Fractionation of Hairless Canary Seed (<i>Phalaris canariensis</i>) into Starch, Protein, and Oil
Bibliographic record
Abstract
Canary seed is an important specialty crop in Canada. The current market for this true cereal (i.e., belonging to the family Poaceae as wheat) is limited to feed for caged birds. However, canary seed holds a promise for many food and industrial applications based on its composition. Three wet milling procedures based on ethanol (E), water (W), and alkaline (A) extractions used in different order were investigated to determine extraction efficiency and purity of starch, protein, oil, and fiber separated from hairless canary seed, a variety developed for human consumption. Highest extraction efficiencies were obtained when canary seed was defatted with ethanol and then extracted with alkali and water (EAW process). Using this process, approximately 92% pure starch, 75% pure protein, and oil were recovered from canary seed groats. The highest purity of protein, however, was obtained when canary seed was fractionated by the EWA process, that is, defatted and then extracted with water followed by alkali. Fiber component separated prior to alkaline extraction contained high amounts of nonfiber components as indicated by its yield. The EAW extraction process seems to be more promising in canary seed fractionation based on recovery and purity of components.
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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".