Influence of Ascorbic Acid on the Color of Dehydrated Sweet Potatoes
Bibliographic record
Abstract
The objective was to evaluate the production yield and influence of the action of ascorbic acid on the color of dehydrated white and purple sweet potatoes produced in a semi-arid region. The experiment was carried out at the Laboratory of Technology of Products of Plant Origin (TPOV) of the State University of Montes Claros, Janáuba, Minas Gerais, Brazil. Sweet potato roots of the cultivars Brazlândia roxa and Brazlândia branco were used. To determine the action of ascorbic acid on the color of dehydrated white and purple sweet potato, a completely randomized design with 4 replications was used. Analysis of variance was performed in a 2 × 2 factorial scheme, with two cultivars (Roxa and Branca) and absence and presence of ascorbic acid. The results were submitted to statistical analysis using the Sisvar Software. The average yield of white potato was 23% and purple 18.41%. For the variable of soluble solids, no significant differences were observed between the varieties. The sweet potato cultivar Brazlândia Branca showed better yield when submitted to the drying process. The sweet potato cultivar Brazlândia, when submitted to the dehydration process, presented a more yellowish color, however, with less intense coloration in the presence of ascorbic acid.
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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".