The Moisture Content Effect on Some Physical and Mechanical Properties of Corn (Sc 704)
Bibliographic record
Abstract
Physical and mechanical properties of grains are necessary for the designing the facility of storage, handling and processing of agricultural products. Physical and mechanical properties of corn grains were determined as a function of moisture content in the range of 4.73-22% w.b. (wet basis) using standard techniques. The average length, width, thickness, geometric mean diameter, equivalent diameter, arithmetic diameter, sphericity, angle of repose, grain volume, surface area and aspect ratio ranged from 11.62 to 12.60 mm, 7.27 to 7.98 mm, 4.47 to 4.71 mm, 7.20 to 7.77 mm and 7.63 to 7.96 mm, 7.77 to 8.43 mm, 62.31% to 62.00%, 49° to 58°, 209.66 to 265.00 mm3, 137.69 to 160.09 mm2 and 63.05% to 63.77% as the moisture content increased from 4.73-22% w.b. With increase in moisture content, the bulk density was found to decrease from 710 to 649 kgm-3 whereas true density and porosity increased from 1250 to 1325 kgm-3 and 43.2% to 51.02%. In the moisture range from 4.73% to 22% w.b., studies on rewetted corn grains showed that the thousand grain weight (TGW) increased linearly from 271.0 to 321.4 g. The static coefficient of friction of corn grains increased linearly against surfaces of three materials, namely, plastic (0.32–0.51), plywood (0.48–0.60) and galvanized iron (0.38–0.65) and the static angle of repose increased from 49º to 58º when the moisture content increased from 4.73% to 22% w.b. The mechanical properties of corn were determined in terms of average rupture force and rupture energy. Rupture energy of the corn grains generally increased in magnitude with an increase in moisture content, while rupture force decreased for compression.
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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 | 0.000 |
| 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".