The Effect of Specialty Salts on Cooking Loss, Texture Properties, and Instrumental Color of Beef Emulsion Modeling Systems
Notice bibliographique
Résumé
ObjectivesSalt plays an integral role in meat processing, and reduction or exclusion will have negative impacts on water holding capacity and binding function of protein and fat. Specific to meat emulsions, NaCl is used in the formulation due to its effect on the solubilization (extraction) of myofibrillar meat proteins, which allow the formation and stabilization of the interfacial matrix during manufacture and preparation. While previous research has addressed preservation (shelf-life and oxidation attributes) and flavor (sensory attributes) when using specialty salts in meat products, the application of specialty salts in meat emulsions has never been addressed in a scientific manner. Therefore, the purpose here was to evaluate the incorporation of different levels and types of specialty salts on the physicochemical and textural characteristics of beef emulsions.Materials and MethodsThree specialty NaCl salts (premium sea salt, pink sea salt, and gray sea salt) were added to beef emulsion modeling systems at three different inclusion levels (0.70, 1.00, and 1.30%) and then compared with commercially sourced white salt. Salt (NaCl) purity levels for commercially sourced white salt, premium sea salt, pink sea salt, and gray sea salt were 99.8, 99.8, 95.2, and 94.9%, respectively. Cooking loss, emulsion stability, proximate composition, pH, texture profile analysis, and instrumental color of the emulsions were evaluated with three independent replications from one batch of ground beef. One batch of ground beef was used to properly control for confounding factors such as beef source and day of manufacture. Treatment was applied to one of twelve 500-g base emulsions (without artificial food dyes, preservatives, spices, and seasonings) containing beef (according to the level of salt added), water (28.14%), oil (8.00%), starch (2.00%), and phosphate (0.35%) for each replication (36 total experimental units). Data were analyzed with PROC GLIMMIX of SAS with fixed effects of salt type, salt inclusion level, and their interaction, and the random effect of replication. Least square means were separated using the PDIFF option with a Tukey-Kramer adjustment, and was further separated using an orthogonal set of estimate statements to analyze linear and quadratic effects for salt inclusion level. Differences were considered different at P ≤ 0.05.ResultsEmulsion stability and cooking loss were primarily affected (P < 0.01) by salt inclusion level rather than salt type (P ≥ 0.13). Stability increased and cooking loss decreased as salt inclusion level increased (linear P < 0.01). Proximate composition of cooked meat emulsions trended differently as salt increased from 0.70% to 1.30% salt inclusion level for the different salt types. Moisture increased and lipid decreased for commercial white salt, while moisture decreased, and lipid increased for all three of the specialty salts. Hardness, springiness, gumminess, and chewiness of emulsions increased as the level of salt increased for all the treatments and were greatest (P < 0.0001) in all treatments at the 1.30% salt inclusion level, however, no differences were observed between the salt types.ConclusionOverall, salt inclusion level, rather than salt type, had significant effects on the solubilization of protein and dispersion interactions of the emulsions, which affected physicochemical and functional properties.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».