PSXI-11 Oxidation Analysis on Chicken Meat Meals Composition, Aromatics, and Palatability: A Novel Aromatic Palatability Trial Utilizing Labrador Retrievers, Hercules Enose Ufgc, Spme, and Broad Spectrum Gcms
Bibliographic record
Abstract
Abstract Even the highest quality ingredients undergo oxidative stresses during manufacturing processes, increasing the nutrition delivery challenges facing large-scale feed manufacturing. In this study we investigate the impact of increasing peroxide values (PV) in the chemical composition in rendered chicken meal (CM) and chicken by-product meal (CB). To determine canine acceptance, working Labrador Retrievers (20 male; 20 female) were used in a preliminary novel aromatic palatability test as well as a traditional two-pan palatability test. PV sample levels ranged from < 10-200 (CB or CM Sample identification: 1.~ < 10, 2.~20-50, 3.~50-100, 4.~100-200). Results indicate that dogs preferred reduced peroxide values in both aromatic (p= < 0.05) and traditional 2-pan palatability trials (p= < 0.05). Preference testing results correlated with extensive physical and chemical data obtained using a Heracles Electronic Nose ultra-fast gas chromatography (UFGC), solid-phase micro-extraction (SPME), and gas chromatography-mass spectrometry (GC-MS). The broad-spectrum analysis utilized solid-phase micro-extraction (SPME) and gas chromatography-mass spectrometry (GC-MS) to identify 177 nonpolar compounds, 340 polar compounds, and 457 volatile compounds. The overall composition did not vary; however, individual compounds had strong linear correlations with peroxide value. In chicken by-product meal samples, 38 compounds were linearly correlated; in chicken meals, 27 compounds were identified (r2>0.90). These data: 1) introduces novel quality control markers for further research and showcases the potential for greater accuracy by developing product specific markers; 2) confirms that the chemical differentiation between peroxide values went beyond lipid oxidation and highlighted multiple compounds of interest for further study; and 3) emphasizes greater levels of peroxide in pet foods have unfavorable palatability. This research was funded by the Fats and Protein Research Foundation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".