MétaCan
Menu
Back to cohort
Record W4416714126 · doi:10.1016/j.foodres.2025.117941

Application of absorbent resins in protein extraction to reduce off-Flavours in flaxseed proteins

2025· article· en· W4416714126 on OpenAlexafffund
Federica Higa, Nancy D. Asen, Jianheng Shen, Brittany Polley, Pankaj Bhowmik, Martin J. T. Reaney, Michael T. Nickerson

Bibliographic record

VenueFood Research International · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsNational Research Council CanadaUniversity of Saskatchewan
FundersGovernment of SaskatchewanMinistry of Agriculture - SaskatchewanUniversity of SaskatchewanNational Research Centre
KeywordsAmberliteExtraction (chemistry)Chlorogenic acidWhey proteinFerulic acidFlavourSolid phase extractionDetection limit

Abstract

fetched live from OpenAlex

This study investigated the use of adsorbent resins (Amberlite XAD-16 N, Sepabeads SP-207, and Diaion HP-20) during flaxseed protein extraction to reduce the volatile organic (VOCs) and non-volatile compounds (non-VOCs). These compounds could limit the application and consumption of flaxseed proteins by imparting off-aromas and flavours, including bitterness and astringency. The reduction of these compounds using resins during protein extraction could potentially enhance the sensory quality of flaxseed proteins, making them more suitable for incorporation into a wider range of food products such as plant-based meat alternatives, beverages, and protein supplements. Headspace solid phase microextraction- gas chromatography–mass spectrometry (HS-SPME-GC–MS) analysis was performed to examine VOCs in flaxseed meal, untreated flaxseed protein isolate (FPI- control), and resin-treated protein isolates. The flaxseed meal was predominant in hydrocarbons. After extraction, the flavour profile of FPI exhibited aldehydes, ketones, alcohols, and hydrocarbons. Resin treatment indicated that Amberlite XAD-16 N and Diaion HP-20 were more effective at reducing total peak areas for hydrocarbons, aldehydes, alcohols, and acids/esters than Sepabeads SP-207 resin. Analysis of non-VOC using proton nuclear magnetic resonance ( 1 H NMR) showed that resin treatments decreased the sinapine content twelve times compared to the control and thirty-eight times compared to the flaxseed meal. The phenolic reductions were resin-dependent: Amberlite XAD-16 N achieved the highest reduction for gallic acid, ferulic acid reduction was similar across all resins, while chlorogenic acid reduction was approximately 50 % for all resins used. Additionally, the levels of cyanogenic glucosides were significantly reduced by resin treatment. The functional properties of the resin-treated protein isolates were comparable to the control. Overall, the combination of protein extraction with resin treatment was more effective than the extraction alone at reducing both VOCs and non-VOCs, supporting the use of resins to mitigate flaxseed off-flavours. • The use of adsorbent resins during protein extraction reduced the off-flavour compounds in flaxseed during protein extraction. • Amberlite XAD-16 N and Diaion HP-20 resins were the most effective at lowering VOCs. • Phenolics were reduced significantly by resin treatment. • Protein functionality remained unchanged after resin treatment.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.070
GPT teacher head0.390
Teacher spread0.319 · 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 designBench or experimental
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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueFood Research InternationalSame topicProteins in Food SystemsFrench-language works237,207