Improvement in the Extraction of Hass Avocado Virgin Oil by Ultrasound Application
Bibliographic record
Abstract
The virgin oil extraction from avocado Hass was carried using an Abencor pilot scale plant.High-power ultrasound (1.73 MHz) was applied after mixing. High-frequency ultrasound device consists of two transductors which each deliver 30 W/L.Different proportions of water were added before ultrasound treatment (no water added and paste:water relation (1:3, 1:2, 1:1, 2:1, 3:1) and also different ultrasound application times (0, 1, 2, 3, 4, 5, 10, 15, 20 and 25 minutes). The study was carried out by setting one of the two variables considered and changing the values of the other. In the water addition study, ultrasound time was set at 15 min.It was found that oil recovery increased with the percentage of water added. It was decided to employ a ratio of 1:1 to study the influence of ultrasound application time. Under these conditions, it was found that with 1 minute of ultrasound application, recovery increased by 40 % over the process without ultrasound.It was observed that the composition in fatty acids and the content of natural antioxidants (tocopherols and polyphenols) are not affected by the ultrasound application.It is concluded that the application of high-frequency ultrasound with addition of water post malaxing improves recovery of virgin avocado oil without negative effects on the general quality of the oil.
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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 | 0.001 |
| 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) | 0.001 | 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".