Effect of ripening stage on aliphatic alcohol, 4‐monomethylsterol and 4,4‐dimethylsterol compositions of <i>Pistacia lentiscus</i> fruit (lentisc)
Bibliographic record
Abstract
Fruits were collected from Pistacia lentiscus trees at five distinct stages of development, and lipid extract composition of 4‐monomethylsterols, 4,4‐dimethylsterols, and aliphatic alcohol was identified and quantified using GC‐MS. Four triterpene alcohols and two 4‐methylsterols were identified by GC‐MS during the ripening of the lentisc fruit. Cycloartenol is the major component of the 4,4‐dimethylsterol fraction with up to 1093 mg/100 g of oil in the 25th DAF. The accumulation of monomethylsterols begins at 60th DAF and peaked in the 75th DAF. Furthermore, thirteen aliphatic compounds including seven belonging to the policosanol group have been identified and quantified in Pistacia lentiscus oil. During the early stages of lentisc fruit ripening, the aliphatic alcohol fraction contains predominantly policosanol molecules which are highly prized by the food and pharmaceutical industries for their therapeutic and nutritional value. Practical applications: One of the main objectives of industry is to identify plant matrices rich in molecules with good nutritional value such as 4‐monomethylsterols and 4,4‐dimethylsterols. This study allowed identification and monitoring of the dynamics of accumulation of the lentisc unsaponifiable fraction (4‐monomethylsterols, 4,4‐dimethylsterols, and aliphatic alcohols), which should contribute to determination of the maturation stages corresponding to the threshold accumulation of certain molecules with good nutritional value. Evolution of 4‐monomethylsterol, 4,4‐dimethylsterol, and aliphatic alcohol composition during maturation of Tunisian Pistacia lentiscus fruit was determined using GC‐MS methods.
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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) | 0.002 | 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".