Biomass quantification and 3-D topography reconstruction of microalgal biofilms using digital image processing

Abstract

An accurate and non-invasive technique for online biomass quantification of microbial attached growth is needed. In this research, image processing through Red-Green-Blue (RGB) analysis is used to assess biomass thickness from simple macroscopic images captured from microalgal biofilms by a digital camera. The results show that the green (G) vector in images of an Ettlia sp. biofilm can estimate the biomass concentration with R2 = 0.994 through an exponential correlation. Moreover, the R2 coefficient for the biofilm thickness measurement using the G vector is 0.973, which shows the high potential of this method. Furthermore, using the mathematical correlation between the G index and the biofilm thickness, it is possible to reconstruct the 3-D topography of a microalgal biofilm and to calculate the quantitative parameters, such as biomass yield and thickness, at every specific point of the biofilm. RGB analysis can easily determine the biofilm concentration and 3-D topography with satisfactory accuracy. This is promising technique for biofilm quantification and can be used in different applications, such as wastewater treatment by moving a bed biofilm reactor (MBBR), which was formerly possible only through sophisticated techniques.