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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".