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Record W4230785756 · doi:10.21203/rs.3.rs-32671/v1

Effects of Brewers’ Spent Grain Protein Hydrolysates on Gas Production, Ruminal Fermentation Characteristics, Microbial Protein Synthesis and Microbial Community in an Artificial Rumen Fed a High Grain Diet

2020· preprint· en· W4230785756 on OpenAlexafffund
Tao Ran, Long Jin, Ranithri Abeynayake, A.M. Saleem, Xiumin Zhang, Dongyan Niu, Lingyun Chen, Wenzhu Yang

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversity of CalgaryUniversity of AlbertaAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsMonensinFermentationRumenFood scienceHydrolysateChemistryDry matterMethanogenesisOrganic matterStarchMicrobial population biologyNutrientHydrolysisAnimal scienceBiochemistryBiologyBacteriaMethaneOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Background: Brewers’ spent grain (BSG) contains 20 ~ 29% protein with high amount of glutamine, proline and hydrophobic and non-polar amino acid residues, making it an ideal material for producing value-added products like bioactive peptides. Protein were extracted from BSG, hydrolyzed with 1% alcalase and flavourzyme, and the generated protein hydrolysates (AlcH and FlaH) showed antioxidant activities. This study was conducted to evaluate effects of AlcH and FlaH on gas production, fermentation characteristics, nutrient disappearance, microbial protein synthesis and microbial community using an artificial rumen system (RUSITEC) fed a high-grain diet.Results: Supplementation of FlaH decreased (P < 0.01) disappearances of dry matter (DM), organic matter (OM), crude protein (CP) and starch, without affecting fibre disappearances; while AlcH had no effect on nutrient disappearance. Neither AlcH nor FlaH affected gas production and VFA profiles, except they enhanced (P < 0.01) NH3-N but decreased (P < 0.01) H2 production. Supplementation of FlaH decreased (P < 0.01) percentage of CH4 in total gas and dCH4 in dissolved gas. Addition of monensin reduced (P < 0.01) nutrient disappearances, improved fermentation efficiency and reduced CH4 and H2 emission. Total microbial nitrogen production decreased (P < 0.05) but proportion of feed particle associated (FPA) bacteria increased with FlaH and monensin. Numbers of OTUs or Shannon diversity indices of FPA microbial community were unaffected by AlcH and FlaH; whereas both indices were reduced (P < 0.05) by monensin. Taxonomic analysis revealed no effect of AlcH and FlaH on the relative abundance (RA) of bacteria at phylum level; monensin reduced (P < 0.05) the RA of Firmicutes and Bacteroidetes and enhanced Proteobacteria. The FlaH enhanced (P < 0.05) the RA of genus Prevotella, reduced Selenomonas, Shuttleworthia, Bifidobacterium and Dialister as compared to control; monensin reduced (P < 0.05) RA of genus Prevotella but enhaced Succinivibrio.Conclusions: Inclusion of FlaH in high-grain diet may potentially protect CP and starch from ruminally degradation, without adversely affecting fibre degradation and VFA profiles. The FlaH also showed promising effects on reducing CH4 production by suppressing H2 generation. Protein enzymatic hydrolysates from BSG using flavourzyme showed potential application to high value-added bio-products.

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 score0.002
Threshold uncertainty score0.004

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 head0.030
GPT teacher head0.312
Teacher spread0.282 · 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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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