Determination of Glucosinolates in Canola Seeds Using Anion Exchange Membrane Extraction Combined with the High-Pressure Liquid Chromatography Detection
Bibliographic record
Abstract
A rapid, simple, and reliable method for the determination of individual glucosinolates in canola seeds was developed using a semiquantitative extraction of glucosinolates with anion exchange membranes and HPLC detection. In this one-step extraction procedure, a membrane (7 cm(2)) is placed in the seed suspension prepared by grinding and boiling 0.8 g of seeds in 20 mL of water. After 10 min of shaking on the mechanical shaker, the membrane is removed from the suspension, washed, and transferred to a vial containing 5 mL of 1 N tetramethylammonium chloride. The glucosinolates are eluted from the membrane by shaking the membrane for 10 min with the eluting solvent. The glucosinolate content in membrane eluates is determined by HPLC using sinigrin standards. A coefficient of variation ranging from 1.9 to 7.6% for aliphatic glucosinolates indicated very good reproducibility of the method. Because of the instability of 4-hydroxyglucobrassicin, the coefficient of variation for the determination of this indolyl glucosinolate was 13.9%. To verify the results of the membrane extraction/HPLC detection, this new method was compared with the existing colorimetric and GC procedures. Very good correlation (R(2) = 0.98) was obtained between the total glucosinolates determined by the membrane extraction/HPLC method and the palladate colorimetric procedure for 17 canola varieties. Concentrations of individual glucosinolates in five canola varieties were compared with the GC data. Very good agreement between these two methods was obtained for aliphatic glucosinolates. However, the membrane extraction/HPLC method yielded slightly higher values for 4-hydroxyglucobrassicin than the GC method, possibly indicating that the decomposition of this glucosinolate was reduced during the sample extraction with the membranes. The simplicity and low cost of the membrane extraction/HPLC method make it an attractive alternative to the existing procedures for glucosinolate analysis in canola seeds.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".