Innovative prediction of milk microbiological quality from pH measurements by digital imaging photometry

A novel colorimetric assay was proposed to predict microbiological contamination of milk from pH measure-ments. It was based on the adsorption of the acid-base indicator phenol red to milk proteins, with the color of the suspension monitored by smartphone-based photometry through the RGB color system. Sample throughput of 30 measurements h-1, relative standard deviation of 2.0 % (n = 20), cost-effectiveness, low waste generation (570 mu L per determination), and a broad analytical range (5.4 <= pH <= 7.2) were achieved. The procedure was applied for pH determination in raw and processed milk samples and the results agreed with near-infrared spectroscopy and potentiometric reference procedures at the 95 % confidence level. Relative errors were lower than 2.0 % with recoveries from 97 % to 106 %. A screening approach based on the analytical responses at G and B channels yielded the correct classification of samples masked with ammonium chloride, sodium hy-droxide, urea, or formaldehyde, as well as acid and diluted milk, even when the pH of non-conforming samples was adjusted to the expected values (pH from 6.60 to 6.80). This advantage in relation to potentiometric pH measurements demonstrates the potentiality of the proposed approach for evaluation of microbiological contamination of milk.

Automated summary

A novel colorimetric assay was proposed to predict microbiological contamination of milk using a smartphone-based photometry system. The method achieved high sample throughput, low error, low cost, and a broad analytical range. The results showed that the method accurately determined the pH of milk samples and evaluated their microbiological contamination.