Impact of processing on the in vitro protein quality, bioactive compounds, and antioxidant potential of 10 selected pulses
Bibliographic record
Abstract
Abstract Pulses are consumed worldwide with different processing methods, which may impact their digestibility, protein quality, and composition. This study aims to analyze the effect of extrusion, baking, and cooking on protein nutritional parameters; bioactive compounds; and the impact on antioxidant capacity (AOX) of 10 selected pulses. Sodium dodecyl sulphate‐polyacrylamide gel electrophoresis (SDS‐PAGE) revealed that thermal processing causes modifications to the main storage proteins in pulses. Heating decreased saponin content from 12% to 44% in most heat‐processed samples; phytates were reduced 30%–84%, and polyphenol content decreased 28%–66%. In addition, the in vitro protein digestibility (IVPD) was enhanced 2.5%–9.5%, 3.5%–10.7%, and 2.2%–8.4% by extrusion, cooking, and baking, respectively. AOX showed an improvement in all processed samples (compared to raw flour) evaluated by the 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) method and by the oxygen radical absorbance capacity (ORAC). Fe2+ chelation showed that extruded and baked chickpea exhibited a decrease in IC50 by 40% and 70%, respectively. Extruded green and yellow split pea presented the highest Fe2+ chelation, improving by 11%–17% and 13–80%, respectively, when compared to the raw samples. Reducing power was enhanced by 26% in extruded chickpea, 18% and 29% in extruded and baked faba bean, respectively, and 50% in baked navy bean, when compared to the raw samples. Extrusion showed the highest β‐carotene AOX improvements (IC50 90%–96%). In this study, it was demonstrated that pulses AOX attributes can be enhanced by thermal processing; however, this will depend on the legume species and heating process applied. Furthermore, cooking seems to be the most effective thermal method to decrease saponins and phenolics, while extrusion reduced effectively phytic acid on bean samples, and cooking for the rest of pulses. All heating treatments affected positively IVPD, while the highest in vitro protein‐digestibility corrected amino acid score (IVPDCAAS) values were observed for baked pulses. Employing adequate processing methods represents an effective strategy to improve the digestibility of their proteins, as well as increasing the antioxidant potential of the resulting ingredients.
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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".