Determining the effects of <i>Candida utilis</i>‐fermented pea starch vs. unfermented pea starch, alone or in whole diets, on palatability and glycemic response in dogs and cats
Bibliographic record
Abstract
Current research suggests yeast fermentation has the potential to improve palatability of pea-based diets for both cats and dogs. However, to be useful, fermentation should not compromise other healthy attributes of peas such as a low glycemic response. Fermentation of uncooked pea starch with Candida utilis (ATCC 9950) appeared to increase crude protein, crude fiber content, inorganic compounds (phosphorus and iron) and phenols. Whole diets were designed with fermented and unfermented pea starch to assess palatability, food intake, and glycemic responses in unacclimated, mixed sex Beagle dogs and mixed breed cats (n = 8 and n = 7, respectively). For palatability testing, a control diet was formulated with 30% corn starch as well as test diets with 30% inclusion of fermented or unfermented pea starch (all lab-made), then compared to a commercial diet containing pea starch (Legacy/Horizon). Fermentation had little effect on rapidly digestible starch either in uncooked starch form or when incorporated into whole diets, but did decrease resistant starch by 15% and increase slowly digestible starch by 20%. Palatability tests using either two choices or four choices at a time revealed a significant preference for the fermented pea starch diet (p < 0.01) in both species. For the glycemic responses, a total of four different pea products were included: unfermented pea starch, fermented pea starch, and 30% inclusion of unfermented and fermented pea starch in whole formulated diets. There were no significant changes in glycemic responses with the fermented pea diet compared to the unfermented diet, demonstrating that healthful low glycemic properties of pea starch were retained after C. utilis fermentation. Overall, C. utilis-fermentation technique was successfully adapted to pea starch where it resulted in increased palatability and food intake in dogs and cats, with potential to positively contribute to overall health benefits for both species.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".