Physiological Effects of Barley: Examining the Effects of Cultivar, Processing and Food Form on Glycemia, Glycemic Index, Satiety and the Physico-chemical Properties of β-glucan
Bibliographic record
Abstract
Barley has been receiving increased attention as a human food due to the health benefits associated with β-glucan fiber and its potential as a low glycemic index (GI) functional food. Research has shown a relationship between the physico-chemical properties of β-glucan and the physiological effects, which may be altered by processing. However, it is not known if the physiological effects of consuming barley are affected by variations in chemical composition among cultivars or by common processing methods such as pearling or milling. The primary objective of this thesis was to characterize the effects of differences in cultivar starch and fibre content, level of pearling and milling on the GI, satiety and the physico-chemical properties of β-glucan. Nine barley cultivars varying in starch-type and β-glucan content were studied in three experiments in separate groups of ten healthy participants. Blood glucose and satiety ratings were measured and the GI was calculated. Total starch, total fibre, β-glucan, molecular weight (MW), solubility and β-glucan viscosity were determined in vitro. Results showed that GI varied by cultivar (CDC-Fibar, 26 ± 3 vs. AC-Parkhill, 35 ± 4, P < 0.05) and pearling (WG, 26 ± 4 vs. WP 35 ± 3, P < 0.05). When two cultivars were milled and processed to wet pasta the GI increased by 184% (P < 0.05). The pearled wet pasta had a significantly lower GI compared to the whole grain (P < 0.05). Boiled barley kernels tended to elicit greater satiety than white bread, but the difference was not significant. In both the boiled barley kernels and the wet pasta, pearling did not affect the MW, viscosity and solubility. MW did not significantly differ between cultivars but solubility and viscosity did (P < 0.05). The wet pasta had significantly lower MW, solubility, viscosity but not β-glucan content than the boiled barley kernels (P < 0.05). In conclusion, pearling did not have an effect but milling and extruding resulted in significant reduction in MW, solubility and viscosity. The GI of barley is influenced significantly by cultivar, pearling and milling. Further studies are required to determine the effect on satiety.
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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".