Machine learning-assisted paper-based chemiluminescence biosensor for choline quantification in infant milk: toward portable nutritional quality monitoring.

) which is generated through the use of choline oxidase (ChOx), and then the produce a luminol-cobalt chemiluminescent reaction, where the intensity of the emitted light is directly proportional to the concentration of choline. ML models quantify light intensity, and are highly accurate without the need to use standard methods of calibration. This device has a linear dynamic range of 0.5-10 mM and a detection limit of 257.12 µM, thus it is useful in quantification in real time and can also be used in the real field envirnoment. This point-of-care testing (PoCT) biosensing tool, enriched with an ML algorithm, therefore, increases nutritional surveillance functions, especially in resource-limited environments, and contributes to adherence to the infant food safety protocols..