379 Effect of yeast fermentation on pea starch glycemic index in dogs.
Bibliographic record
Abstract
Yeast fermentation can convert starch into increased protein content in feed ingredients, thereby increasing nutritional value. Yeast cell wall also contains mannooligosaccharides that have prebiotic effects. Therefore, yeast fermentation may be a valuable processing method to develop novel functional pet foods. Previously, our group showed that peas have a lower glycemic index than grain-based starches that produces metabolic benefits in dogs and cats. We hypothesized that yeast fermentation will improve pea starch nutritional properties without affecting glycemic index. Candida utilis was used to ferment pea starch, then glycemic index of the starches were compared in an acute feeding trial using fasted, normal-weight beagles (n=8). Yeast fermentation increased the pea starch protein content from 7.7% (dry matter) to 10.4% after fermentation. In contrast, carbohydrate content decreased from 88.3% to 83.9% after fermentation. For glycemic testing, timed blood samples were collected after feeding 1 g/kg available carbohydrate of starches compared to glucose control. Despite the change in macronutrient content, no statistical difference was found in glycemic index between the unfermented and fermented pea starch at 30 ± 10 and 33 ± 6, respectively (p=0.89). Peak blood glucose tended to increase, but was not significantly changed with fermentation, being 4.22 ± 0.14 and 4.53 ± 0.13 mmol/L, respectively (p=0.05). Time to peak blood glucose appeared to take longer at 91 ± 20 minutes after consuming the fermented pea starch compared to 58 ± 10 minutes after consuming the unfermented pea starch, but was not statistically different (p=0.08). Therefore, yeast fermentation of pea starch improved the protein content, but yet retained the low glycemic index properties of unfermented pea starch that is known to increase satiety and prevent obesity compared to higher glycemic index starches. Further studies are needed to compare the effects of fermented pea starch inclusion in a whole balanced diet for dogs and cats as well as potential prebiotic effects.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".