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Enregistrement W4241497800 · doi:10.22175/rmc2016.018

Extraction and Characterization of Gelatin from Bovine Heart

2017· article· en· W4241497800 sur OpenAlexaff
Bimol C. Roy, Chamali Das, Mirko Betti, Heather L. Bruce

Notice bibliographique

RevueMeat and Muscle Biology · 2017
Typearticle
Langueen
DomaineMaterials Science
ThématiqueCollagen: Extraction and Characterization
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésGelatinPepsinChemistryHydrolysisChromatographyMolar mass distributionResidue (chemistry)Food scienceBiochemistryEnzymePolymerOrganic chemistry

Résumé

récupéré en direct d'OpenAlex

ObjectivesGelatin is extracted by partial hydrolysis of the inter-molecular and intra-molecular bonds of collagen and is widely used in the cosmetic, food and pharmaceuticals industries. Generally gelatin is extracted from collagen in animal tissues with heat which results in low yields but the enzyme pepsin may increase gelatin yield. Bovine heart (BH) which consists mainly of type I collagen can be a potential source of gelatin. This study was aimed to extract gelatin from BH with heat and subsequently with pepsin to assess potential increases in yield and characterize and compare the quality of the extracted gelatin to evaluate functionality.Materials and MethodsConnective tissue (CT) from BH was isolated by blending BH in deionized (DI) water and then collecting CT on a metal sieve. This was repeated twice and blotted dry by filter paper. BH gelatin was extracted first at 80°C for either 4 or 6 h from collected CT and the CT residue subsequently digested with pepsin at either 100 or 200 mg pepsin/g CT residue. Resulting gelatins were characterized for functionality by testing gel strength, viscoelastic properties and molecular weight (MW) distribution. The characteristics of heat extracted BH gelatins were examined for the effect of duration of heating at 80°C using the Statistical Analysis System (SAS Inst. Inc., Cary, NC) with a one-way ANOVA using PROC GLM. The sole source of variation was heating duration (4 or 6 h), and mean differences were determined using ANOVA. For pepsin-extracted gelatins, the effect of pepsin concentration and duration of heating were determined using a two-way ANOVA with prior heating time (4 or 6 h) and pepsin concentration (100 or 200 mg) and their interaction as fixed sources of variation. Mean differences were determined using Tukey’s Honest Significant Difference.ResultsHeat- followed by pepsin-extraction of BH yielded about 7.5 and 11.5-fold more gelatin than 4 h heat extraction of BH at 100 and 200 mg pepsin/g CT, respectively, and about 7.0 and 7.5-fold more than 6 h heat extraction of BH at 100 and 200 mg pepsin/g CT, respectively. Protein was the major proximate component of BH gelatin and trace amounts of crude fat and ash indicating high quality. The gel strength of heat-extracted BH gelatin did not differ between 4 and 6 h of extraction period but poor in pepsin-extracted gelatin and highest for gelatin extracted with 100 mg pepsin/g CT regardless of whether it had been previously heated for 4 or 6 h. Gelling and melting temperatures of heat-extracted BH gelatin were about 25 and 33°C, respectively, with pepsin-extracted gelatin showing the lowest gelling and melting temperatures. Frequency sweep tests showed that both heat- and pepsin-extracted BH gelatins were frequency independent. Heat-extracted BH gelatin gels showed numerically higher storage moduli than pepsin-extracted BH gels which indicated heat-extracted gelatin gels were more stable and stronger than pepsin-extracted gels. Heat-extracted BH gelatin contained predominantly γ, β, and ɑ chains with some low MW peptides not lower than 37 kDa, while the pepsin-extracted gelatin were characterized by a comparative decrease in β and ɑ chains and increased low MW peptides.ConclusionResults indicated that BH is a potential source of gelatin for application in diverse applications and use of pepsin is a viable method of extracting additional gelatin after heat extraction, but that increasing gelatin yield with pepsin was at the expense of gelatin quality.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,774
Score d'incertitude au seuil0,399

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
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)0,0000,000

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.

Tête enseignante Opus0,020
Tête enseignante GPT0,273
Écart entre enseignants0,253 · 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 tête enseignante, 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
GenreEmpirique

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

En bref

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

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