Implications of dissolved organic carbon, turbidity and salinity on detection and monitoring of cyanobacteria using UV–VIS derivative spectrophotometry
Bibliographic record
Abstract
Cyanobacterial blooms are now a long-standing and recurring environmental issue around the globe due to their potential toxicity and accompanying negative impacts, such as the formation of taste and odor compounds, water discoloration, scum formation, to name a few. Early detection and routine monitoring of source water is, therefore, an increasing need, and methods to promptly identify cyanobacterial presence are critical. In this study, M. aeruginosa was used to test the impact of three water quality parameters (WQP), including salinity, DOC (dissolved organic carbon), and turbidity, on the detection and monitoring of cyanobacteria using UV-Vis derivative spectrophotometry. The study established the method detection limits under a wide range of WQP. Further, the effect of two cuvette pathlengths (50-, and 100-mm) and two exposure times (90 and 180 mins) at two peaks, corresponding to photopigments chlorophyll-a ( Chl-a ) and phycocyanin (PC), were investigated while applying and Savitzky-Golay (S-G) first derivative of absorbance technique to improve sensitivity. Results indicate that the relationship between the two photopigments and absorbance was generally strong (R 2 > 0.9), except for higher turbidity tests (R 2 > 0.8), and 100 mm pathlength was found to be the most sensitive in terms of detection. Additionally, there was no significant change in absorbance, detection limit, or slope observed between the two exposure times. The lowest detection limits using the established method were found to be 11,083 cells/mL and 12,632 cells/mL for 1 mg/L DOC for Chl-a and PC, respectively. Sensitivity analyses revealed slight variations in slopes of regression with increasing WQP concentration, which was expected with increasing interfering contaminants. Overall, the results demonstrate that despite varying WQPs, with the aid of derivate spectrophotometry and longer cuvette pathlength (100 mm), the method can be successfully used for potential detection and monitoring of cyanobacteria in different source waters. • Derivative spectrophotometry was used for testing cyanobacteria in water matrices. • 3 concentrations of salinity, dissolved organic carbon, and turbidity were tested. • Lowest MDL was found to be 11,083 & 12,632 cells/mL for 1 ppm DOC for Chl-a and PC . • Similar results were found with increasing exposure times from 90 and 180 mins. • Longer cuvette pathlengths (50 and 100 mm) could sensitively detect M. aeruginosa .
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".