MétaCan
Menu
Back to cohort
Record W2148073341 · doi:10.1002/jsfa.2997

Decrease of the chlorogenic acid content in commercial sunflower meal using a polyphenol oxidase preparation secreted by the white‐rot fungus <i>Trametes versicolor</i> ATCC 42530

2007· article· en· W2148073341 on OpenAlexaff
Emerson Martinez, Z. Duvnjak

Bibliographic record

VenueJournal of the Science of Food and Agriculture · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEnzyme-mediated dye degradation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTrametes versicolorChlorogenic acidFood sciencePolyphenol oxidaseSunflowerChemistryMealExtraction (chemistry)PolyphenolAnimal feedBiologyEnzymeBiochemistryLaccaseHorticultureChromatographyAntioxidant

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: Sunflower meal (SFM) is a by‐product from the oil extraction process from sunflower seeds. The meal is used as a protein supplement in the livestock diet. However, relatively high levels of polyphenols, among which chlorogenic (CGA) and caffeic acids are in larger amounts, in the meal compromises its use for animal feed and human consumption. The aim of this work was to investigate an enzymatic process for upgrading the quality of SFM by decreasing its CGA content using an enzyme preparation from the white‐rot fungus Trametes versicolor . RESULTS: The effects of pH, temperature, enzyme and meal concentrations, and mass transfer on the decrease of the CGA content in SFM were investigated. It was found that: (1) the optimum pH and temperature were 3.4 and 45 °C, respectively. (2) The system was saturated with the enzyme when its concentration was 5 nkat/mL of liquid phase; (3) the agitation speed of the system influenced the extraction of CGA from the meal; and (4) the conversion of CGA in the SFM system increased in the presence of larger volumes of liquid phase. CONCLUSIONS: The enzyme preparation used in the experiments is able to decrease successfully the CGA content in SFM. Copyright © 2007 Society of Chemical Industry

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.222
Teacher spread0.201 · 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
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Science of Food and AgricultureSame topicEnzyme-mediated dye degradationFrench-language works237,207