Measurement of algae concentration by using Color identification

Abstract

The measurement of algae concentration in water plays a crucial role in environmental monitoring and assessment. Traditionally, this quantification has been accomplished using methods such as gravimetric analysis or spectrophotometry. However, in recent years, innovative approaches have emerged to enhance the accuracy, efficiency, and cost-effectiveness of this process.One such advancement is the utilization of RGB (Red-Green-Blue) light absorption as a means to estimate the concentration of algae. The RGB color model, a fundamental representation of colors, involves the blending of three primary light beams to produce a wide spectrum of colors. Building upon this principle, Benavides et al. (2015) conducted pioneering research that demonstrated the potential of RGB light absorption as a viable method for approximating algae concentration. In their study, Benavides et al. established a correlation between the component weights of the RGB color space and the presence of algae in water. This correlation was particularly evident when employing the YCbCr color space representation, which facilitated a quantitative link between the RGB values and algae concentration. This innovative approach hinged on the selection of a suitable RGB light sensor. The researchers opted for the Arduino KY-016 3-color LED module, a cost-effective solution that seamlessly integrated an RGB LED and a light-to-voltage converter, based on the Arduino UNO R3 platform.The implementation of this low-cost device opened up new avenues for estimating algae concentration with remarkable accuracy. By leveraging the RGB light sensor's capabilities, the researchers were able to establish a practical framework for estimating algae concentration that holds potential for widespread application. This innovation carries significant implications for environmental monitoring, as it offers a streamlined and accessible method for assessing water quality and potential ecological imbalances caused by excessive algal growth. In conclusion, the research conducted by Benavides et al. showcases a paradigm shift in algae concentration measurement. Through the inventive integration of RGB light absorption and the YCbCr color space representation, coupled with the utilization of the Arduino KY-016 3-color LED module, the study introduces a novel, cost-effective approach to estimate algae concentration in water bodies. From the experiment data there is a tight exponential correlation between correlation between the RGB (-Ln(I/Io)) and the biomass concentration (mg/L) of y = 15.153e0.4813x with a Pearson's correlation coefficient R2=0.973. This breakthrough holds promise for revolutionizing environmental monitoring practices, enabling more efficient and widespread assessment of aquatic ecosystems and contributing to the preservation of water resources. Keywords: Algae concentration, RGB light absorption, Environmental monitoring