Enzymatic Inter‐Esterification of Binary Blends Containing <i>Irvingia gabonensis</i> Seed Fat to Produce Cocoa Butter Substitute
Bibliographic record
Abstract
In order to investigate Irvingia gabonensis seed fat (IGF) as a potential cocoa butter alternative (CBA), its melting behavior is first compared to that of cocoa butter (CB). It is then modified by blending 90% of this fat with 10% of a liquid oil either rapeseed oil (RO) or groundnut oil (GO) or palm super olein (PSO) or Dacryodes edulis pulp oil (DPO). Those blends are then enzymatically interesterified in order to improve their melting profiles. The binary blend that shows a similar profile with CB and palm kernel stearin (PKS) is chosen as the best potential new speciality fat. Compatibility between the new speciality fat and CB is evaluated by constructing phase diagrams from NMR and XRD data. The interesterified blends with 90% of IGF and 10% of DPO is chosen as the new speciality fat because its profiles is close to that of CB and shows similar characterics to PKS. The results indicate that the specialty fat produced from IGF and DPO could be used as CBS in confectionery industries (alone or mixed in low proportion with CB). Practical Applications: Fractionnated and/or hydrogenated lauric fats are frequently used by confectionery industries to substitute CB. Results from this study demonstrate that an interesterified blend made of 90% IGF and 10% of DPO can be used also as CBS. The use of these two tropical oils (Irvingia gabonensis seeds fat and Dacryodes edulis pulp oil) as new sources of CBS constitutes a promizing way for their valorization at an industrial scale. Irvingia gabonensis seed fat (IGF) is a naturel lauric fat source with a high quantity of lauric acid (≈37%). Its melting profile, which is similar to cocoa butter (CB), is too high for a direct use in its native state in confectionery application. When IGF is blend to Dacryodes edulis pulp oil and after enzymatically interesterified, its profile is close to that of CB. This result indicated that the interesterified blend can be used as cocoa butter subtitute in confectionery industries (alone or mixed in low proportion with CB).
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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".