Prediction of concentration for microalgae using image analysis
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Prediction of concentration for microalgae using image analysis Haikal Nando Winata 1,2 & Muhammad Ansori Nasution 3 & Tofael Ahamed 4 & Ryozo Noguchi 4 Received: 28 January 2020 / Revised: 3 September 2020 / Accepted: 7 October 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
Maintaining the optimum growth rate and estimating the concentration of microalgae are critical in improving microalgae production. An efficient concentration assessment of microalgae is essential for a timely and effective determination of the harvest period. This study proposes the luminance and viscosity methods to predict the concentration of microalgae. Image analysis was applied to measure the concentration of native microalgae: Desmodesmus sp., Scenedesmus sp., Dictyosphaerium sp., and Klebsormidium sp. The experiments were performed using different concentrations of the dry cell weight (DCW) of these microalgae species. A dual-camera device was used to capture the images of the DCW solution in a flask. For the confirmation of viscosity, a viscometer was used to determine the concentration of microalgae. A comparative analysis was performed between the data from the image analysis and viscosity method. The results from the viscosity method showed a higher accuracy with R2 = 0.9784 and the luminance method with R2 = 0.8266. Further investigations revealed that the brightness of the DCW image had a limitation at a specific concentration where the color was unrecognized. The current image processing method has the potential to be applied in an outdoor cultivation facility for real-time data acquisition. Both methods have advantages in terms of required time and experimental costs. The image analysis method provides an alternative way to efficiently monitor the cultivation and harvesting of microalgae. Keywords Dry cell weight . Microalgae . Concentration . Luminance method . Viscosity method Abbreviations DCW Dry cell weight GS Grayscale HTL Hydrothermal liquefaction LGS Luminance grayscale
* Ryozo Noguchi [email protected] Extended author information available on the last page of the article
Multimedia Tools and Applications
MP Megapixels ORP Open raceway pond PBR Photobioreactor RGB Red, green, and blue ROI Region of interest Nomenclature B Blue color (px) b Normalized blue color (px) Clinear Linear intensity value of RGB Crgb Nonlinear value of RGB DCW Dry cell weight (%) G Green color (px) g Normalized green color (px) R Red color (px) r Normalized red color (px) Coefficient of determination (-) R2 T Temperature (°C) v Kinematic viscosity (mm2/s) ρ Density (kg/m3) ϒ Luminance (px) μ Basic viscosity (mPa·s) ϑ Dynamic viscosity (mPa·s) f Color channel pixel value x Color channel pixel value coordinates y Color channel pixel value coordinates
1 Introduction 1.1 Cultivation stage of microalgae biofuel production Microalgae are single-celled microscopic organisms that live in water. They are considered the third-generation source of biofuel and a potential resource for increasing bioe
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