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Record W3155010361 · doi:10.1139/cjas-2020-0185

Effects of <i>Quillaja</i> saponin supplementation on growth performance, nutrient digestibility, fecal microbiota, and fecal gas emission in growing pigs

2021· article· en· W3155010361 on OpenAlexvenueno aff
De Xin Dang, In Ho Kim

Bibliographic record

VenueCanadian Journal of Animal Science · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNatural product bioactivities and synthesis
Canadian institutionsnot available
Fundersnot available
KeywordsFecesAnimal scienceBiologySaponinNutrientCrossbreedFeed conversion ratioBody weightFood scienceMicrobiologyMedicineEndocrinology

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate the effects of dietary supplementation of Quillaja saponin (QS) on growth performance, nutrient digestibility, fecal microbiota, and fecal gas emission in growing pigs. A total of 50 crossbred growing pigs [(Yorkshire × Landrace) × Duroc] with an initial body weight of 23.83 ± 1.95 kg were randomly assigned to one of two treatments for a 56 d trial with five replicate pens per treatment and five pigs (two barrows and three gilts) per pen. Dietary treatments including control diet and control diet supplemented with 200 mg·kg −1 QS. The average daily gain was significantly increased during days 0–56, whereas the fecal ammonia emission on day 56 and fecal coliform bacteria counts on day 28 were significantly decreased in pigs fed with QS-containing diet. However, dietary supplementation of QS had no significant effects on apparent total tract digestibility. In conclusion, dietary supplementation of 200 mg·kg −1 QS had beneficial effects on growth performance, fecal microbiota, and fecal gas emission in growing pigs. Considering the carry-over effects, the adaption period should be at least 28 d when supplementing 200 mg·kg −1 QS to the diet of growing pigs for improving the growth performance.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.100
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.219
Teacher spread0.214 · 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.

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

Citations6
Published2021
Admission routes1
Has abstractyes

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