Thai Purple Sweet Potato Flours: Characteristic and Application on Puffed Starch-Based Snacks
Bibliographic record
Abstract
Characteristics and properties of 4 Thai purple sweet potato flours, Maejo 343, Phichit 65-3, Phichit 290-9 and Torperk were determined in terms of native and pre-gelatinized flours. Color, physicochemical properties and antioxidant activity of native and pre-gelatinized flours depend on their varieties. All native flours showed low redness (a*) and blueness (-b*) values but high pasting properties. Pre-gelatinized flours had a unique purple color and high antioxidant activity. Flours produced by Phichit 65-3 showed a deep intense purple color, high anthocyanins and good antioxidant activity. Both native and pre-gelatinized Phichit 65-3 flours were used as the main raw materials of air-puffed pre-gelatinized flours with different ratios at 10%, 30% and 50%. Increasing the content of pre-gelatinized flours improved color, expansion and antioxidant activity of snacks. Low hardness (9.55-11.65 kg) was presented in all snacks prepared from sweet potato flours. Purple sweet potato snacks prepared from 50% pre-gelatinized flour had good appearance, light texture, high anthocyanins and high antioxidant activity. Results showed that Thai purple sweet potato flours can be used to produce healthy snacks with improved appearance and texture. They also have potential as sources of natural colorants and antioxidants in food products.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".