Evaluation of Nutritional and Sensory Properties of Cocoa Pulp Beverage Supplemented with Pineapple Juice
Bibliographic record
Abstract
One of the major unutilized by-products of cocoa is cocoa mucilage (pulp). Cocoa pulp can be fortified with nutrients such as vitamins from other sources or the juice can be blended with other fruit juices from fruits such as pineapple that are good sources of vitamins. The objective of this study is to produce Cocoa pulp beverage supplemented with pineapple juice. Cocoa Pulp (CP) was used to replace Pineapple juice (PJ) at 0, 50, 60 70, 80, 90 and 100% levels. The nutritional and sensory properties of the CP+PJ beverages were evaluated. The CP beverage contained increasing levels of calcium, iron, fat and phosphorus with increased levels of CP in the blend but lower amounts of protein, carbohydrates and vitamin C than the PJ. In the CP+PJ blends there were not any significantly effect on the pH, ash and crude fiber contents. However, Titratable Acidity increased from 5.43 to 5.92%. Of all the blends, the 50% PJ mixture received the best evaluation from panelists-higher sensory ratings-next to the 100% PJ that was the best performer in the tests. Incorporation of cocoa pulp in the new beverages added value to the cocoa by-product and offers new options of easy, convenient and highly nutritive beverages for children and adult at the local level.
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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".