Technological Properties of Beef Emulsions Prepared with a Novel Processed Potato Ingredient (O’Brien’s Best)
Notice bibliographique
Résumé
ObjectivesThe processed potato ingredient tested in this study was a commercially available ingredient (O’Brien’s Best; Botaniline Foods, LLC) that consists of skinned, sliced potatoes that were cooked to an exact time/temperature to enhance physiochemical properties. The objective of the study was to assess the technological properties of beef emulsion modeling systems prepared with the novel processed potato ingredient (O’Brien’s Best).Materials and MethodsThe meat used in this study was lean ground beef from one master batch of beef that was targeted to 90% lean and 10% fat. The meat batter formulations contained 20% water, 6.15% spice/seasoning, 0.18% Prague powder, and 0.0035% sodium erythorbate, and varying quantities of sodium tri-polyphosphate, salt (NaCl), and binders (processed potato, tapioca starch, or all-purpose binder). In total, eight treatments were formulated and manufactured on three separate, independent occasions (N = 24 experimental units; n = 3 replications). Three treatments were formulated with the novel processed potato ingredient (formulated without phosphate, 0.635% NaCl, and either 5, 10, or 15% the processed potato ingredient). Three treatments were formulated with commercially sourced tapioca starch (formulated without phosphate, 0.635% NaCl, and either 5, 10, or 15% commercial tapioca starch, which was tested to be 78% starch purity). Two treatments were formulated with a commercial formulation [formulated with 0.30% sodium tri-polyphosphate, 10% all-purpose binder (a multi-ingredient proprietary blend binder from Herman Laue Spice Company Inc.; Uxbridge, Ontario), and 1.905% NaCl, or 1.270% NaCl]. Parameters tested were cooking loss, proximate composition of cooked meat batters, texture profile analysis of cooked meat batters, and instrumental color of uncooked and cooked meat batters. Data were analyzed with the GLIMMIX procedure of SAS v9.4 with a fixed effect of treatment and a random effect of replication. Least square means were separated using the PDIFF option with a Tukey-Kramer adjustment. Differences were considered statistically different at P < 0.05.ResultsCooking loss was not different (P = 0.44) among treatments and ranged from 0.64% to 0.77%, indicating acceptable stability for all emulsion formulations in the study. Proximate composition revealed significant differences (P < 0.05) in moisture, protein, ash, and other components (carbohydrates), while lipid content was unaffected. Texture profile analysis revealed that textural properties were generally unaffected (P > 0.05) by treatment, with the exception of less gumminess (P < 0.05) and less chewiness (P < 0.05) in processed potato formulated emulsions compared with the tapioca starch and commercially formulated emulsions. Instrumental color of uncooked emulsions was affected to a greater degree than instrumental color of cooked emulsions. Yet, when tapioca starch was included at high levels (> 10%) in cooked emulsions lightness (L*) and yellowness (b*) were greater (P < 0.05) compared with emulsions formulated with the processed potato ingredient and with the commercial formulations.ConclusionIn summary, the technological properties (cooking loss, texture profile analysis, and instrumental color) of beef emulsion systems were largely unaffected by the processed potato ingredient (despite removal of phosphates and less NaCl) and performed similar to the commercial formulations.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».