Development of Extraction and Gas Chromatography Analytical Methodology for Cyanogenic Glycosides in Flaxseed (Linum usitatissimum)
Bibliographic record
Abstract
The development of well-characterized rapid methodology for the extraction and gas chromatographic analysis of the cyanogenic glycosides linustatin and neolinustatin from flaxseed (Linum usitatissimum L.) is reported. Two quantitation methods using phenyl-beta-D-glucopyranoside as an internal standard are described: direct quantitation using linustatin and neolinustatin external standard curves [standard curve slope variabilities of 2.6 and 5.7% relative standard deviation (RSD), respectively, over 7 days] or by use of methyl-alpha-D-glucopyranoside as a surrogate external standard, with conversion factors to convert to linustatin and neolinustatin concentration [1.109 +/- 0.015 (SD) mg linustatin/mg methyl-alpha-D-glucopyranoside and 1.180 +/-0.067 (SD) mg neolinustatin/mg methyl-alpha-D-glucopyranoside]. The former method is direct, thereby contributing less uncertainty to the method, and the latter adds a small degree of uncertainty coupled with considerable cost savings. Limits of detection for all standards were in the low- to sub-nanogram level and were 10-100 times lower than the lower limit of quantitation (LOQ). Repeatability precision was performed on 2 separate days at the lower and upper LOQs, with the RSD in peak response being 1% or lower in all cases. Extraction methods were evaluated for their ability to extract linustatin and neolinustatin from flaxseed using several combinations of aqueous ethanol, and recoveries were determined against the highest yielding method. Recoveries were as low as 82%, indicating that optimized extraction methodology is critical for the accuracy of results.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".