Impact of Cassava Starch Varieties on the Physiochemical Change during Enzymatic Hydrolysis
Bibliographic record
Abstract
The enzymatic modification of starch extends its industrial use to flavor delivery and probiotic encapsulants, among other uses. However, it is not known how starch from different cassava varieties responds to enzymatic hydrolysis. Starches from two Ecuadorian cassava varieties (INIAP 650, an edible starch, and INIAP 651, an industrial starch) were partially modified at three enzymatic hydrolysis degrees (0%, 30%, and 50%), and their physicochemical properties were assessed. The structural analysis revealed that both varieties showed progressive structural damage as hydrolysis increases, probably due to exo-hydrolysis. However, deeper pores were observed in INIAP 651 with the SEM analysis. The crystallinity percentage obtained by XRD analyses remained constant in INIAP 651 and decreased (by 26%) in INIAP 650 (p < 0.05). In addition, the amylose−lipid complex index in INIAP 650 remained constant, while INIAP 651 increased (p < 0.05) at 30% hydrolysis (by 93%). In both varieties, hydrolysis increased (p < 0.05) the water holding capacity (WHC) (by 10−14%) and the water binding capacity (WBC) (by 16%), but 50% hydrolysis of INIAP 650 was needed to significantly affect these properties. No differences were observed in the varieties’ thermal properties. Regarding the rheological properties, the variety did not influence the changes in the storage module (G′) and the loss modulus (G″) with the hydrolysis (p > 0.05). However, the phase angle decreased significantly (p < 0.05) with the hydrolysis, being higher in the INIAP 650 variety than in the INIAP 651 variety. In general, the results indicate that the variety affects the response of the starch granule to enzymatic hydrolysis (noticeable in the principal component analysis, PCA) and opens up the possibility to modulate starch properties.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".