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Record W3119680233 · doi:10.1186/s40104-020-00531-5

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

2021· article· en· W3119680233 on OpenAlexafffund
Long Jin, Ranithri Abeynayake, A.M. Saleem, Xiumin Zhang, Dongyan Niu, Lingyun Chen, Wenzhu Yang

Bibliographic record

VenueJournal of Animal Science and Biotechnology/Journal of animal science and biotechnology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of LethbridgeUniversity of AlbertaUniversity of CalgaryAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsFermentationRumenFood scienceMonensinDry matterChemistryHydrolysateStarchOrganic matterNutrientMicrobial population biologyMethanogenesisAnimal scienceHydrolysisBiologyBacteriaBiochemistryMethaneOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Background Brewers’ spent grain (BSG) typically contains 20% – 29% crude protein (CP) with high concentrations of glutamine, proline and hydrophobic and non-polar amino acid, making it an ideal material for producing value-added products like bioactive peptides which have antioxidant properties. For this study, protein was extracted from BSG, hydrolyzed with 1% alcalase and flavourzyme, with the generated protein hydrolysates (AlcH and FlaH) showing antioxidant activities. This study evaluated the effects of AlcH and FlaH on gas production, ruminal fermentation characteristics, nutrient disappearance, microbial protein synthesis and microbial community using an artificial rumen system (RUSITEC) fed a high-grain diet. Results As compared to the control of grain only, supplementation of FlaH decreased ( P < 0.01) disappearances of dry matter (DM), organic matter (OM), CP and starch, without affecting fibre disappearances; while AlcH had no effect on nutrient disappearance. Neither AlcH nor FlaH affected gas production or VFA profiles, however they increased ( P < 0.01) NH 3 -N and decreased ( P < 0.01) H 2 production. Supplementation of FlaH decreased ( P < 0.01) the percentage of CH 4 in total gas and dissolved-CH 4 (dCH 4 ) in dissolved gas. Addition of monensin reduced ( P < 0.01) disappearance of nutrients, improved fermentation efficiency and reduced CH 4 and H 2 emissions. Total microbial nitrogen production was decreased ( P < 0.05) but the proportion of feed particle associated (FPA) bacteria was increased with FlaH and monensin supplementation. Numbers of OTUs and 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, whereas monensin reduced ( P < 0.05) the RA of Firmicutes and Bacteroidetes and enhanced Proteobacteria. Supplementation of 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 The supplementation of FlaH in high-grain diets may potentially protect CP and starch from ruminal degradation, without adversely affecting fibre degradation and VFA profiles. It also showed promising effects on reducing CH 4 production by suppressing H 2 production. 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.117
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.005
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.238
Teacher spread0.222 · 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 teacher head, not a consensus.

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

Citations56
Published2021
Admission routes2
Has abstractyes

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