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Record W4388530524 · doi:10.1093/jas/skad281.126

191 Apparent Total Tract Digestibility, Fecal Metabolites, and Feces Quality of Pulse-Based Vegan Dog Foods with Or Without Added Enzymes in Adult Dogs and Comparison to Digestibility from a Pig Model

2023· article· en· W4388530524 on OpenAlexaff
W P G Van Straten, Anna K. Shoveller, L F Wang, E. Beltranena, Thava Vasanthan, R. T. Zijlstra

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of GuelphUniversity of Alberta
Fundersnot available
KeywordsXylanaseFood scienceFecesPhytaseProtein qualityCellulaseNutrientChemistryDigestion (alchemy)ProteaseEnzymeBiologyBiochemistryChromatographyMicrobiology

Abstract

fetched live from OpenAlex

Abstract Consumer demand for vegetarian and vegan dog foods is increasing. These specialty diets may rely on alternative plant-based protein sources such as pulses and pulse protein concentrates instead of animal protein to meet amino acid (AA) requirements. Pulses such as field pea and lentil contain more protein than cereal grains, but also contain anti-nutritional factors (ANF) such as phytate and insoluble dietary fiber (IDF) that have the potential to reduce nutrient digestibility. The objectives were 1) to determine if the addition of enzymes before or after extrusion would increase apparent total tract digestibility (ATTD) of pulse-based extruded vegan dog foods; and 2) to compare ATTD of nutrients and gross energy (GE) between dogs and growing pigs fed the same diets. Two formulations were created: low protein (Low) containing 24% crude protein (CP) including 35% field pea flour and 15% lentil flour, and high protein (High) containing 43% CP including 50% pea protein concentrate and 20% lentil protein concentrate. Each formulation was used to prepare 3 diets: control without enzymes (Con), with enzymes added before extrusion (P; X-115 single screw; Wenger, Sabetha, KS) or enzymes added after extrusion (A) for a total of 6 diets. The enzyme blend contained cellulase (480,000 or 510,000 U/kg of diet), xylanase (360,000 or 680,000 U/kg), protease (960,000 or 1,360,000 U/kg), and phytase (12,000 or 17,000 U/kg) for Low and High diets, respectively. Following extrusion, kibbles were ground and 0.5% TiO2 was added to diets. Ten mix breed adult dogs (1.5 - 2yrs; 21-29 kg BW) were fed in a 6 × 6 replicated incomplete Latin square with 10-d periods. Feces were collected during the last 4-d of each period. The ATTD of organic matter (OM) and CP ranged from 77.7 to 86.3% and 74.6 to 87.8%, respectively. The ATTD of OM, CP, crude fat, GE, and ash did not differ between A and Con diets. Feces concentrations of glucose, xylose, acetic and propionic acid was greater (P < 0.05) for A than Con diets, indicating that enzymes hydrolyzed some IDF that was subsequently fermented by gut microbes. Addition of enzymes after extrusion increased (P < 0.05) feces moisture by 1.5% causing loose stools. Addition of enzymes before extrusion reduced (P < 0.05) ATTD of CP due to overheating during drying after wet enzyme processing. The ATTD of nutrients was greater (P < 0.05) for pigs than dogs; Nevertheless, could be a good predictor (R2 = 0.74 - 0.87) for ATTD of OM, CP, and GE. In conclusion, enzyme addition after extrusion did not increase ATTD for the dogs but did impact feces metabolites and fecal quality. Finally, pigs are a good translational model for testing ATTD of dog foods.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.338
Teacher spread0.268 · 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 designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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