Analytical Method Assessment for the Determination of DHA and Fatty Acids Present in Unextracted <i>Aurantiochytrium limacinum</i> Biomass
Bibliographic record
Abstract
Research into long-chain polyunsaturated fatty acids (LC-PUFA), such as docosahexaenoic acid (DHA C22:6 n-3), has shown that their inclusion in the human diet is linked with many health benefits. This has led to an increased interest in the enrichment of certain foodstuffs with DHA by supplementing animal fed with DHA-rich ingredients which can lead to an increased uptake in the meat, milk and eggs animal by-products. The microalgae Aurantiochytrium limacinum has been found to be especially useful in this pursuit. It is subsequently desirable to availably have a simple and robust method for the routine analysis of DHA and other fatty acids in the algal biomass. The AOAC method 996.06 is often followed for the analysis of fatty acids in foods and demonstrating that its fitness for purpose in the analysis of DHA and additional fatty acids in Aurantiochytrium limacinum is therefore the objective of this paper. A validation of the method for the determination of DHA and three other fatty acids in Aurantiochytrium limacinum is presented. The method was found to be linear over the following ranges for each fatty acid methyl ester (FAME) analyte; 50 to 15,000 μg/ml (C14:0), 300 to 95,000 (C16:0), 25 to 15,000 (C18:0) and 300 to 59,375 (C22:6). The accuracy, precision and LOD and LOQ of the method were confirmed and its robustness tested. The application of the method to assess the stability of Aurantiochytrium limacinum containing two alternative antioxidants was further examined. The investigation showed that DHA was stable over six months with the inclusion of either Duralox? or ethoxyquin as an antioxidant and ethoxyquin could additionally stabilize DHA in Aurantiochytrium limacinum up to 24 months.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".