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Enregistrement W2987477229 · doi:10.1016/j.dib.2019.104801

Dataset on improved nutritional quality and safety of grilled marinated and unmarinated ruminant meat using novel unfiltered beer-based marinades

2019· article· en· W2987477229 sur OpenAlexafffund
Charles F. Manful, Natalia P. Vidal, Thu Huong Pham, Muhammad Nadeem, Evan Wheeler, Melissa C. Hamilton, Karen M. Doody, Raymond Thomas

Notice bibliographique

RevueData in Brief · 2019
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueMeat and Animal Product Quality
Établissements canadiensMemorial University of Newfoundland
Organismes subventionnairesMemorial University of NewfoundlandAtlantic Canada Opportunities AgencyNatural Sciences and Engineering Research Council of CanadaResearch and Development Corporation of Newfoundland and LabradorCotton Research and Development CorporationDepartment of Natural Resources, Government of Newfoundland and LabradorDepartment of Natural Resources
Mots-clésFood scienceRuminantQuality (philosophy)MarinationBiotechnologyBusinessBiologyAgronomyPhysics

Résumé

récupéré en direct d'OpenAlex

[1]. Grill food safety and quality is a major concern globally. Here in we present data demonstrating the use of novel unfiltered beer based marinades in improving the nutritional quality and safety of grilled ruminant meat. Grilling can lead to the formation of harmful compounds and modify the functional lipids in meats via oxidation, thereby affecting the nutritional quality and safety of the finished product. Lipid oxidation is a deteriorative process involving the degradation of lipid double bonds and the formation of new compounds. Some of these compounds can result in reduced meat quality and off-flavours affecting the sensory, nutritional quality and safety of grilled meat. Unfiltered beers, herbs and spices are known to be excellent sources of antioxidants and polyphenols which can suppress oxidation of functional lipids in grilled meat. Novel unfiltered beer based marinades were developed and used to marinate ruminant meat (beef and moose) prior to grilling. The effect of marination on the fatty acid profile, including saturated, mono- and polyunsaturated fatty acids, of grilled meat was analyzed by gas chromatography/mass spectrometry (GC/MS). In this data in brief article, we include 3 tables containing the fatty acid composition of unmarinated and marinated grilled ruminant meats (beef and moose), a figure showing the percent distribution of grilled meat fatty acid classes, and 2 figures on Pearson's correlation for the associations between phenolic contents, oxidation status and total conjugated linolenic acid (CLA) content. To the best of our knowledge, there is a paucity of information in the literature on the fatty acid composition of wild Cervid meat following preparation by grilling. Grill food safety and nutritional quality is of significant interest to researchers and consumers in the scientific and general food science communities. This article provides data on the fatty composition of grilled moose meat and could be of value to fill the paucity of information currently available in the scientific community on the observed fatty acid composition of grill moose meat. Furthermore, the article presents data on the effects of beer based marinade formulations on the quality of the fatty acid composition of grilled ruminant meats (beef and moose). The growing awareness of the benefits of dietary fatty acids in enhancing personal and population health by reducing the risk factors for cardiovascular diseases and neurodegenerative disorders means that consumers demand meat products with improved fatty acid composition [2,3]. Cervids such as moose (Alces alces) are popular as superior sources of low-fat lean meat with balanced omega 6:3 essential fatty acids compared to traditional farm raised or domesticated meat animals due to the forage they consume as a normal part of their diet [2,4,5]. Furthermore, session ale beers is currently a global phenomenon derived from unique combinations of grains, hops, fruits and herbs to produce low alcohol by volume beers with unique flavors popular among consumers. Two unfiltered session beers were used as base ingredients to produce two novel marinades infused with unique combination of antioxidant rich herbs and spices as a suitable system for the production of grilled foods with enhanced nutritional and sensory characteristics. Whilst there are a limited number of studies in the literature that have used unfiltered beers to evaluate the effects of these beers on suppression of lipid oxidation in grilled meat, none to the best of our knowledge has evaluated the effect of antioxidant rich unfiltered beer based marinades on fatty acid composition of grilled meat systems [6] [7]. As such, this data set presents the concept of using craft beers (specifically session ales) infused with unique combination of herbs and spices to produce unfiltered beer base marinades with enhanced ability to improve grill food sensory attributes and quality, and demonstrates that novel formulations of popular unfiltered India session ale and wheat ale based marinades infused with unique combinations of herbs and spices could be used to marinate beef and moose meats prior to grilling to preserve meat lipids including anticarcinogenic linoleic acid and essential ω3 and ω6 fatty acids.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Jeu de données · Signal consensuel: aucune
Score de désaccord entre enseignants0,005
Score d'incertitude au seuil0,016

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0050,001

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.

Tête enseignante Opus0,111
Tête enseignante GPT0,313
Écart entre enseignants0,203 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2019
Routes d'admission2
Résumé présentoui

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