β-Glucan content, viscosity, and solubility of Canadian grown oat as influenced by cultivar and growing location
Bibliographic record
Abstract
The composition and physicochemical properties of oat flour with respect to β-glucan content and its solubility and viscosity were investigated. Eight oat cultivars grown in 20 prairie locations for three consecutive years were examined in this study to establish how cultivar, growing location, and their interaction influence the abovementioned attributes. It was found that the β-glucan content was primarily influenced by oat cultivar, while growing location and the interaction between cultivar and location had minimal effect. Among the eight cultivars, HiFi had the highest β-glucan content (5.82% w/w), while Derby had the lowest (4.37% w/w). Growing location, oat cultivar, and their interaction had a significant effect on β-glucan solubility and viscosity. The β-glucan solubility differed among oat cultivars, where 28.44–34.28% of the β-glucan present in the oat flour could be solubilized at 37°C. Viscosity was evaluated by consecutive fixed speed tests at shear rates of 1.29–129 s−1. Results showed that shear rate, growing location, and cultivar affected viscosity. The flow behavior index (n) for all β-glucan dispersions indicated shear-thinning behavior. HiFi had the highest β-glucan solubility and viscosity among all the cultivars analyzed. The findings provide insight into raw material selection and variations in raw material characteristics when targeting specific oat product applications.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".