Ultrasound, microwave, and their synergism assisted non-thermal isolation of pinto bean starch: Effects on physicochemical, techno-functional, rheological, and in vitro digestibility properties
Bibliographic record
Abstract
This study compared the non-thermal (<50 °C) effects of ultrasound, microwave, and their combination on starch isolation from pinto beans, along with the concurrent changes in the characteristic properties of the isolated starch. The conventional pH-shifting method was used as a control. Ultrasound and synergistic ultrasound-microwave treatments at optimum conditions enhanced starch recovery to 88 %, whereas microwave treatment, under its optimum conditions, achieved a recovery comparable to the control (81 %). Ultrasound and synergistic methods significantly increased amylose content, retrogradation tendency, solubility, swelling power, pasting viscosities, gel strength, and starch digestibility, while reducing thermal stability and crystallinity of isolated starch. However, ultrasound treatment alone induced stronger modulations. A single microwave treatment showed insignificant modification effects except for reduced pasting viscosity, crystallinity, and increased digestibility. The expected glycemic index (eGI) of pinto bean starch remained below 65 for all methods, with ultrasound and synergistic treatments resulting in the highest eGI. Thus, ultrasound and/or microwave technologies can isolate starch with distinct properties, potentially eliminating the need for additional modification steps for specific applications, thereby expanding industrial applicability.
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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".