Prediction of Microalgae Total Solid Concentration by Using Image Pattern Technique
Haikal Nando WINATA, Ryozo NOGUCHI, Ahamed TOFAEL, Muhammad Ansori NASUTION
Digital image processing have the potential for estimating biomass during cultivation of microalgae in Photobioreactor (PBR). In this research, computer algorithm and non-destructive method were implemented to predict the total concentrated solid of dry microalgae. This research used the native microalgae samples from the experimental facility located at the Minamisoma city of Fukushima Prefecture in Japan. Dry microalgae (DCW) were dissolved in a predetermined concentration range up to 12 g DCW L-1 and proven to be efficiently used up to 3 g DCW L-1. Raw red, green and blue (RGB) values in biomass were extracted and converted into Grayscale (GS) images. Furthermore, GS images were compared with seven conversion methods for determining the most suitable conversion results. The GS methods were investigated: luminance, intensity, monotonic, desaturation, average, minimum decomposition and lightness grayscale methods. The GS method was used to simplify the algorithm, for increasing efficiency in analyzing images. Each GS image of microalgae biomass aimed to derive a special pattern that only each image has in accordance with its concentration. For the result, luminance GS was found the most suitable method for recognizing color pattern identifier to determine total solid concentration using the image taken from the mobile device (R2 = 0.9033).
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