content and yield, and concentration of the major components varied with harvest day and part of the plant. These results can be used to determine when and where to extract EO to maximize the desired content, yield, or component.
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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 | 0.000 | 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 | 0.001 |
| 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".