Smartphones have become widely adopted as tools for enhancing the sensitivity and usability of microfluidic paper-based analytical devices ( \(\mu PADs\) ) through high-resolution imaging, real-time data processing and reduced reagent consumption. However, their performance is often affected by many factors such as device parameters and lighting conditions. Addressing these may add cost and complexity, undermining on-site simplicity and affordability. The current work focuses on identifying optimal colour spaces for reducing these effects and improve accuracy of the estimated results. Bromocresol Green method and Biuret method were used for Albumin and Total protein respectively. These tests were optimized for paper microfluidics and images were captured and analyzed using a smartphone. Coefficient of determination ( \(\hbox {R}^{2}\) ) analysis revealed that \(\Delta E_{00}\) in CIELAB space best correlated with analyte concentration ( \(\hbox {R}^{2}\) = 0.9785 for total protein, 0.9179 for albumin). Limit of detection (LOD) of \(0.236\text { g/dl}\) and \(0.31\text { g/dl}\) for total protein and albumin respectively were achieved using the \(\Delta E_{00}\) . Hence, \(\Delta E_{00}\) and CIELAB are recommended as the optimal colour space for smartphone readouts of these biochemical assays on microfluidic paper-based analytical devices.
