Production, Processing, and Protection of Microalgal n-3 PUFA-Rich Oil
Bibliographic record
Abstract
Microalgae have been increasingly considered as a sustainable "biofactory" with huge potentials to fill up the current and future shortages of food and nutrition. They have become an economically and technologically viable solution to produce a great diversity of high-value bioactive compounds, including n-3 polyunsaturated fatty acids (PUFA). The n-3 PUFA, especially eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), possess an array of biological activities and positively affect a number of diseases, including cardiovascular and neurodegenerative disorders. As such, the global market of n-3 PUFA has been increasing at a fast pace in the past two decades. Nowadays, the supply of n-3 PUFA is facing serious challenges as a result of global warming and maximal/over marine fisheries catches. Although increasing rapidly in recent years, aquaculture as an alternative source of n-3 PUFA appears insufficient to meet the fast increase in consumption and market demand. Therefore, the cultivation of microalgae stands out as a potential solution to meet the shortages of the n-3 PUFA market and provides unique fatty acids for the special groups of the population. This review focuses on the biosynthesis pathways and recombinant engineering approaches that can be used to enhance the production of n-3 PUFA, the impact of environmental conditions in heterotrophic cultivation on n-3 PUFA production, and the technologies that have been applied in the food industry to extract and purify oil in microalgae and protect n-3 PUFA from oxidation.
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 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) | 0.001 | 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 | 0.001 |
| 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 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".