Investigation into the predictive performance of colorimetric sensor strips using RGB, CMYK, HSV, and CIELAB coupled with various data preprocessing methods: a case study on an analysis of water quality parameters

Abstract The potential use of colorimetric sensors has received significant attention due to its feasibility for in various applications. After reacting with a sample, the image sensor can be captured and converted into digital data using several different color models. analytical then processed chemometric methods. This research study investigated predictive performance calibration models established commonly used chemistry including RGB, CMYK, HSV CIELAB. A total eight commercially available were determine presence manganese (Mn 2+ ), copper (Cu iron (Fe /Fe 3+ nitrate (NO 3 – phosphate (PO 4 3– sulfate (SO 2– as well hardness pH values. As external validation tests, real water samples collected Chiang Mai, Thailand used. Based on resulting obtained synthetic test samples, that was most similar appearing chemical could offer satisfactory results. However, it not always case especially when strips composed multiple or array When tested validation, improved appropriate preprocessing and, this study, normalization method recommended guarantee accuracy