Assessment of Potential for Biodiesel Feedstock of Selected Wild Plant Oils Indigenous to Botswana
Bibliographic record
Abstract
Biodiesel is attracting increasing attention worldwide as a blending component or a direct replacement of petroleum diesel fuel in transport sector.The challenge to scientists and engineers is to identify appropriate feedstocks for biodiesel production. The majority of potential feedstocks are edible species which are at the centre of the “fuel versus food” debate. It is therefore imperative for scientists and engineers to continue the search for biodiesel feedstocks that do not compete with food security. This work investigated some properties of selected wild plant oils to assess suitability as feedstock for biodiesel production. Properties reviewed include oil yield levels, oil acidity, percentage of free fatty acids and the level of energy content. The wild plant oils under review were extracted from Scelerocarya birrea, Tylosema esculentum and Ximenia caffra fruit seeds. In addition, Jatropha oil was analysed for purposes of comparison. Thermal properties of wild plant oils were compared with those of petroleum diesel. Results indicate that wild plant oils investigated had sufficiently high oil yield levels desirable for potential feedstocks for biodiesel production. The energy content levels of wild plant oils were marginally lower than that of petroleum diesel with a maximum variation of 5.7 MJ/Kg.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".