How green is green? Long‐term relationships between green seeds and chlorophyll in canola grading
Bibliographic record
Abstract
Abstract Chlorophyll is undesirable in canola seeds because it is extracted into the oil resulting in problems during processing and utilization. In the Canadian grain grading system, and in similar systems in use in the United States and Australia, chlorophyll is estimated in canola seeds subjectively by crushing and counting the number of distinctly green seeds in a sample while simultaneously assessing the overall natural color of the crushed seeds. Chlorophyll contents of canola may be determined by extraction with solvent followed by spectrophotometric analysis or by using NIR instrumentation, capable of operating in the visible region and calibrated against samples with known amounts of chlorophyll. The relationship between the green seeds and chlorophyll content in canola export shipments from 1988 to 2001 was found to be linear. The intercept, referred to as the background chlorophyll, ranged from 6 to 16 mg/kg, and the slope ranged from 300 to 1000 mg/kg per green seed. In recent years, both the background chlorophyll and the slope have been increasing, resulting in an increase in the chlorophyll levels in top‐grade canola exported from Canada. The increase may be partly a result of the change in proportion of species of canola grown in Canada, and also may result from changes in perception of what constitutes a green seed. The use of an objective measurement of chlorophyll is recommended to improve the consistency of the grading system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".