Determining the lmpact of Genotype × Environment on oat protein isolate structure, function, and composition
Notice bibliographique
Résumé
Oat has recently received widespread attention owing to its relatively high protein content (15-20%) among cereals. Given the increased use of plant proteins in the food industry, oat protein isolate is also considered a sustainable plant protein alternative. The characteristics of oat protein depend on both genotype and the environment in which it is grown. Therefore, the genotype × environment interaction (G × E) has a major influence on protein composition, structure, and functionality which is of great importance in the context of end product quality and consistency. The goal of the first study of the thesis was to evaluate the effect of G × E on oat protein structural characteristics and functionality using three oat genotypes (Summit, AC Morgan, and CS Camden) grown in three different environments (Manitoba, Alberta, and Saskatchewan) in the Canadian Prairies. The second study aimed at determining the effect of G × E on the relative protein composition through SE-HPLC and the use of LC-MS for protein identification. Oat protein isolate (OPI) was extracted from defatted oat flour at pH 9 at a 1:5 flour:NaOH ratio and precipitated at pH 5.3. The OPI samples were freeze-dried and evaluated for structural characteristics such as protein profile, surface hydrophobicity, secondary structure, and denaturation characteristics, as well as functional properties such as solubility, foaming, emulsification, and gelling. All structural and functional tests were conducted at pH 7. The first study indicated that oat protein content, protein profile, and functional properties are dependent on genotype and the environment. The surface hydrophobicity indicated a stronger impact from the growing environment and samples from Alberta showed the highest surface hydrophobicity. The denaturation temperature for OPI ranged from 110.2 -111.6 °C. The water solubility of OPI was significantly impacted by G × E, where the solubility ranged from 13-30 %. Samples Alberta – Summit exhibited the highest foaming capacity, while all samples tested had good foaming stability >70%. Furthermore, it was found that G×E significantly impacts OPI structure and functionality including denaturation enthalpy, protein solubility, foaming capacity, emulsion stability, and textural characteristics. The SE-HPLC separated the OPI into four major fractions including polymeric globulin, avenins, glutelins and albumins as well as smaller peptides, whereas LC-MS was able to identify eight major types of proteins present in OPI including globulins, prolamins/avenins, glutelins, enzymes/ albumins, enzyme inhibitors, heat shock proteins, grain softness proteins and allergenic proteins. The SE-HPLC analysis revealed that environment has a stronger effect on overall oat protein composition, while LC-MS results indicated a significant genotypic effect on the main globulin protein type in OPI. PCA results indicated that certain environment and genotypic combinations could be better choices in terms of globulin protein quality given their positive and negative associations with certain genotypes and environments. Overall, the results indicate that genotype, environment and G×E significantly impact OPI structure, functionality and composition, highlighting the need for future work to further expand the examination of OPI structure-function and compositional characteristics to determine oat cultivars that can be used to produce OPI of consistent quality. To that end, this study provides new insights into the selection of oat genotypes and environment combinations for targeted protein applications in the food industry.
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 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».