Non-enzymatic browning in glucosamine and glucosamine-peptides reaction systems as a source of antioxidant and flavouring compounds
Notice bibliographique
Résumé
Non-enzymatic browning is a common and complex reaction that occurs in everyday cooking-indeed, it is a crucial step in food processing. A typical browning process \nincludes both the Maillard reaction and caramelization, which normally occur only at extreme temperatures to produce both desired and distinctive flavours and an intense brown colour in foods. On one hand, advanced stage Maillard reaction compounds canbe toxic, such as acrylamide and 5-hydroxymethylfurfural (5-HMF). And yet on the other hand, Maillard reaction compounds can possess bioactivities including taste enhancing, antioxidant and antimicrobial capacities; collectively these are known as Maillard reacted peptides (MRPs). This bizarre paradox among non-enzymatic browning reaction compounds has long deserved a more in depth investigation under controlled conditions. To achieve these positive bioactivities yet reduce the accumulation of the harmful compounds associated with the Maillard reaction, a research strategy was proposed to produce and understand MRPs at . lower temperatures. However, information on the antioxidant and sensorial properties MRPs at moderate temperatures is scarce. Glucosamine (GlcN) is an amino sugar recently revealed to be capable of triggering a fast Maillard reaction with protein at 25°C. Additionally, due to the presence of both a carbonyl and amino group wi~hin the same molecule, GlcN can form \nsubstantial dicarbonyls at 37°C-the precursors to desirable flavours. The main objective of this thesis was to study taste enhancement and antioxidant activity of GlcNpeptides in GlcN model systems. A total of 3 studies were designed representing the main building blocks of this project. The first study focused on the potential of GlcN to modifying protein hydrolysates at 25 and 37°C in a fish gelatin hydrolysates-GlcN model. Modification of \nthe hydrolysates by GlcN was accomplished by two approaches: firstly, a Maillardbased glycation with GlcN, and secondly, an enzymatic glycosylation catalyzed by the \ntransglutaminase (TGase ), condensing the primary amine group of GlcN with the carboxamide group of a glutamine residue in a peptide. GlcN-induced modification was \nachieved at both 25 and 37°C, and the antioxidant and antimicrobial activities were improved compared to native hydrolysates. The second study focused on the taste enhancing property of GlcN-modified hydrolysed meat proteins produced at37 and 50°C in the presence or absence of TGase. Samples were formulated into seasoning compositions and evaluated by untrained consumers. The meat protein hydrolysate was perceived as the saltiest (p<0.05) whereas the glycated hydrolysate produced at 50°C tended (p= 0.0593) to be the most savoury \nseasoning composition. This further confirmed the role of GlcN as an important component in modified hydrolysate by eliciting an umami taste, despite its inability to \nstrike a balance between: eliciting saltiness and savouriness. The non-enzymatic browning of GlcN was further investigated in the third study. Chemical-physico changes and antioxidant activity were monitored in 3-level factorial models: in phosphate buffer versus ammonium hydroxide solution, at 40 versus 60°C, and incubated up to 48 h. Incubation at 40°C for 6 h produced a yellow-coloured caramel with the greatest levels of anti-radical activity and diacetyl-a volatile flavour compound of dicarbonyls. Overall, this thesis showed GlcN to be a reactive amino sugar capable of key rapid peptide reactions and self-modifications at moderate temperatures. Compounds from these GlcN-mediated non-enzymatic browning reactions not only represent important flavour and colour agents, but also showed promise as antimicrobials and antioxidants. A future paradigm shift is anticipated for GlcN, evolving from its current status as a health supplement to become a multi-functional food ingredient.
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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 | 0,001 | 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 ».