Current techniques for identifying the presence of cyanobacteria in a given water sample are cumbersome. This project is an attempt to simplify the process by using image capture with smartphones. Experiments were designed to ascertain if it is possible to detect cyanobacteria present in a water sample based on measurements of color and transmission spectra. Four types of organisms were used in the experiment. A colonial and a filamentous variant of cyanobacteria and of green algae were measured and compared. In these tests, the results from the four smartphones followed the same trends. All four smartphones displayed a linearity in the relationship between the C* values measured by the spectrophotometer vs. the C* values captured by the smartphone cameras for both types of cyanobacteria and for the colonial green algae. The behavior of the filamentous green algae differed from the behavior of the other organisms and presented an S-shaped curve when comparing the C* values from the spectrophotometer and camera. Each smartphone was able to capture this strange behavior, lending hope that it may be possible to successfully use smartphone cameras for the purpose of detection with further work. Only four smartphones were tested, so more would need to be tested to make greater generalizations about the use of this technique.
Katherine Carpenter, Anthony Vodacek, Susan Farnand, "Smartphone Calibration for Crowd-Sourced Determination of the Presence of Cyanobacteria in Water Samples" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Quality and System Performance XV, 2018, pp 405-1 - 405-7, https://doi.org/10.2352/ISSN.2470-1173.2018.12.IQSP-405