Colorimetric Determination of Ascorbic Acid Based on Its Interfering Effect in the Enzymatic Analysis of Glucose: An Approach Using Smartphone Image Analysis

Abstract

The use of digital image analysis as an analytical tool is a reality nowadays, and the use of smartphones stands out due to its high accessibility and practicality. Ascorbic acid (AA) is a natural and essential vitamin available as a supplement as a result of its use in preventing and treating several pathologies. This paper reports a simple, fast and low cost method using smartphone image analysis for quantification of AA based on its interfering effect in the enzymatic colorimetric detection of glucose. Commercial vitamin C tablets were used as prediction set for AA quantification, showing very satisfactory results (relative errors < 4%), where no statistical difference at a 95% confidence level was observed between the AA content estimated by the imaging method and the labeled reference values. As advantages, this method does not use expensive reagents neither laborious procedures to carry out the analysis.

Point-of-use detection of ascorbic acid using a spectrometric smartphone-based system

“…It should be noted that, as a result of the spectrometric capability of the device, our observed LOQ values of AA in this work are significantly lower than those obtained using colorimetric approaches using either a smartphone (LOQ 100 μg mL −1 ) (Hong & Chang 2014) or a desktop scanner (LOQ 276 μmol L −1 ) (MeloFerreira, et al 2015). Two studies demonstrate LOQ values either slightly better (via portable transmittance) (MeloFerreira, et al 2015) or better (via smartphone image analysis) (Coutinho, et al 2017), though we believe that in each case our demonstrated methodology provides significant improvements. In the former, the paperbased sensor is neither reusable nor stable for periods greater than three weeks, even when stored under refrigeration and in the darkness, resulting in significant challenges for practical point-of-use testing.…”

“…The LOD was found to be 5 μg mL −1 (27 μM), and the LOQ was 16 μg mL −1 (89 μM). To our knowledge, few analytical methods for AA quantification using portable optical systems have been published, and none of them are capable of providing spectrallyresolved analysis (Table S3 in supplementary data ) (Coutinho, et al 2017;Hong & Chang 2014;MeloFerreira, et al 2015). It should be noted that, as a result of the spectrometric capability of the device, our observed LOQ values of AA in this work are significantly lower than those obtained using colorimetric approaches using either a smartphone (LOQ 100 μg mL −1 ) (Hong & Chang 2014) or a desktop scanner (LOQ 276 μmol L −1 ) (MeloFerreira, et al 2015).…”

“…Though there has been much progress developing point-of-care devices, the use of a spectrometric smartphone-based system for AA quantification has not been previously reported. There are only a few examples of portable optical systems for AA quantification that have been demonstrated (Coutinho et al 2017;Hong & Chang 2014;MeloFerreira et al 2015), but they are all colorimetric in nature, and frequently have significant challenges in differentiating between AA and commonly interfering substances present in commercial products expected to contain AA, such as orange juice (Table S3).…”

PhotoMetrix and colorimetric image analysis using smartphones

“…From 2011, the use of these devices begins to be more explored, and the first applications for image processing on the phone itself were reported. [14][15][16][17] 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][19][20][21][22][23][24][25][26][27] quality control of the environment, [28][29][30][31][32][33][34][35][36][37][38][39] forensic analysis, [40][41][42] control and quality of beverages and food, 15, quality evaluation of pharmaceutical products, 54,65,66 fuel quality control, 67,68 pigments, 69 chemical education, kinetic studies, and chemical receptors. [70][71][72][73][74][75][76][77] In ...…”

“…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 …”