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Record W4213356840 · doi:10.5539/jfr.v11n2p16

Effect of Grain Moisture Content and Roller Mill Gap Size on Various Physical Properties of Yellow Dent Corn Flour

2022· article· en· W4213356840 on OpenAlexvenueno aff
Bernard Darfour, Nazira Mahmud, Kurt A. Rosentrater

Bibliographic record

VenueJournal of Food Research · 2022
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
FundersIowa State University
KeywordsRoller millParticle sizeCorn flourMoistureWater contentMaterials scienceAgronomyFood scienceChemistryRaw materialComposite materialGrindingBranBiology

Abstract

fetched live from OpenAlex

Corn has six main varieties grown globally for animal feed, human consumption, and commercial/industrial purposes. Flour is an end-product of corn dry-milling. Products that are derived from corn flour often show differences in physical, chemical, and pasting properties due to corn varietal differences, milling methods, differences in flour particle sizes, and drying temperatures. The study aimed to determine the effect of different moisture contents of yellow dent corn and roller gap sizes, on the physical properties of the resulting corn flour. The possibility to use the flour in the manufacturing of animal feed and ethanol production was also considered. Yellow dent corn grain with moisture contents (MC) of 8%, 14.0%, and 18%, and roller gap sizes (GAP) of 0.1016 mm, 0.2032 mm, and 0.3048 mm were used. The Witt corrugated roller mill equipment with rollers of 1/32 inches corrugations was used to produce fine grits and flours. The particle sizes obtained were between 0.54 mm and 0.75 mm which increased with an increase in MC and GAP. Grain with 8% MC and GAP of 0.1016 mm and 0.2032 mm, and grain with 14.0% MC and GAP of 0.1016 mm can produce flour of particle sizes good for swine feed. Grain with 8% MC and GAP of 0.3048 mm and grain with 14.0.0% MC and GAP of 0.1016 mm and 0.2032 mm can produce flour of particle sizes good for ruminant feed. Grain with 18% MC and GAP of 0.1016 mm, and grain with 14.0% MC and GAP of 0.2032 mm can produce flour of particle sizes good for poultry feed. GAP of 0.1016 mm and 8% MC can produce flour of particle sizes suitable for the ethanol production industry. Flour preparation should purposely be done based on grain MC and GAP. The geometric mean diameter of particle sizes ranged from 0.54 mm-0.75 mm, and the geometric mean diameter of particle sizes increased with increasing MC and GAP. Also, grains with 8% MC had the highest loss in flour, and the higher moisture of 18% significantly affected the red color of flour.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.092
GPT teacher head0.333
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2022
Admission routes1
Has abstractyes

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