Variation of Fatty Acids and Vitamin E Composition in Seed Oils of Some Plant Species
Bibliographic record
Abstract
The composition of fatty acids (FA) and vitamin E in seed oils of Albezia lebbeck (AL), Citrus sinensis (CS), Terminalia catapa (TC), Tamarindus indica (TI) and Citrullus vulgaris (CV) was investigated. The oil yields were obtained by solvent extraction and analysed for fatty acids by Gas chromatography mass spectroscopy (GC-MS). The oil yields of the seeds were found to be AL 8.22± 0.55%, CS 20.00 ± 1.50%, TC 35.60 ± 1.60%, CV 24.00 ± 1.20% and TI 9.42 ± 1.30%. Both saturated and unsaturated FA were identified in all the seed oils with the latter being the predominant with 77.70% in CV, 60.76% in CS, 56.98% in AL, 54.58% in TC and 34.52% in TI. Vitamin E was highest in CV 27.51 ± 2.42mg/ml and lowest in TI 10.60 ± 1.50mg/ml. There was significant decrease in percentage saturated FA, increase in percentage unsaturated FA with increase in vitamins E concentration in all the seed oils. The oils have many FA such as oleic acid, eicosadienoic acid and ?-linoleic acid which could be of biological and industrial significance to humans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".