Determination of the fatty acid composition of canola, flax, and solin by near‐infrared spectroscopy
Bibliographic record
Abstract
Abstract The ability to rapidly measure key FA in oilseed crops would assist in the administration of identity‐preserved systems in the grain‐handling system or in selection systems in plant‐breeding programs. This study shows near‐infrared reflectance (NIR) spectroscopy to be a reliable method of determining FA composition in canola, flax, and solin (low‐linolenic flax), for oleic acid, linoleic acid, linolenic acid, and iodine value, and to a limited extent for saturated fat. Samples from cultivar trials, harvest surveys, and export shipments were scanned on a NIRSystems 6500 spectrometer (Silver Spring, MD), and calibrations were developed and optimized using modified partial least squares. SE of prediction results for prediction sets of canola, flax, and solin, were, respectively: oleic acid (0.77, 1.03, 0.62%); linoleic acid (0.71, 1.20, 0.37%); linolenic acid (0.42, 0.62, 0.08%); saturated FA (0.23, 0.39, 0.31%); and iodine value (0.63, 0.95, 0.43 units).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".