Development of a microfluidic paper-based analytical device (μPAD) for detection of urea, nitrite, and starch adulteration in milk with smartphone app assisted detection

Milk is a vital part of a balanced diet that supports growth and overall health. However, widespread adulteration has raised serious concerns about its safety and quality. This study focuses to develop a microfluidic paper-based analytical device (μPAD) for the simultaneous detection of urea, nitrite, and starch adulteration in milk. Additionally, the current work aims to develop a smartphone app for automated interpretation of the colorimetric responses. The μPAD was fabricated using direct chemical patterning method. The microfluidic design was printed on a transparent film and used as the positive mask. Hydrophobic patterning was achieved by uniformly spraying the FluoroPel 800 solution onto Whatman grade 4 filter paper using a portable airbrush system operated at a constant spray rate of 0.15 mL/s and a height of 5 mm. After drying, the device was loaded with specific reagents for nitrite, urea, and starch adulteration detection in milk sample. A smartphone app was developed using the Thunkable workspace and integrated with Imagga as the application programming interface (API) platform. The coated paper showed a high contact angle of approximately 119 ± 3°, which confirmed the successful modification of the substrate from hydrophilic to hydrophobic. The result indicated that the liquid was completely confined within the hydrophilic region, with no evidence of spreading or leakage beyond the coated boundaries. The color response analysis showed that the urea detection zone changed from pale yellow at lower concentrations to orange-yellow, while the nitrite detection zone transitioned from light purple to deep reddish-purple as the adulteration levels increased from 0.5 to 3 g/L. On the other hand, the starch detection zone shifted its output color from brown at the initial to dark blue at 20 g/L. The smartphone app demonstrated a high ability to detect adulteration levels of urea and nitrite from 0.5 to 3.0 g/L and starch from 5.0 to 20.0 g/L. The strong correlation between the level of adulterants and observed color changes established the sensitivity and reliability of the μPAD. The platform offers a cost-effective and rapid tool for on-site milk adulteration screening, particularly in resource-limited settings where laboratory testing is impractical.