Characterization Of Coconut Oil (Cocos Nucifera L.) From Commonly Cultivated Kenyan Varieties Extracted by Different Methods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The objective of this study was to characterize the effects of different extraction methods and varieties on the extraction yields and quality profile of the resultant coconut oil. Three mature coconut varieties (East Africa Tall, Tall Yellow and Dwarf) were collected and subjected to different oil extraction techniques (traditional method, modified traditional method, mechanical expression and soxhlet method). The quality characteristics of the oil were determined using established standard protocols. Soxhlet extraction exhibited the highest oil yield ranging from 45.4% to 58.4% followed by mechanical expression (39.2-50.1%) and the least was traditional extraction method (6.3 to 10.2%) yield depending on variety. The Dwarf variety gave significantly lower yields compared to the other varieties. The quality characteristics were within codex standards except for the high levels of free fatty acid in traditionally (0.42%) and mechanically (0.33%) extracted oil. Lauric acid was the dominant fatty acid at 47.5%-53.5% followed by myristic acid at 15.3-18.5% depending on variety and the method of extraction. The % saturated fatty acid in all varieties was >90%. Unlike in previous studies, arachidic acid was present in all varieties. The study has demonstrated that extraction methods and variety influence the oil yield and quality characteristics of coconut oil.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 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 it