Preliminary study of fungi from mangrove sediments as a bioremediation agent of lead (Pb) heavy metal
Bibliographic record
Abstract
Abstract The mangrove ecosystem in Tapak Village is one of the coastal areas in Tugu District, Semarang, Central Java and close to the industrial area. This mangrove ecosystem presumed to be contaminated by heavy metals. This study aims to analysis of lead heavy metal in Tapak, isolate fungi from mangrove sediments, and identify the potential fungus according to molecular approach. The sampling method used a purposive random sampling method with 4 sampling points. The isolation of fungi was carried out using the dilution method and then cultured on the general Potato Dextrose Agar (PDA) media. The purified isolates were tested its ability as a bioremediation agent of lead heavy metal (Pb) and were identified molecularly using ITS1 and ITS4 as universal primers. The results of the analysis of the Pb content in the sediment samples using the Atomic Absorption Spectrophotometer (AAS) ranged from 59.07-76.76mg/Kg, where these results exceeded the CCME (Canadian Council of Ministers of the Environment) quality standards, 2001, with Pb standards of 35mg/Kg. Based on the screening of fungal isolates on media supplemented with (Pb) of 70 ppm, a total 18 isolates were purified. There were 9 isolates with the fastest growth in observations for 7 days. One of the 9 fastest-growing isolates, MT.1.E, was identified molecularly using Internal Transcribe Spacer (ITS) region and the homology was closely related to Aspergillus fumigatus which has a 100% similarity. According to this study, fungi can be proposed as a bioremediation agent.
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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) | 0.000 | 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 | 0.000 |
| 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".