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Record W7001906083

MAILLARD INDUCED PEA PROTEIN-POLYSACCHARIDE CONJUGATES: A FUNCTIONALLY ENHANCED INGREDIENT FOR THE FOOD AND BEVERAGE INDUSTRY

2025· article· en· W7001906083 on OpenAlexfundno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2025
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaillard reactionPapainHydrolysateHydrolysisStarchEnzymatic hydrolysisIngredientCarbohydrate
DOInot available

Abstract

fetched live from OpenAlex

Pea proteins are increasingly recognized as a cost-effective, sustainable source of legume proteins with a well-balanced amino acid profile. The primary goal of this research was to enhance the functional properties of pea proteins by combining enzymatic hydrolysis with Maillard conjugation, using starch and other carbohydrate fractions from air-classified pea flours. The process was designed to be environmentally sustainable, relying on food-grade enzymes and heat-induced Maillard reactions, eliminating the need for enzyme inhibitors and supporting a "green label" approach. In the first study, pea protein-enriched flour (PPEF) was hydrolyzed using trypsin and papain to achieve low to medium degrees of hydrolysis (2% – 15%). These hydrolysates were then conjugated with residual starch and non-starch polysaccharides within the PPEF through heat conjugation by the Maillard reaction. The resulting conjugates showed improved functional properties compared to the raw samples, particularly foaming (~20% - 40%) and emulsifying capacities (~2% - 14%), with enhanced stability (3% - 28%) at acidic pH. Water-holding capacity was improved by ~42% - 100% and oil-holding capacity also increased by about 72% - 254%. The second study focused on obtaining conjugates having higher degrees of hydrolysis (above 15%) of the pea proteins, with additional carbohydrate hydrolysis using α-amylase. These hydrolysates were then heat-conjugated with intact starch and other carbohydrates in the flour, including non-starch carbohydrates. The trypsin-hydrolyzed conjugates outperformed papain-hydrolyzed ones across a range of pH levels (4, 7, and 10), demonstrating superior foaming (60% - 90%) and emulsifying (~ 6% - 210% improvement) properties whereas water-holding and oil-holding properties did not show any significant differences. Contrary to previous findings in the literature, the research showed that extensive hydrolysis, when combined with Maillard conjugation, did not impair functionality but enhanced it. In the third study, both fine and coarse fractions from air classification, i.e., protein- and starch-rich flour, were hydrolyzed using trypsin and α-amylase, respectively, and conjugated using heat through the Maillard reaction. Molecular weight analysis indicated a shift towards higher molecular weights, while microstructural analysis revealed protein-protein aggregates and starch-protein conjugates. Functional evaluations showed significantly higher starch solubility (<200%), improved foaming capacity (~50 % - 75%) and emulsifying properties (~9% - 33%) of the conjugates as compared to the controls, particularly at acidic pH, with notable enhancements across all pH levels (4, 7, and 10). Overall, this research demonstrated the potential of conjugating residual carbohydrate and low-value starch fractions to enhance the functional properties of pea proteins which can be used to improve the texture and stability of foams and emulsions or to improve sensory attributes in alternate meat products. The process not only adds value to starch fractions typically used for animal feed but also promotes eco-friendly, cost-effective solutions for food and beverage applications, such as alternative meats, acidic beverages, and emulsifiers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.211
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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