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Record W2049553252 · doi:10.3390/ijms12031563

Distribution and Molecular Characterization of β-Glucans from Hull-Less Barley Bran, Shorts and Flour

2011· article· en· W2049553252 on OpenAlexaff
Xueling Zheng, Limin Li, Qi Wang

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2011
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBranArabinoxylanCultivarFood scienceChemistryGlucanStarchBeta-glucanPolysaccharideXylanaseBotanyBiologyBiochemistryEnzymeRaw materialOrganic chemistry

Abstract

fetched live from OpenAlex

Six hull-less barley cultivars widely grown in China were roller-milled to produce bran, shorts and flour fractions. The distribution and molecular characteristics of β-glucans from the three roller-milled fractions were investigated. The β-glucan contents in the six hull-less barley cultivars varied from 4.96% to 7.62%. For all the six cultivars, the shorts fraction contained the highest concentration of β-glucan (8.12-13.01%), followed by bran (6.15-7.58%) and flour (2.48-2.95%). Crude β-glucans were prepared from the three roller-milled fractions using aqueous sodium carbonate (pH 10). These preparations contained 45.38-71.41% β-glucan, 10.81-17.26% arabinoxylan, 2.6-9.6% protein, 2.7-9.0% starch, and 5.23-9.68% ash. Purification using α-amylase and β-xylanase in combination with pH adjustment and dialysis produced high purity β-glucan preparations (91-95%). The molecular weight (Mw) of β-glucan preparations from roller-milled fractions ranged from 117,600 to 852,400 g/mol. β-Glucan from flour had higher Mw than those from shorts and bran within the same cultivar, and β-glucan preparations from bran had the lowest Mw.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.260

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 head0.021
GPT teacher head0.250
Teacher spread0.228 · 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

Citations53
Published2011
Admission routes1
Has abstractyes

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