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Record W2916445290 · doi:10.1093/jas/skz073

Supplementation with live yeast increases rate and extent of in vitro fermentation of nondigested feed ingredients by fecal microbiota

2019· article· en· W2916445290 on OpenAlexaff
Tadele G. Kiros, Atta Kofi Agyekum, Jing Wang, Romain d'Inca, A. D. Beaulieu, Eric Auclair, Andrew G. Van Kessel

Bibliographic record

VenueJournal of Animal Science · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFermentationYeastFecesFood scienceCanolaIncubationLeavening agentChemistrySoybean mealBiologyAnimal scienceBiochemistryMicrobiology

Abstract

fetched live from OpenAlex

Two studies were conducted to investigate the effect of live yeast (LY) on the in vitro fermentation characteristics of wheat, barley, corn, soybean meal (SBM), canola meal, and distillers dried grains with solubles (DDGS). In Study 1, LY yeast was added directly to in vitro fermentations inoculated with feces from lactating sows, whereas as in study 2, feces collected from lactating sows fed LY as a daily supplement was used. Selected feedstuffs were digested and the residue added to separate replicated (n = 3) fermentation reactions. Study 1 was conducted in two blocks, whereas study 2 was conducted using feces collected after a period of 3 (Exp. 1) or 4 wk (Exp. 2) of LY supplementation. Accumulated gas produced over 72 h was modeled for each substrate and the kinetics parameters compared between LY and control groups. The molar ratio of the volatile fatty acids (VFAs) produced in vitro were also compared at 12 and 72 h of incubation. In study 1, in vitro addition of yeast increased (P < 0.001) the rate of gas production (Rmax). However, a yeast × substrate effect (P < 0.05) observed for total gas accumulated (A), time to half asymptote (B), and time required to reach maximum rate of fermentation (Tmax) suggested that yeast-mediated increases in extent and rate of fermentation varied by substrate. Greater total gas production was observed only for corn and SBM, associated with greater B and Tmax. Supplementation with LY appeared to increase A and Rmax although with variation between experiments and substrates. In Exp. 1, LY decreased (P < 0.05) B and Tmax. However, a yeast × substrate effect (P < 0.05) was observed for only A (for wheat, barley, corn, and corn DDGS) and Rmax (wheat, barley, corn, and wheat DDGS). In Exp. 2, LY increased (P < 0.0001) A and decreased B. However, an interaction (P < 0.05) with substrates was observed for Rmax (except SBM) and Tmax. With exception of the DDGS samples, LY supplementation increased (P < 0.05) VFA production at 12 and 72 h of incubation. Yeast increased (P < 0.05) the molar ratios of acetic acid and branch-chain fatty acids at 12 h of incubation; however, this response was more variable by substrate at 72 h. In conclusion, LY supplementation increased the rate and extent of in vitro fermentation of a variety of substrates prepared from common feedstuffs. Greater effects were observed when LY was fed to sows than added directly in vitro, suggesting effects on fermentation were not mediated directly.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.005
GPT teacher head0.262
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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