Smartphone digital image colorimetry couple with chemometric approach for determination of boron in nuts prior to deep eutectic solvent liquid-liquid microextraction: a first application of hybrid chemometrics in SDIC.

In this research, a green approach utilizing deep eutectic solvent liquid-liquid microextraction is combined with smartphone digital image colorimetry for the determination of boron in nut samples. A smartphone camera was used to capture the image of the analyte extract located in a custom-made colorimetric box. Using ImageJ software, the images were split into RGB channels, with the green channel identified as the optimum. The distance between the cuvette containing the analyte extract and the detection camera was determined to be 8 cm, while the brightness of the light source was 30%. All the images were obtained at 585 nm monochromatic light positioned as a background source. The extraction was achieved with 450 µL of a 1:4 choline-chloride to phenol mole ratio within 60 s and another minute of centrifugation. The limits of detection and quantification were found to be 0.02 and 0.06 µg mL, respectively. The method linearity, as indicated by the relative coefficient, was greater than 0.9955 and the relative standard deviations were below 5.4%. Lastly, the application of chemometrics in the form of artificial intelligence (AI)-based models and hybrid machine learning methodologies has been incorporated with SDIC for the quantitative simulation of SDIC parameters. The results gathered showed that these models are capable of predicting the quantitative SDIC parameters.