Effect of Grain Moisture Content and Roller Mill Gap Size on Various Physical Properties of Yellow Dent Corn Flour
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".