2019
DOI: 10.1016/j.microc.2019.104072
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A smartphone-based colorimetry after dispersive liquid–liquid microextraction for rapid quantification of calcium in water and food samples

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Cited by 42 publications
(13 citation statements)
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“…This leads to a fast semi-quantitative result. Individual differences in color recognition can be avoided using smartphone apps measuring the R, G and B value of the colored test solutions (Peng et al 2019) or of commercially available field test kits for selected soil contaminants like As (Haque et al 2016). Furthermore, there is no problem with the disposal of the chemicals, since everything is kept in the closed tubes.…”
Section: Field Applicationmentioning
confidence: 99%
“…This leads to a fast semi-quantitative result. Individual differences in color recognition can be avoided using smartphone apps measuring the R, G and B value of the colored test solutions (Peng et al 2019) or of commercially available field test kits for selected soil contaminants like As (Haque et al 2016). Furthermore, there is no problem with the disposal of the chemicals, since everything is kept in the closed tubes.…”
Section: Field Applicationmentioning
confidence: 99%
“…The colored image mainly consists of three color channels, i. e., RGB (Red, Blue and green), depending on the color change and intensity. [39,42] The calibration plot for any colorimetric change can be obtained using these unit pixel values.…”
Section: Introductionmentioning
confidence: 99%
“…This indicator can be prepared and the analysis can be conducted at home without the need of any laboratory setup or personal expertise. The Android app Color Grab [39,43,44] from Loomat, which is free of cost, was used to pick RGB data from the photographed images. The H-paper indicator we prepared was successfully tested on real milk samples (Fresh milk, packaged milk, and samples prepared from powdered milk), stored in a domestic fridge and on milk kept at room temperature for different durations.…”
Section: Introductionmentioning
confidence: 99%
“…By evaluating the works that used smartphones for image acquisition and performed the external processing of the acquired data (Figure 1), we can see that these devices are explored in several areas, such as the detection of diseases and markers of diseases causing in the medical field, immunoassay, 18–27 quality control of the environment, 28–39 forensic analysis, 40–42 control and quality of beverages and food, 15,43–64 quality evaluation of pharmaceutical products, 54,65,66 fuel quality control, 67,68 pigments, 69 chemical education, kinetic studies, and chemical receptors 70–77 …”
Section: Introductionmentioning
confidence: 99%