Baccilus amyloliquefacins Strains Isolated in a Wastewater Treatment Plant: Molecular Identification and Amylase/Protease Production Capacity
Bibliographic record
Abstract
This study centred on isolating and characterizing Bacillus amyloliquefaciens strains derived from wastewater sludge to assess their potential for sludge treatment. Samples were collected from the Etoa wastewater sludge treatment plant in Yaounde, Cameroon. The isolates were obtained on nutrient agar medium and were identified through morphological and biochemical characterization, followed by 16S rRNA gene sequencing analysis. The sequences showed 99–100% similarity with Bacillus amyloliquefaciens strains in the NCBI database. The isolates exhibited significant in vitro enzymatic activities, including catalase, amylase, and protease production, indicating their ability to degrade hydrogen peroxide starch and proteins, respectively. The results confirmed the in vitro potential of Bacillus amyloliquefaciens as a promising microbial agent for organic matter degradation in wastewater sludge. Although the findings were limited to laboratory conditions, they provided a foundation for future pilot-scale or in situ studies aimed at validating their practical efficiency. This research contributes to the development of microbial-based and eco-efficient strategies for sustainable sludge management.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".