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Record W2909021884 · doi:10.5539/jfr.v8n1p52

Sugar Profile of Syrups from Malted and Unmalted Rice of Different Varieties

2019· article· en· W2909021884 on OpenAlexvenueno aff
Chigozie E. Ofoedu, Chijioke M. Osuji, Moses Ojukwu

Bibliographic record

VenueJournal of Food Research · 2019
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
FundersTertiary Education Trust Fund
KeywordsMaltotrioseMaltoseRaffinoseGlucose syrupStachyoseSugarFood scienceStarchChemistryAlpha-amylaseSucroseBrewingAmylaseHydrolysateMaltitolHydrolysisFermentationBiochemistryEnzyme

Abstract

fetched live from OpenAlex

Rice syrup was produced from ten varieties of locally available rice in Nigeria. Flours of malted and unmalted rice from different varieties were treated with a combination of starch hydrolyzing enzymes (Amyloglucosidase, Bacterial α-amylase and Fungal α-amylase); and the starch hydrolysates were either filtered and/or centrifuged at the end of hydrolysis. The resulting rice syrup was evaluated for sugar compositions (maltose, glucose, maltotriose, sucrose, raffinose and stachyose) using HPLC. The results showed that syrups from malted rice had significantly higher (p<0.05) maltose and maltotriose concentration than syrups from unmalted rice. The resultant syrup is a ‘High Maltose Syrup’ since maltose was found to be the predominant sugar in the rice syrup with concentration of above 50% especially for malted samples. Rice syrup can be widely applied as a potential raw material in beverage and confectionery industries as well as a good adjunct for brewing since the sugar profile of the rice syrup was similar to that of barley wort.

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 score0.035
Threshold uncertainty score0.251

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.060
GPT teacher head0.329
Teacher spread0.269 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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