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Enregistrement W6987880726

VALUE ADDED FRACTIONATION OF CANARYSEED (Phalaris canariensis L.) STORAGE PROTEINS

2023· dissertation· en· W6987880726 sur OpenAlexfundaboutno aff

Notice bibliographique

RevueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Langueen
DomaineNursing
ThématiqueFood composition and properties
Établissements canadiensnon disponible
Organismes subventionnairesFoundation for Food and Agriculture ResearchMinistry of Agriculture - Saskatchewan
Mots-clésEndospermFractionationLinoleic acidEmulsionGermPhytic acidHexaneCanolaPhospholipid
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The overall goal of this research was to develop an aqueous-based protein fractionation process from canaryseed (Phalaris canariensis L.), an important specialty crop for Canada, for value addition in the food industry. Evaluation of the microstructural features of canaryseed showed that it is composed of a bran, germ (embryo) and a starch-rich (starchy) endosperm, which is a typical characteristic of a cereal grain. The germ covers ~8-12% of the total endosperm area and it is highly concentrated with oil. Except for the germ, oil is distributed in the starchy endosperm and accounts for most of the oil in the whole seed. Presence of oil distributed in the starchy endosperm would be challenging to apply aqueous-based processing techniques for protein fractionation. \n\nThe whole (full bran) canaryseed flour was high in oil, ash, fiber, phytic acid and phenolic content than that of white (low bran) flour prepared from roller-milling whereas, they contained 21.3% and 21.4% of protein concentration, respectively, which is not significantly different (p>0.05). Therefore, white flour could be a purer starting material for protein fractionation than whole flour. However, whole-flour showed better oil and water holding, emulsifying capacities, and digestibility in terms of in vitro protein digestibility corrected amino acid score (IV-PDCAAS) compared to that of white-flour whereas, emulsion and foaming stability, and foaming capacity were similar. Both hexane and ethanol were tested as de-oiling solvents for canaryseed, and it was found that linoleic acid and phosphatidylcholine were the major fatty acid and phospholipid extracted by these two solvents. Neither hexane nor ethanol denatured the canaryseed protein (peak denaturation temperature of 107-108°C) and did not cause any negative impact on their techno-functionality and digestibility. \n\nA laboratory-scale-enzyme-assisted-aqueous process was developed to prepare a protein concentrate (>70% protein purity) using yellow-canaryseed-white flour. The same process was successfully adapted for brown canaryseed. However, lower protein purity can be expected depending on the protein content in the white flour if the protein content in the seed is lower due to genetic and environment factors. The aqueous treatment applied for de-oiling reduced the initial oil content (6%) in yellow-seed flour to 1.2%. The enzymatic treatment applied afterward degrade the starch in the flour improving the protein content from 21% to 74.8%. It also increased the oil content from 1.2% to 12.1%, which was higher than anticipated oil content in the final product. Same trend was observed for brown canaryseed processing. The protein concentrates from yellow and brown canaryseed prepared using this aqueous-based method showed a least gelation concentration at 16% (w/w), which is higher than commercial soy protein concentrate (CSPC, 13%), but lower than the commercial vital wheat gluten (CVWG, 19%). At the least gelation concentration, the protein gels from both yellow and brown canaryseed showed significantly lower (p<0.05) strength than that of CSPC even with the presence of mono- and divalent salts. On the other hand, yellow and brown canaryseed protein concentrates showed comparable bread-dough improving properties to CVWG at lower inclusion levels (1-3%). Noticeable differences of gelation properties between yellow and brown canaryseed was not observed. \n\nDuring the scaling up of the lab process, some modifications to the original aqueous process was performed to address issues related to upstream decanter separation. The modified process reduced the oil content to <1% and degraded ~85% starch to prepare the final protein product. However, proteins were lost into the waste stream due to the modifications, subsequently lowering the protein recovery into the final product. Further investigations on process modifications and optimization are required to prevent protein losses and improve protein recovery. \n\nIn summary, this research was able to develop an enzyme-assisted aqueous process for canaryseed protein fractionation for value addition despite having a major fraction of oil distributed within the starchy endosperm. This process used canaryseed white flour obtained using roller milling as the starting material for protein fractionation, which is purer in chemical composition compared to whole-seed flour. The developed method can be used for both yellow and brown canaryseed to fractionate protein. Canaryseed protein has high thermal stability and the use of hexane and ethanol as de-oiling solvent does not denature the protein and affect negatively for its techno-functional and nutritional properties. The fractionated protein did not display uniquely improved techno-functional properties compared to commercial soy protein or vital wheat gluten. However, canaryseed protein showed comparable bread-dough-forming properties to that of vital wheat gluten. The enzyme-assisted aqueous process was scaled up using pilot-scale equipment and was able to successfully de-oil white canaryseed flour. However, some process modifications were required to address the issues encountered during scaling up which caused lower protein recovery and purity in the final fractionated product. Further investigations and modifications are required to improve and optimize the scaled-up process for protein recovery.

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 candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,151
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

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

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 Opus0,009
Tête enseignante GPT0,183
Écart entre enseignants0,174 · 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.

Devis d'étudeQualitatif
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
Publié2023
Routes d'admission2
Résumé présentoui

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