Chromatographic, NMR and vibrational spectroscopic investigations of astaxanthin esters: application to “Astaxanthin-rich shrimp oil” obtained from processing of Nordic shrimps
Bibliographic record
Abstract
Astaxanthin (ASTX) is a keto carotenoid, which possesses a non-polar linear central conjugated chain and polar β-ionone rings with ketone and hydroxyl groups at the extreme ends. It is well known as a super anti-oxidant, and recent clinical studies have established its nutritional benefits. Although it occurs in several forms, including free molecule, crystalline, aggregates and various geometrical isomers, in nature it exists primarily in the form of esters. Marine animals accumulate ASTX from primary sources such as algae. Nordic shrimps (P. borealis), which are harvested widely in the Atlantic Ocean, form a major source of astaxanthin esters. "Astaxanthin-rich shrimp oil" was developed as a novel product in a shrimp processing plant in Eastern Canada. A compositional analysis of the shrimp oil was performed, with a view to possibly use it as a nutraceutical product for humans and animals. Astaxanthin-rich shrimp oil contains 50% MUFAs and 22% PUFAs, of which 20% are omega-3. In addition, the shrimp oil contains interesting amounts of EPA and DHA, with 10%/w and 8%/w, respectively. Astaxanthin concentrations varied between 400 and 1000 ppm, depending on the harvesting season of the shrimp. Astaxanthin and its esters were isolated from the oil and analysed by NMR, FTIR and Micro-Raman spectroscopy. Astaxanthin mono- and diesters were synthesized and used as standards for the analysis of astaxanthin-rich shrimp oil. NMR and vibrational spectroscopy techniques were successfully used for the rapid characterization of monoesters and diesters of astaxanthin. Raman spectroscopy provided important intermolecular interactions present in the esterified forms of astaxanthin molecules. Also discussed in this paper is the use of NMR, FTIR and Micro-Raman spectroscopy for the detection of astaxanthin esters in shrimp oil.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".