Mechanical stress on canola seed during dehulling
Bibliographic record
Abstract
The mature canola seed comprises an embryo, a group of structures that have a high content of protein and oil, and a fibrous seed coat held together by endosperm tissues. High-quality canola meal production requires removal of fiber-rich seed hull that typically contributes little nutrient value. Canola hull accounts for more than 70.0% of the insoluble fiber within the seed, which limits its uses as feed. Dehulling canola seed, before oil extraction, increases the protein content and decreases fiber content in the meal, to up to 50.0% and to down to 10.0%, respectively. Due to the complexity in dehulling canola seeds, several methods have been explored by the canola processing industry. However, little research has been conducted in analyzing the effects that mechanical dehulling methods have on seeds. In this study, we conducted mechanical tests to characterize seed behavior and hull fracture under uncoupled stresses such as compression and shear;stresses generated by the common dehulling equipment used in the industry, such as mills. All tests were carried out on single seeds at different moisture contents, from 5.00% to 25.0% wet mass basis (w.b.). Over a range of moisture contents studied, shear loading mode limited deformation of embryos in comparison to compression loading. Additionally, hardness tests were performed with a nano-indenter machine to determine seed hull properties. The overall results from these experiments provided information used to construct a computational model that represents canola seed deformation under compression stress.
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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) | 0.002 | 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".