Roasting Effect on the Nutritional and Cosmetic Potential of Citrullus Lanatus Kernels Oil
Bibliographic record
Abstract
The objective of this study was to evaluate the effect of roasting on the nutritional and cosmetic potential of oil extracted from kernels of C. lanatus, which is one of the most widespread Cucurbitaceae species in Sub-Saharan Africa. The dried kernels (DKO) and roasted kernels (RKO) oils were extracted by cold press and hot using hexane. The physicochemical properties of these oils were evaluated. The results showed that C. lanatus roasted kernels were important sources of lipids (40.12 %) and protein (37.50 %). Oil extracted by press was of high quality, compared to that extracted by hexane. The study of the roasting effect revealed that the physicochemical characteristics of DKO and RKO oils were significantly different, with the exception of their specific gravity (≈ 0.9) and their refractive index (≈ 1.47). The absorbance of the two oils decreased in the range of UV-A and UV-B wavelengths. Both oils had low oxalates content (≈ 0.05 %) and were free of phytates and cyanogenic glycosides. All these features suggest that the roasted kernels oil of the C. lanatus could be used in food and cosmetic industries.
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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 | 0.000 |
| 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".