Breadmaking Potential of Andean Roots and Tuber Starches from Ahipa (<i>Pachyrhizus ahipa</i>), Oca (<i>Oxalis tuberosa</i>), and Arracacha (<i>Arracacia xanthorrhiza</i>)
Bibliographic record
Abstract
Abstract Aim is to explore the breadmaking potential for gluten‐free goods of non‐conventional starches from Andean crops ahipa, oca, and arracacha. Their characteristics and performance in breadmaking are compared with those of cassava, taken as a reference for conventional gluten‐free root starch. Physicochemical properties of breads are studied along with the pasting and thermal properties, composition, and α‐amylase hydrolysis of starches. Arracacha starch has the lowest amylose content (2.4%) and the highest water hydration (1.4 g g−1). Its batter shows adequate proofing, but the bread is highly adhesive, with dense crumb. Ahipa starch paste has the lowest peak, trough and final viscosities determined by rapid visco analyzer, and the highest hydrolysis rate (kRVA = 2.30 min−1). Its batter exhibits, along with oca, the highest volume increase during fermentation (193–197%), but structure collapses in the oven and no alveoli are observed in the crumb. Conversely, oca forms a crumb structure similar to cassava, but with higher cell density (131 alveoli cm−2), cohesiveness (0.95), and resilience (0.65) than the latter (71 alveoli cm−2, 0.88, and 0.45, respectively). Oca starch has lower pasting temperature (64 °C) and the starch paste has similar hydrolysis rate (kRVA = 1.92 min−1) compared to cassava (71.9 °C and 2.08 min−1, respectively), making it a suitable option for providing gluten‐free yeast‐leavened breads with improved technological properties and a comparable glycemic index.
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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".