Moisture-Dependent Physical Properties of Sunflower (SHF8190)
Bibliographic record
Abstract
Physical properties are very important in design and manufacturing of harvest and post harvest machines. In this research some physical properties of sunflower seeds (SHF8190 variety) were determined as a function of moisture content in the range of 4-22 % wet basis (w.b.) using standard techniques. The average length, width, thickness, geometric mean diameter, equivalent diameter, arithmetic diameter, sphericity, surface area and angle of repose ranged from 12.14 to 12.57 mm, 5.79 to 6.38 mm, 3.86 to 4.09 mm, 6.47 to 6.85 mm, 6.56 to 6.97 mm, 7.27 to 7.61 mm, 53.33% to 55.42%, 112.16 to 125.01 mm2 and 41 to 57° as the moisture content increased from 4% to 22% w.b., respectively. The thousand grain weight (TGW) increased from 80.3 to 96.8 g whereas the bulk density decreased from 410 to 380 kgm-3 and the true density from 740 to 980 kg m-3 with an increase in the moisture content range of 4–22 % w.b.The data of sunflower seeds showed that the porosity ranged from 44.59 to 61.22%. The static coefficient of friction of sunflower seeds increased linearly against different surfaces of structural materials, namely, plastic (0.29–0.55), plywood (0.36–0.53), and galvanized iron (0.36–0.55) and the static angle of repose increased from 41º to 57º, respectively when the moisture content increased from 4 % to 22% w.b.
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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".