PSVIII-12 Hexanal, as Identified Through Flash Gas Chromatography Electronic Nose, Strongly Correlates with Pv in Rendered Chicken Meal Samples, Although Additional Compounds Influence Aromatic Palatability
Notice bibliographique
Résumé
Abstract Samples of rendered chicken meal (CM) and chicken by-product meal (CB) were obtained from a commercial plant with samples representing various storage time points and a range of peroxide values from < 10 (1), 20-50 (2), 50-100 (3), 100-200 (4). Samples were utilized in a novel aromatic palatability trial with 20 working Labrador Retrievers (n = 10 males and n = 10 females). Aggregated interaction time showed the most pronounced difference between the lowest PV sample and the highest PV for both CB and CM (P < 0.0001, 0.001). Both CB1 and CM1 were significantly different from all other samples (P = 0.05). Samples were also sent to a third party for HERACLES Neo flash gas chromatography electronic nose analysis (e-nose). Analysis of e-nose chromatograms showed good discrimination between samples (DI = 97) with the largest spatial differences between the low and high PV samples. Chromatogram peaks were tentatively identified according to their Kovats index and the AlphaChemBase database. Component 1 (X-axis) accounted for 99.4% of the difference while component 2 (Y-axis) showed 0.54% of the difference. The strongest odor, as determined by the highest area peak was hexanal which produces a fatty and fishy smell. When evaluated in a bivariate model hexanal vs PV was well correlated on a 2P curve (R2= 0.986, P < 0.0001). However, hexanal was less correlated with aromatic palatability (R2 = 0.616. P = 0.09). Therefore, a primary least squares model was created to better display the relationship between palatability and oxidation. Utilizing two factors, the PLSR model explained 72% of the variation in the e-nose peak area data (X) and 90% of the variation in the PV*palatability (Y). Of the 61 aromatic compounds identified, the model identified 45 compounds with a VIP over 0.8. Both PV and palatability were well-fitted by the model as indicated by their position between the outer two ellipses (R2 = 75% to 100%). In the model, Hexanal had a VIP of 1.1 suggesting it was an important component, although other compounds had significantly better VIP scores and are likely to better predict palatability. Therefore, these data show aromatic hexanal is an accurate predictor of the oxidation of a product, although it may not provide the full picture regarding palatability.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».