A <sup>1</sup>H NMR study of the fatty acid distribution in developing flax bolls before and after a cooking treatment
Bibliographic record
Abstract
Flax is an important Canadian crop that contains a large percentage of fatty acids (FAs) by seed weight. Gas chromatography (GC) methods have traditionally been used to study FA distributions in oil seed crops. These methods, however, require sample preparation involving saponification and methyl ester formation. Recently, 1H NMR has been shown to be an excellent way to directly measure FA distributions in edible oils using a nondestructive and experimentally faster methodology. As such, we have examined the FA profiles in developing bolls of flax cultivar AC McDuff using 1H NMR and assessed the effect of cooking on FA stability and distribution. The data confirmed the high percentage of linolenic acid in mature AC McDuff flax seed compared to early stages of development and showed that FAs at early stages of boll development are more prone to thermal degradation. Triacylglycerol was found to be important to FA stability to heat. It was also observed that the FAs did not convert from cis to trans under the cooking process used herein. The usefulness of 1H NMR spectroscopy in oils chemistry is highlighted.
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 | 0.000 | 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".