Current lipid extraction methods are significantly enhanced adding a water treatment step in Chlorella protothecoides
Bibliographic record
Abstract
Microalgae have the potential to rapidly accumulate lipids of high interest for the food, cosmetics, pharmaceutical and energy (e.g. biodiesel) industries. However, current lipid extraction methods show efficiency limitation and until now, extraction protocols have not been fully optimized for specific lipid compounds. The present study thus presents a novel lipid extraction method, consisting in the addition of a water treatment of biomass between the two-stage solvent extraction steps of current extraction methods. The resulting modified method not only enhances lipid extraction efficiency, but also yields a higher triacylglycerols (TAG) ratio, which is highly desirable for biodiesel production. Modification of four existing methods using acetone, chloroform/methanol (Chl/Met), chloroform/methanol/H 2 O (Chl/Met/H 2 O) and dichloromethane/methanol (Dic/Met) showed respective lipid extraction yield enhancement of 72.3, 35.8, 60.3 and 60.9%. The modified acetone method resulted in the highest extraction yield, with 68.9 ± 0.2% DW total lipids. Extraction of TAG was particularly improved with the water treatment, especially for the Chl/Met/H 2 O and Dic/Met methods. The acetone method with the water treatment led to the highest extraction level of TAG with 73.7 ± 7.3 µg/mg DW, which is 130.8 ± 10.6% higher than the maximum value obtained for the four classical methods (31.9 ± 4.6 µg/mg DW). Interestingly, the water treatment preferentially improved the extraction of intracellular fractions, i.e. TAG, sterols, and free fatty acids, compared to the lipid fractions of the cell membranes, which are constituted of phospholipids (PL), acetone mobile polar lipids and hydrocarbons. Finally, from the 32 fatty acids analyzed for both neutral lipids (NL) and polar lipids (PL) fractions, it is clear that the water treatment greatly improves NL-to-PL ratio for the four standard methods assessed. Water treatment of biomass after the first solvent extraction step helps the subsequent release of intracellular lipids in the second extraction step, thus improving the global lipids extraction yield. In addition, the water treatment positively modifies the intracellular lipid class ratios of the final extract, in which TAG ratio is significantly increased without changes in the fatty acids composition. The novel method thus provides an efficient way to improve lipid extraction yield of existing methods, as well as selectively favoring TAG, a lipid of the upmost interest for biodiesel production.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".