Nutritional, organoleptic, and physical properties of biscuits made with cassava flour: effects of eggs substitution with kidney bean milk ( <i>Phaseolus vulgaris L</i> .)
Bibliographic record
Abstract
Common bean forms a significant part of the diet in Africa and hence plays a critical role in human nutrition. In order to promote it, this study was designed to investigate the effects of fully substituting eggs with bean milk on the physical, nutritional and organoleptic properties of biscuits made with cassava flour. Replacement of egg by bean milk increased the biscuits’ fat, carbohydrates, crude protein, and energy content. On the other hand, there were no significant differences in mineral contents between the cassava biscuits with eggs which served as the control and cassava biscuits with bean milk following substitution by bean milk. There was no significant difference (p < .05) in the Saponin and Phytate contents regarding anti-nutrients contents between bean milk and cassava bean milk biscuits. In contrast, Tannin contents were significantly higher in biscuits than in bean milk. Biscuit made with eggs, was rated as “very good,” while the test biscuits were rated as “good.” Substitution of egg by bean milk in cassava biscuits increased the biscuits’ protein, the fat, and carbohydrates contents with an appreciable taste. These biscuits made with bean milk can be used as a food supplement to help fight protein malnutrition in vulnerable groups.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Food science study of cassava biscuits with kidney bean milk substituted for eggs.
It studies the nutritional and sensory properties of biscuits, not research itself.
Food science study of cassava biscuits with bean milk substitution; nutrition product properties.
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) | 0.001 | 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".