Potato starch nanocrystal preparation via supercritical carbon dioxide pretreatment combined with enzymatic hydrolysis
Bibliographic record
Abstract
In this work, starch nanocrystals were successfully produced from downgraded potatoes using enzymatic hydrolysis combined with a supercritical carbon dioxide pretreatment to improve the accessibility of the enzyme to the starches. Enzymatic hydrolysis was carried out using the pullulanase enzyme at a temperature of 60 °C and a pH of 4. Following hydrolysis, the starch nanoparticles were recovered via precipitation and recrystallization. Comparative characterization of the native, supercritical carbon dioxide-pretreated, and hydrolyzed-recrystallized starch materials was conducted via transmission electron microscopy, scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray diffraction. The scanning electron microscopy images revealed alterations, e.g., layered strips, on the surface of the potato starch granules after the supercritical carbon dioxide pretreatment. The transmission electron microscopy images revealed that spherical nanostructures from 80 nm to 150 nm were successfully produced. The Fourier transform infrared spectroscopy spectra displayed several absorption bands corresponding to the molecular structure of starches. The X-ray diffractograms exhibited a typical B-type scattering pattern for all the samples. In addition, it was found that the crystallinity of the potato starch nanoparticles was considerably increased compared with native starch.
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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) | 0.000 | 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 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".