Extraction of Avocado Seed Waste as a Potential Feedstock for Biodiesel Production
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 rising interest in sustainable energy sources has spotlighted biodiesel as a promising alternative to fossil fuels. Avocado seed waste, rich in vegetable oil, presents a potential feedstock for biodiesel production. However, optimizing the extraction process to maximize oil yield and quality is crucial. This study addresses the knowledge gap concerning the impact of drying time and solvent type on oil extraction efficiency from avocado seeds. Here, we show the effects of varying drying times (2, 3, and 4 hours) and using two solvents (96% ethanol and isopropyl alcohol) on the oil yield and quality using Soxhlet extraction. Results indicate increased drying time correlates with reduced moisture content, with values of 79.94%, 63.17%, and 47.39% for 2, 3, and 4 hours, respectively. Comparatively, isopropyl alcohol exhibited a higher fatty acid content (0.718%) than 96% ethanol. The density of oil extracted with 96% ethanol (1.34 g/ml) after 3 hours of drying surpassed that of isopropyl alcohol. These findings suggest that drying time and solvent type significantly influence the extraction efficiency and quality of oil from avocado seeds, highlighting their potential as a viable biodiesel feedstock.
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 | 0.000 | 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) | 0.000 | 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 it