Microalgae growth and diversity in anaerobic digestate compared to synthetic media
Bibliographic record
Abstract
Economizing microalgal cultivation is a considerable milestone targeted by efforts put into microalgal biorefineries. In light of that, the present study was aimed to explore the potential of using anaerobic liquid digestate (ALD) as culture media to grow microalgae and compared it with three different synthetic media (i.e., N8, BBM, and M8) in terms of biomass yield, fatty acid composition, and nutrient utilization/recovery. Moreover, a mixed culture of wild-type microalgae was employed in this study owing to the ability of mixed cultures to survive extreme conditions, eliminating the risk of losing the culture easily, as it mostly happens with pure cultures. The highest nutrient yield coefficients were achieved when the mixed microalgae culture was cultivated in ALD, where the yield coefficient for nitrogen (YN) and yield coefficient for phosphorus (YP) were 10.7 mg biomass mg-1 N and 98 mg biomass mg-1 P, respectively. The highest lipid content (34%) and the highest concentrations of C16:0 (114 mg L-1) and C18:0 (60.9 mg L-1) were also recorded when the mixed microalgae culture was cultivated in ALD. Furthermore, the polyunsaturated fatty acids (PUFA) content also increased significantly in ALD, a beneficial phenomenon as PUFAs in microalgae allow them to adapt more effectively to extreme conditions. Based on the microbial community analysis performed using the multi-marker metabarcoding approach, Diphylleia rotans, Synechocystis PCC-6803, Cyanobium gracile PCC 6307, and Chlorella sorokiniana were identified as the most abundant species in the ALD growth. Overall, based on the findings of the present study, ALD could be used as a promising cultivation medium for microalgae, offering a process integration approach to combine anaerobic digestion and algae cultivation as an effective way to simultaneously treat the high-strength dark-colored ALD and valorize it into profitable byproducts.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".