Cultivation of Microalgae in Unsterile Malting Effluent for Biomass Production and Lipid Productivity Improvement
Bibliographic record
Abstract
Microalgae have the potential to grow in nutrient-rich environments and have the ability to accumulate nutrients from wastewater. The nutrients in malting wastewater are ideal for microalgae cultivation. However, there is limited published work on the growth characteristics of freshwater microalgae grown in malting effluent. This study examined the potential of diluted malting effluent for the growth of freshwater green algae Chlorella sp. and Chlamydomonas sp. isolated from northern Ontario and subsequent biomass and lipid production. Under the 18:6 h light/dark cultivation cycle, the highest cell number counted (540 × 104 cell·mL−1 on day 20) and total chlorophyll content were found in 50% diluted malting effluents for Chlorella sp., whereas the 70% dilution concentration was the most productive for Chlamydomonas (386 × 104 cell·mL−1 on day 16). The total lipid content was higher in the 50% dilution concentration of malting effluent in both Chlorella sp. (maximum 20.5%–minimum 11.5% of dry weight) and Chlamydomonas sp. (max 39.3%–min 25.9% of dry weight). These results emphasize the suitability of using unsterile diluted malting effluent for microalgae cultivation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".