Evaluation of Turbidity Effect on Manganese Detection Based on Spectroscopy Approach

• Published in: 14th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2024 - Proceedings
• Main Author: Zain N.S.N.M.; Rahman M.F.A.; Robi F.I.M.; Ahmad K.A.; Yahaya S.Z.; Boudville R.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207045909&doi=10.1109%2fICCSCE61582.2024.10696504&partnerID=40&md5=4ccf970e581dabfe0ad0da6116e25377

The presence of heavy metals such as manganese ions in water poses significant health risks to consumers, especially humans. Therefore, it is crucial to monitor the levels of manganese in the water. Currently, detection is based on optical sensing techniques such as spectrometers. In this process, turbidity always causes issues and affects the accuracy of optical measurements during in-situ experiments. Therefore, the ability to evaluate the effect of turbidity on manganese detection is significant in improving the accuracy of measurement, which become the objective of this work. In this work, 70 samples data were analysed using statistical analysis techniques such as normality test, correlation and regression analysis. For the normality test, a histogram and a Q-Q plot were used. Meanwhile, for the correlation, the Pearson correlation method was used to determine the strength of relationship between the deviation of absorbance measurement of manganese, Δ A b s for different concentration of turbidity, T. Finally, linear regression analysis was performed to obtain the regression equation of these variables. It is found that the resulting regression equation is Δ A b s=0.004 T-0.03. This equation can be used to predict the amount of absorbance deviation under the influence of turbidity so that proper action can be taken to compensate the deviation and improve the accuracy of measurement. © 2024 IEEE.