Reduction of antinutrients and off-flavour in kidney bean flour by acidic and alkaline reactive extrusion
Bibliographic record
Abstract
The presence of antinutrients and undesirable flavours in kidney bean flour poses challenges to consumer acceptance. Although extrusion can mitigate antinutrients to some extent, its impact on reducing beany flavour in bean flour remains underexplored. This study investigated the effects of injecting acetic acid or sodium carbonate solutions at three concentration levels (0.05, 0.1, 0.15 mol/L), in conjunction with three temperature profiles (40/60/80/80/90, 40/60/80/90/110, 50/70/90/110/130 °C) and two feed moisture levels (25, 30 %), on the removal of antinutrients (condensed tannins, trypsin inhibitor activity, phytic acid, raffinose family oligosaccharides) and reduction of volatile compounds that contribute to beany flavour in whole kidney bean flour. The results showed that all concentrations of acetic acid and sodium carbonate solutions effectively reduced condensed tannins compared to water, especially at 130 °C extrusion temperature. Introducing acetic acid and sodium carbonate solutions at a concentration of 0.15 mol/L led to 72 and 90 % reduction of total raffinose family oligosaccharide content, respectively, in contrast to the 17 % reduction observed with water alone. The incorporation of sodium carbonate solution reduced the total volatile compounds by 45-58 % as compared with water (23-33 %) and acetic acid (11-27 %). This reduction was primarily due to the reduction of aldehydes, alcohols, and aromatic hydrocarbons. These results indicate that injecting sodium carbonate solution during extrusion can effectively reduce antinutrients and beany flavour compounds in kidney bean flour.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".