Eurasian water milfoil: Composition, recovery of phenolics and anthocyanins, and saccharification
Bibliographic record
Abstract
Abstract Eurasian water milfoil (Myriophyllum spicatum; EWM) is an invasive aquatic weed that has spread worldwide but remains unstudied as a potential source of bioenergy and valuable chemicals. In this study, the composition of EWM biomass is characterized by determining the monosugar and lignin content, ash, and extractives. EWM extractives contain beneficial phenolic compounds, among them anthocyanin pigments. Following the biorefinery concept, a stepwise treatment of this aquatic plant was carried out toward integrating the extraction of phenolics with the saccharification of carbohydrates for viable biomass utilization. The recovery of phenolics and anthocyanin pigments was studied, in which different extracting compositions and conditions were applied. The antioxidant capacity of the extracts was evaluated. Saccharification was carried out using autoclaving, followed by hydrolysis using common cellulase enzyme. Different media were studied. Under the best condition, the carbohydrates contained were hydrolyzed to reducing sugars, and the conversion rate to glucose reached 90%. The yield of glucose was 0.245 g g−1 dried plant. This study demonstrates the potential of EWM as a source of antioxidants comparable to some phenolics‐rich algae, and as a bioenergy resource comparable with other sugar‐rich macrophytes.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".