Evaluating the breadmaking potential of wholemeal flours from einkorn, emmer, and spelt grown in the Canadian prairies
Bibliographic record
Abstract
Abstract Background and Objectives Ancient grains like einkorn, emmer, and spelt remain underutilized and underexplored, limiting their market potential. This study evaluates the chemical composition, rheology, pasting, and baking properties of spring growth habit einkorn, emmer, and spelt cultivars grown in the Canadian prairies compared to wholemeal and refined hexaploid wheat. Findings Einkorn cultivars (CDC Aixe and CDC Marval) had inferior dough mixing properties and the lowest bread loaf volume. CDC Tatra (emmer) bread had a significantly (p < .05) higher specific volume (3.32 mL/g) than Canada Western Red Spring (CWRS) wholemeal bread. Conclusions Results from mixing and baking indicate that emmer and spelt cultivars have the potential to be used in breadmaking applications, while einkorn cultivars with suboptimal properties need ingredient technology and process modifications to improve their functionalities. Significance and Novelty The study was able to identify and characterize an emmer cultivar (CDC Tatra) with excellent mixing and baking properties having the potential as a standalone flour for baking applications. This represents a significant advancement, as prior research had not recognized any emmer cultivars for their suitability in baking. Our results highlight that cultivar‐based assessment is essential in evaluating the end‐use quality of ancient grain species, thereby developing products using such underutilized grains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".