Cyanobacterial detection using in vivo fluorescence probes: Managing interferences for improved decision‐making

Abstract

The applications of in vivo probes that can detect the fluorescence of cyanobacterial phycocyanin are emerging and widely used for cyanobacterial detection in source waters. The objectives of this project were to study the sources of interferences involved with the readings of five probes (three commercially available probes and two prototype probes) using laboratory cultures and field samples. To compare the direct readings of different probes, the probe readings were presented in the form of a biovolume equivalent of cyanobacteria. Inorganic turbidity and the presence of algal biomass interfered with probe readings. A correction factor was developed for the cyanobacteria probes using simultaneous chlorophyll a measurements. The field data demonstrate that the potential underestimation of cyanobacterial biomass that corresponds to alert levels is a major issue with the application of in vivo probes. These alert levels are used to trigger monitoring and management actions. This study shows that the correlation between a probe's reading and cell count is almost meaningless, and that the correlation to biovolume is a relevant option for management purposes. Results show that probe users should be fully aware of the sources of interferences when applying and interpreting the results. In addition, the authors offer a novel procedure that corrects for chlorophyll a interference.

Breakthrough of cyanobacteria in bank filtration

“…Below 1 mm 3 L À1 , the PC probe may underestimate the cyanobacterial biovolume by about 20%. Probe readings for log PC were correlated to log chl a in RFU (r 2 ¼ 0.71, p < 0.001) and could indicate a partial interference from green algae (Zamyadi et al, 2012b). However, the Table 1 General water quality characteristics of well water and Lakes A and B from the mean values of grab samples collected at 0.5 m below the surface from July to October 2013 (n ¼ 15).…”

“…S1). Cyanobacteria contribute to turbidity, but turbidity can also influence the probe's RFU readings (Zamyadi et al, 2012b). The higher turbidity and RFU values at 10 m depth cannot be explained by the probe disturbing the bottom sediments because Lake B's depth was greater than 10 m and the probe did not reach the lake's bottom sediments.…”

Low‐risk cyanobacterial bloom sources: Cell accumulation within full‐scale treatment plants

“…Using the maximum Microcystis cellular toxin production (Falconer et al, 1994), McQuaid et al (2011) published the microcystin production per biovolume of Microcystis (0.014 pg microcystin per 1 μm 3 Microcystis ). Furthermore, the Microcystis biovolume (0.5 mm 3 /L) equivalent to 1 RFU of the in vivo phycocyanin probe reading has been published recently (Zamyadi et al, 2012a). The average of the in vivo probe readings in the entire volume of water over the submerged launders, which collect the clarified water and conduct it to the filters, is 16 RFU (Figure 7, parts A and B).…”

“…The Québec action plan requires predefined interventions at a DWTP if at least one raw water sample (before any treatment) taken at the water intake of a plant during the past five years contains more than 10,000 cells/ mL. However, these interventions are triggered by the results of monitoring, most often conducted on a weekly or biweekly basis, that may be insufficient to identify critical periods of cyanobacterial presence (Zamyadi et al, 2012a;Newcombe et al, 2010).…”

Hydrophysical and Hydrochemical Controls of Cyanobacterial Blooms in Coursey Pond, Delaware (USA)

“…Due to turbidity, temperature, and scattering interferences associated with these in vivo fluorescence measurements, the ratio of in vivo Pc to in vivo Chl (Pc/Chl) was used to characterize the relative abundance of cyanobacteria in this study. Other investigators have studied and discussed the relationships between in vivo fluorescence, the actual concentrations of Chl and Pc, the structure of the phytoplankton community, and the difficulties of using these measurements as quantitative indicators of plankton abundance (Chang et al, 2012; Zamyadi et al 2012; Bowling et al, 2016; Hodges et al, 2017). …”