ISSN 1061-9348, Journal of Analytical Chemistry, 2017, Vol. 72, No. 11, pp. 1127–1137. © Pleiades Publishing, Ltd., 2017. Original Russian Text © V.V. Apyari, M.V. Gorbunova, A.I. Isachenko, S.G. Dmitrienko, Yu.A. Zolotov, 2017, published in Zhurnal Analiticheskoi Khimii, 2017, Vol. 72, No. 11, pp. 963–977.

REVIEWS

Use of Household Color-Recording Devices in Quantitative Chemical Analysis V. V. Apyari*, M. V. Gorbunova, A. I. Isachenko, S. G. Dmitrienko, and Yu. A. Zolotov Department of Chemistry, Lomonosov Moscow State University, Moscow, 119992 Russia *e-mail: [email protected] Received March 13, 2017; in final form, May 4, 2017

Abstract⎯Published data on the use of household color-recording devices, such as office scanners, digital cameras, web cameras, mobile phones, and smartphones, in quantitative chemical analysis are generalized and systematized. The main approaches underlying the use of these devices for recording optical analytical signals are discussed. Methodological approaches used in the measurements and processing of the results are described. Examples of the determination of chemical compounds and ions using household color-recording devices are given. Keywords: household color-recording devices, digital colorimetry, computer scanner technologies, digital camera, mobile phone DOI: 10.1134/S106193481711003X

One of the trends in modern analytical chemistry is the creation of easy-to-use and universally accessible means of chemical analysis. Important methods stimulating the development of this trend are spectrophotometry, colorimetry, and visual colorimetry. With the proliferation of digital photography, desktop scanners, and other household devices capable of recording an image of an object and its color characteristics, a fast, objective, and automated way of assessing the colorimetric characteristics of the colored samples appeared. Gradually, studies in this area have grouped into a separate, intensively developing direction. Since the early 2000s, there has been a rapid increase in the number of scientific publications devoted to the use of scanners for the purposes of chemical analysis; since 2005, a rapid increase in the proportion of works where a digital camera or a web camera is used as a recording device has been rapidly grown. In 2007, the use of cellular phones and smartphones for this purpose was first mentioned; currently such works occupy a leading position in the number of publications (Fig. 1) [1]. In Russia, the efficiency of digital colorimetry was demonstrated in the interpretation of thin-layer chromatograms [2, 3] and in the determination of compounds forming a colored analytical form using an office scanner [4–7] as an analytical device and a video camera (in combination with a specially designed system for lighting samples) [8]. Subsequently, a digital camera was also used for analytical purposes [4, 9].

In this review, information on the use of household color-recording devices in quantitative chemical analysis for the determination of chemical compounds and ions, published primarily over the past decade, has been systematized. GENERAL INFORMATION ON COLORIMETRY According to the basic law of color theory [10–13], any color can be represented as a sum of three linearly independent components. Depending on the selection of basic components, different colorimetric systems are distinguished, for example, RGB, CMY(K), XYZ, Lab, HSB, and others. Modern digital devices mostly use red (R), green (G) and blue (B), as the primary colors, which correspond to three monochromatic radiations with wavelengths of 700.0, 546.1 and 435.8 nm, respectively [14]. The color of a certain shade and intensity can be obtained by varying the relative amounts (intensity, brightness) of these three components. In this case, the representation of a color in the RGB color system is considered. Mathematically, this can be expressed by equation A(RGB) = rR + gG + bB, where A(RGB) is the final color obtained by mixing red, green, and blue radiations; R, G, and B are the corresponding primary colors; and r, g, and b are their intensities [11]. Other colorimetric systems are associated with the RGB colorimetric system and with each other by

1127

APYARI et al.

120

Number of publications

100

600 500

Mobile phones and smartphones Digital cameras

80

400

Web cameras 60

300 Scanners

40

200

20

100

0

Total number of publications

1128

0 1961 1985 1989 1993 1997 2001 2005 2009 2013 1983 1987 1991 1995 1999 2003 2007 2011 2015 Year

Fig. 1. Number of publications devoted to the use of digital imaging devices in chemical analysis from 1960 to 2015 (N = 587). Histogram shows the distribution by years and by devices (scanners, web cameras, digital cameras, and mobile phones and smartphones). Point markers indicate the total number of publications [1].

coordinate transformation. For example, the transition from the basic colors to conditional XYZ colors can be carried out using matrix equation [11]:

⎡ X ⎤ ⎡0.49000 0.31000 0.20000⎤ ⎡R ⎤ ⎢ Y ⎥ = ⎢0.17697 0.81240 0.01063⎥ × ⎢G ⎥ . ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢⎣ Z ⎥⎦ ⎢⎣0.00000 0.01000 0.99000⎥⎦ ⎢⎣ B ⎥⎦ The Lab coordinates are in turn related to the XYZ coordinates as follows:

⎛ ⎞ L = 116 f ⎜ Y ⎟ − 16, ⎝Y 0 ⎠ ⎡ ⎛ ⎞ ⎛ ⎞⎤ a = 500 ⎢ f ⎜ X ⎟ − f ⎜ Y ⎟⎥ , X ⎣ ⎝ 0⎠ ⎝Y 0 ⎠⎦ ⎡ ⎛ ⎞ ⎛ ⎞⎤ b = 200 ⎢ f ⎜ Y ⎟ − f ⎜ Z ⎟⎥ ⎣ ⎝Y 0 ⎠ ⎝ Z 0 ⎠⎦ 1/3 ⎧t , t > 216 24389 ⎪ where f (t ) = ⎨24389 27 t + 16 . t , 216 24389 ≤ ⎪⎩ 116 In contemporary programs for working with images (graphics editors), enabling various operations of color decomposition into components, information about the color of a pixel can be represented in the form of numbers, for example, from the range of 0– 255, characterizing the contribution of a primary color—R, G, or B—into the resulting color. Sometimes in this case, the brightness of a particular color channel is meant.

Number 0 corresponds to the zero brightness of a given color channel, and number 255 is for its maximum. Then the combination (0, 0, 0) corresponds to the black color; the combination (255, 255, 255) is for the white color of the maximum brightness in the given coordinate system; the combination of the same numbers in the range of 0–255 yields the gray color of an intermediate brightness; and the combination of different values gives shades of a particular color. From the point of view of analytical chemistry, it is important that the color coordinates are functionally related to the spectrum of radiation diffusely reflected from the object under study. For example, in the case of the XYZ colorimetric system, this relationship can be expressed as follows [11]: λ=730 nm

X =k

∑

[Φ(λ)x (λ)] Δλ,

λ=380 nm λ=730 nm

Y =k

∑

[Φ(λ)y (λ)] Δλ,

λ=380 nm λ=730 nm

Z =k

∑

[Φ(λ)z (λ)] Δλ.

λ=380 nm

Here, Φ(λ) is the flux of radiation reflected from the sample, which is the product of the diffuse reflection coefficient by the relative spectral distribution of the illuminator energy: Φ(λ) = R(λ)S(λ); x ( λ), y ( λ), z (λ) are the values of the functions of the so-called “addition curves” that determine the contri-

JOURNAL OF ANALYTICAL CHEMISTRY

Vol. 72

No. 11

2017

USE OF HOUSEHOLD COLOR-RECORDING DEVICES

bution of radiation of a particular wavelength to a given color coordinate; Δλ is the detection step (usually, 10 nm); and k is the normalization factor determined by recording the radiation scattered by a white reference sample during the calibration of the recording equipment. Since the spectral characteristics and color of the sample change during the analytical reaction, a corresponding change in the coordinates of the color of its digital image is observed. The dependence of the brightness of one or several color channels, averaged over all the pixels of the image region under study of the object, on the concentration of the colored matter can be considered as a calibration dependence and used subsequently to find the concentration of the analyte in the test sample [4–7]. PECULIARITIES OF USING HOUSEHOLD COLOR-RECORDING DEVICES IN CHEMICAL ANALYSIS The principles of using digital colorimetric devices in analytical chemistry have been developed in a large number of works [1, 15–52], including in Russia [15– 25]. Examples of such works are systematized in Tables 1–3. Procedures for analysis by digital colorimetry are rather diverse, but in general, they include the following main stages: (1) Instrumental recording of the color characteristics of the reflected, absorbed, or emitted radiation by a digital analytical system. It includes a digital recording device, a sample lighting system (built-in, as in the case of a scanner and digital camera when shooting with flash, or external, as in the case of a web camera and mobile phone). (2) Processing of digital images using a specific algorithm that is a part of commercially available graphic editors, or developed specifically for this task and this recording device. During mathematical processing of a digital image, it is usually necessary to select the analysis area (for example, an immobilized colored analytical reaction product or a colored solution). This area can be selected manually or using program means enabling one to distinguish it from the background. Further, based on the obtained information on the color of the analysis area, an analytical parameter related to the spectral characteristics and concentration of the analyte is calculated. Based on the value of the analytical parameter, qualitative or quantitative information on the composition of the sample is obtained using the calibration curve, pattern recognition, or multiple regression analysis. Among the analytical effects used in combination with digital colorimetric technologies, absorption and reflection of radiation, fluorescence, phosphorescence, chemiluminescence, electrochemiluminesJOURNAL OF ANALYTICAL CHEMISTRY

Vol. 72

1129

cence, and emission can be mentioned. Examples of the use of these effects are summarized in several reviews [1, 26, 27, 102, 103]. Each of the types of household color-recording devices is characterized by its features that determine its capabilities and prospects for use in chemical analysis. For example, scanners are ideally suited for laboratory measurements, since it is easy to standardize the lighting conditions of samples without significant external radiation, but they require constant connection with the personal computer for both control and transmission and analysis of the obtained digital information. Digital cameras and web cameras are much more compact and mobile devices, which makes their use in the field more promising; however, the problem may arise of the effect of external radiation on measurement results. In addition, these devices, as well as scanners, need a connection with a computer for management (web camera) and analysis (web camera and digital camera) of information. Regarding the latter problem, mobile phones and smartphones are universal devices, especially actively offered for analytical chemistry in the last 5 years; they are completely autonomous both in terms of management and in terms of storing and analyzing the obtained digital information. With the help of specially developed programs, they can immediately give out the result in the form of the concentration of the compound being determined. It should be noted, however, that at this stage of development, built-in cameras of mobile phones and smartphones still lose out to digital cameras in resolution and sensitivity, which makes difficult the producing of a high-quality image. In the case of these cameras, it is often impossible to vary the shooting parameters, the tuning of which can significantly improve the analytical characteristics of the procedure. We should separately mention minispectrophotometers, namely, monitor calibrators, which, apparently, are just beginning to find their application in analytical chemistry [104–110]. Their important advantage is the capability of recording not only the three color coordinates but also the complete spectrum of diffuse reflection in the visible wavelength range, which makes analysis much more informative. At the same time, in comparison with professional laboratory diffuse reflection spectrometers and spectrophotometers, these devices stand out with their compactness and low cost. Signals of analytical forms are measured with the help of household color-recording devices both directly [4, 6, 19, 105] and using specially designed holders, boxes, and cuvettes, which are intended to decrease measurement errors by fixing the distance to the measured object and its lighting conditions [15, 17, 92, 111–113]. The use of such devices increases the accuracy and sensitivity of the determination, but complicates the design of the analytical setup as a

No. 11

2017

1130

APYARI et al.

Table 1. Examples of determination of chemical compounds and ions using scanner Colorimetric Analytical cmin Analyte Analytical range system parameter Dissovled CO2, dissolved NH3 Halides

R, G, B

CMYK

d2K/dV 2 Е G

RGB RGB

Cu(II) Cu(II), Fe(III), Ni(II) Ni(II), Pb(II)

RGB RGB RGB

Hg(II) K(I)

Reference

–

[28]

Inorganic compounds and ions 17–1700 ppm, 17 ppm, 14.7–147 ppm 14.7 ppm

RGB

Anions (10) Cl2

Sample

–

–

–

[29]

– 0.05–0.7 mg/L

0.36–880 μM 0.004 mg/L

Water –

[30] [18]

0.16–1.6 μM 1.5–10, 1–17, and 1–15 μg <2.5 μM, <10 μM

HSL HSV

Е GS after inversion of colors Ratios ΔR, ΔG, and ΔB Normalized H H

Na(I), K(I)

HSV

H

Mn(II)

RGB

АG

10–4–10–1 M 1–70 μg/L

0.1–0.6 μg 4.5 × –1.0 × 10–1 М 10–6

10–6–10–4

Mn(II), Zn(II), Ni(II) Cations (9) Cations

RGB

R, B

RGB HSV

R, G, B H

Cations (7), anions (5), and organic compounds

Lab

L

NH 4+ , PO34− ,

RGB

AR, AR, AR, AG

RGB RGB CMYK RGB

G, B, L R, G, B M А

M

0.01–10 mM 10–3–10–7

M 0.01–500 mg/L

0.16 μM – 1.5, 1, and 1 μg Metal particles in aerosol 94 nM, 3 μM Water 70 ng

[31] [32] [33]

Fish Water

[34] [35]

–

Water

[36], [37]

0.314 μg/L

Wire, water

[38]

0.06–2.2 μg/mL

–

[19]

– –

– Water

[39] [40]

–

Water

[21]

–

Water

[41]

0.001 mg/L – 0.5 μM 1 μM, 19 μM

Water Urine Saliva –

[5] [15] [42] [43]

4.5 ×

10–6

N2H4

RGB

AR, AG, AB

1–20, 0.1–1, 1–20 and 0.05–0.25 mg/L 0.003–3.5 mg/L 0–5 mg/L 5–250 μM 10–150 μM, 50–1000 μM 10–300 μg/L

0.1 μg/L

Water

[44]

H2O2

RGB

ΔR

14–1000 μM

14 μM

[45]

H2S

RGB

ΔR, ΔG, ΔB

0.05–50 ppm

50 ppb

Lens cleaning solution –

[46]

Amines Amino acids

RGB RGB, Lab

R/(R+G+B) R+G+B; R, G, B; L, a, b

– –

– Water

[47] [15]

Anthocyanin pigments

RGB

R, G, B

1–45 g/L

–

Water, water– ethanol solutions

[15]

Povidone-I2

RGB

А

0–10%

–

Pharmaceutical preparations

[48]

–

–

–

0.04 pmol

–

[49]

NO3− , Br– NO 2−

NO 2− , NO3−

DNA

Organic compounds 10–100 ppm 0–20, 0–16, and 0–20 g/L

JOURNAL OF ANALYTICAL CHEMISTRY

Vol. 72

No. 11

2017

USE OF HOUSEHOLD COLOR-RECORDING DEVICES

1131

Table 1. (Contd.) Colorimetric system

Analytical parameter

Glucose

RGB

Glucose, BSA

RGB

B CI CI CI

Analyte

Analytical range

cmin

Sample

Reference

0.5 mM 0.5 g/L 0.1 g/L 2.5 μM, –

Blood serum Blood – Artificial urine

[50] [51] [52] [53]

Urine, saliva

[42]

Blood Bovine blood serum

[54] [55]

[56]

RGB, CMYK RGB RGB

GS, M G Е

0.5–100 mM 0.5–2 g/L 0.1–10 g/L 0.5–10 mM, <0.75 μM 3–50 mM, 5–16 mM 25–250 g/L 10–200 μM

RGB

АR, АG

2–20 mg/L

2.8 mM, 0.5 mM 10 g/L 1.3 μM, 1.6 μM, 5.9 μM 0.5 mg/L

Fast Green FCF

RGB

АR

0.03–1 mg/L

0.022 mg/L

Bovine blood serum –

Protein Protein, glucose

RGB Lab

G A, b

– –

Rice Urine

[58] [59]

Acid Red 151 Ascorbic acid

RGB RGB

ΔR, ΔG, ΔB AG, AB

50–130 mg/g 0.46–46 μM, 2.8–28 mM 0.5–19 mg/L 2–20 mg/L

0.32 mg/L 1 mg/L

[60] [61]

Volatile organic compounds N-Methylaniline 1-Naphthylamine

RGB

Е

–

0.1–16 ppm

Water Pharmaceutical preparations –

[62]

RGB RGB

R R, G, B, L

0.014–0.35 vol % 0.02–2.8 mg/L

0.006 vol % 0.01 mg/L

Gasoline –

[20] [63]

Glucose, ketones Hemoglobin Cysteine, homocysteine, glutathione Dopamine

[57]

AR(G, B) is the effective absorbance of a particular color channel; CI is the color intensity; E is the Euclidean distance in the selected color space; and GS is the gray scale intensity.

whole and makes it less mobile. Examples of the proposed designs and circuits for recording a digital signal are shown in Figs. 2 and 3. In addition to object lightning, the characteristics of the equipment used and the settings of its parameters play an important role in recording its image. The important characteristics include the color depth (that is, the number of bits used to represent the color of the pixel, typically 24 or 48 bits, which corresponds to 8 and 16 bits per color channel), resolution (the number of pixels per inch, dpi), and dynamic range (the ability to distinguish shades of light and dark) [1]. As for the settings of the parameters of digital equipment, a digital camera can change them to the largest degree. The effect of the parameters of photography on the sensitivity of the determination with the use of a digital camera was studied in our work [4]. It is shown that for each color scale, there are optimal settings of the camera system, ensuring, other things being equal, the achievement of the maximum sensitivity coefficient. After selecting the conditions of recording and measurement, the analysis of the resulting image JOURNAL OF ANALYTICAL CHEMISTRY

Vol. 72

becomes necessary. At the moment, it is successfully solved by means of modern programs for processing digitized images, for example, Adobe Photoshop, MatLab, ImageJ, GIMP, etc. When analyzing the image and interpreting the received colorimetric information, it is necessary to select the analytical parameter, in over words, the value associated with the concentration of the analyte or the composition of the test object. As such a parameter, both the value of this or that color coordinate in the selected color coordinate system, for example R, G, or B, averaged over the analyzed area of the image, and the value calculated from these values can act. Tables 1–3 shows the proposed options for presenting an analytic parameter. Let us consider some examples in more detail. An effective absorbance value, also called “effective intensity,” is often suggested to use in the role of an analytic parameter. This value is calculated similarly to absorbance in spectrophotometry as

No. 11

AR = − log(R s R b ), AG = − log(G s G b ), AB = − log(B s B b ), 2017

1132

APYARI et al.

Table 2. Examples of determination of chemical compounds and ions using digital camera or web camera Colorimetric Analytical сmin Analyte Analytical range Sample system parameter Li(I), Na(I), Ca(II) Ca(II)

MnO 4−

RGB RGB RGB

Inorganic compounds and ions 6–30, 1.8–9, 0.9, 0.4, and 10–50 mg/L and 1.0 mg/L R, G, B, R+G+B 0.2–2 mg/L 0.07 mg/L GS 0.01–4.4 mM – Е

Reference

Pharmaceuticals, water Water –

[64] [65] [66]

Fe(III), Cl2

Lab

Δb

<2 mg/L, <1 mg/L

0.2 mg/L, –

Water

[67]

H2O2

RGB

R/(R+G+B)

10–80 μM

6.2 μM

–

[68]

Cations (8) Cations (13)

RGB HSV

Е H

0.5–50 μM

0.5 μM –

Water Water

[69] [70]

Ni

RGB

GS

–

Meteoritic particles –

[71]

10–3–10–7

M 2–18 mg/L

O2 gas

RGB

G/R

0–100%

–

O2 dissolved

RGB

R/B, G/B (R–G)/G

0–760 mm Hg 0–100%

– –

S2– Ti(IV)

HSV

H

0.1–145 μM

RGB

Amino acids Amphetamine, methylamphetamine Aromatic amino and hydroxy compounds Glucose Chlorophyll

RGB RGB

Polyphenols, anthocyanins Tannins Trinitrotoluene Thrombin

R, G, B, R+G+B 2–30 mg/L Organic compounds GS 10–90 μg/mL 0.1–1 mg/L, R, G, B, AR, AG, AB 0.25–1 mg/L

RGB

R, G, B

RGB RGB

CI G/B; (R+G)/B; GS

RGB

–

RGB RGB RGB

E A G

0.1 μM

[75]

0.6 mg/L

Plastics

[76]

– 0.14 mg/L, 0.15 mg/L

Tea –

[77] [78]

–

[4]

– –

Blood serum Leaves

[79] [80]

–

Red wine

[81]

2.7 mg/L 1.8 mg/L –

Green tea Soil Blood plasma

[82] [83] [84]

0.01–10 μg/mL 0.004–0.06 μg/mL

0–6 mM 2

10–60 μg/cm 0.5–3 g/L, 0.1–0.3 g/L 2.7–100 mg/L 2–50 mg/L 69–108 μM

[72]

– Water, precipitations Water

[73] [74]

AR(G, B) is the effective absorbance of a particular color channel; CR is the color ratio; E is the Euclidean distance in the selected color space; and GS is the gray scale intensity.

where AR, AG, and AB are effective absorbance along the red, green, and blue color channel; Rs, Gs, and Bs are the corresponding color coordinates of the test sample; and Rb, Gb, and Bb are the color coordinates of the sample in the control experiment [1]. The total absorbance AT = AR + AG + AB or the color ratio

CR =

R s R r + G s G r +Bs Br . 3

are also used. Here, index r refers to a reference sample. In some cases, the intensity value along the gray scale is selected as the analytical parameter. In this case, the image can be converted from color to blackand-white using various algorithms, for example, a lightness algorithm [max(R, G, B) + min(R, G, B)]/2, an averaging algorithm (R + G + B)/3, or a brightness algorithm 0.3R + 0.59G + 0.11B. In the case of the gray scale, the calculation of the optical

JOURNAL OF ANALYTICAL CHEMISTRY

Vol. 72

No. 11

2017

USE OF HOUSEHOLD COLOR-RECORDING DEVICES

1133

Table 3. Examples of determination of chemical compounds and ions using mobile phones and smartphones Colorimetric Analytical сmin Analyte Analytical range Sample Reference system parameter Cl2

RGB

Hg(II)

RGB

K(I)

HSV

Inorganic compounds and ions CR 0.3–1 mg/L Normalized G/R 0–5 μM R, G, B 2 × 10–9–10–3 M H 3.1 × 10–5–

–

Water

[85]

3.5 μg/L

Waters Water

[86] [87]

Water

[88]

–9

2 × 10 3.1 ×

М

10–5

М

–1

RGB HSV

E 1/S

10 М 20–160 mg/L 0.52–100 mg/L

O2 gas

RGB

R/R0

0–100%

Allergens Explosives (5) Vitamin D Cortisol Food colorants Cholesterol 2-(Dibutylamino)ethanol, L-proline β-D-Galactosidase Glucose Neuropeptide Y

RGB RGB HSB HSV RGB HSV RGB

A E ΔH V GS S R

RGB RGB RGB

Median G R, G, B E

Na(I)

NO 2−

6 mg/L 0.52 mg/L

Waters –

[89] [90]

0.75%

–

[91]

Food products – Blood Saliva Beverages Blood –

[92] [93] [94] [95] [96] [97] [98]

– Blood serum Saliva

[99] [100] [101]

Organic compounds 1–25 mg/L <1 mg/L >0.2 μg 0.2 μg–0.1 mg 0–110 nM – 0.01–10 ng/mL 0.01 ng/mL 2–10 mg/L – 1.4–4 g/L – 0.1–5 mM, 0.1 mM, 0.1 mM 0.1–10 mM 0.7–12 nM 0.7–20 mM 0.01–10 μM

0.7 nM 0.7 mM 0.01 μM

AR(G, B) is the effective absorbance of a particular color channel; CR is the color ratio; E is the Euclidean distance in the selected color space; and GS is the gray scale intensity.

darkening ratio (ODR) is a rather common procedure for accounting for the signal of a blank experiment:

Ib − Is , Ib where Ib and Is are the gray scale intensities for the blank and test samples, respectively [1]. It is noted in publications that, generally, the dependence of individual color coordinates on the concentration of the compound being determined is nonlinear [4, 15]. One of the possible solutions to this problem is the allocation of ranges suitable for constructing linear calibration graphs. At the same time, the required calibration sensitivity factors and/or the broadness of the analytical range are achieved by selecting a suitable analytical parameter (see examples above) or a colorimetric coordinate system [15]. An alternative approach is a nonlinear approximation of the color coordinate on concentration. For example, it was demonstrated in [4–6] that in many −c t cases, the exponent of the form of y = y0 + Ae has a satisfactory characteristics as an approximating ODR =

JOURNAL OF ANALYTICAL CHEMISTRY

Vol. 72

function, where y0, A, and t are the parameters of the regression equation, describing the location and shape of the curve; y is this or that color coordinate varying in the range from 0 to 255; and c is the concentration of the component being determined. In [4], a mathematical analysis of this expression was carried out, and equations were proposed for calculating the limit of detection, the upper and lower boundaries of the analytical range under the conditions of nonlinear approximation. In particular, it was noted that the maximum ratio of parameters A/t is the criterion for selecting the optimum color coordinate and measurement conditions, and errors with other conditions being equal are minimal when determining the analyte concentrations close to parameter t. In addition, if ratio A/t and, consequently, the limit of detection are constant, the analytical range is wider, the larger A and t. The examples of comparison of the analytical characteristics obtained with the use of household colorrecording devices with the characteristics of spectrophotometric [15] and solid-phase spectroscopic methods [4, 5], available in publications, enable the

No. 11

2017

1134

APYARI et al.

(a)

(a)

3

4 5

1

4

3

5

2

6

1 (b)

1

6

2 3 (b)

5

5 4

3

2

4

1

6

2 Fig. 2. Proposed designs of measuring units and circuits for recording the digital colorimetric signal of the absorbance of solutions, using (a) a scanner [15] and (b) a digital camera [15]. (a): (1) Moving scanner sensor, (2) case, (3) slide adapter illuminator, (4) cuvette with test solution, (5) scanner glass, and (6) reversing mirrors. (b): (1) Replaceable diffuser screen, (2) radiation sources, (3) cuvette holder, (4) reversing mirror fixed at an angle to the plane of the cuvette holder, (5) observation window, and (6) cuvettes for test solution and reference solution.

conclusions that in general, household color recording devices are comparable in sensitivity and reproducibility with commercially available analytical equipment. CONCLUSIONS Thus, the analysis of literature data shows a prospective viability of using household color-recording devices in quantitative chemical analysis. Considerable theoretical data accumulated in this field, the developed system of working with such devices, and a wide range of problems solved with their use suggest a completely formed approach to chemical analysis. The possibilities and spheres of practical application of this method are constantly expanding due to replenishment of its instrument base with commercially available equipment. Important advantages of household color registration devices are the capability of operating with both liquid and solid analytical forms, low

Fig. 3. Scheme of digital recording of (a) a luminescence signal using a mobile phone [112] and (b) absorbance using a special facility installed on a smartphone [92]. (a): (1) Test tube with the sample being analyzed, (2) radiation source, (3) light filter and observation window, (4) mobile phone, and (5) a mobile phone strap. (b): (1) Radiation sources, (2) diffuser, (3) test tubes with test sample and reference solution, (4) additional lenses, (5) smartphone holder, and (6) smartphone.

cost, ease of use, and accessibility to a wide range of consumers. ACKNOWLEDGMENTS This work was supported by the Russian Science Foundation, project no. 14-23-00012. REFERENCES 1. Capitan-Vallvey, L.F., Lopez-Ruiz, N., MartinezOlmos, A., Erenas, M.M., and Palma, A.J., Anal. Chim. Acta, 2015, vol. 899, p. 23.

JOURNAL OF ANALYTICAL CHEMISTRY

Vol. 72

No. 11

2017

USE OF HOUSEHOLD COLOR-RECORDING DEVICES 2. Gerasimov, A.V., J. Anal. Chem., 2000, vol. 55, no. 9, p. 1161. 3. Nazarova, A.A., Korneva, T.A., Kovaleva, E.V., Rozhkov, P.N., Safonova, E.F., and Rudakov, O.B., Sorbtsionnye Khromatogr. Protsessy, 2003, vol. 3, no. 2, p. 213. 4. Apyari, V.V. and Dmitrienko, S.G., J. Anal. Chem., 2008, vol. 63, no. 4, p. 530. 5. Apyari, V.V., Dmitrienko, S.G., and Zolotov, Yu.A., Moscow Univ. Chem. Bull. (Engl. Transl.), 2011, vol. 66, no. 1, p. 32. 6. Shishkin, Yu.L., Dmitrienko, S.G., Medvedeva, O.M., Badakova, S.A., and Pyatkova, L.N., J. Anal. Chem., 2004, vol. 59, no. 2, p. 102. 7. Ivanov, V.M., Monogarova, O.V., and Oskolok, K.V., J. Anal. Chem., 2015, vol. 70, p. 1165. 8. Budantsev, A.Yu., J. Anal. Chem., 2004, vol. 59, no. 8, p. 703.) 9. Apyari, V.V, Andreeva, E.Yu., and Dmitrienko, S.G., Abstracts of Papers, VI Vseros. konferentsii po analizu ob”ektov okruzhayushchei sredy “Ekoanalitika-2006” (VI All-Russian Conf. on the Analysis of Environmental Objects “Ecoanalytics-2006”), Samara, 2006, p. 65. 10. Schicht, H.J., Digitale Bildverarbeitung mit dem PC, Bonn: Addison Wesley, 1993. 11. Domasev, M.V. and Gnatyuk, S.P., Tsvet, upravlenie tsvetom, tsvetovye raschety i izmereniya (Color, Color Management, Color Calculations and Measurements), St. Petersburg: Piter, 2009. 12. Jadd, D. and Wyszecki, G., Color in Business Science and Industry, New York: Wiley, 1975. 13. Kirillov, E.A., Tsvetovedenie (Color Science), Leningrad: Legprombytizdat, 1987. 14. Ivanov, V.M. and Kuznetsova, O.V., Russ. Chem. Rev., 2001, vol. 70, no. 5, p. 357. 15. Baidicheva, O.V., Cand. Sci. (Chem.) Dissertation, Voronezh: Voronezh State Univ., 2009. 16. Rudakova, L.V., Doctoral (Chem.) Dissertation, Voronezh: Voronezh State Univ., 2013. 17. Rudakova, L.V., Romanova, M.M., Khripushin, V.V., and Rudakov, O.B., Sist. Anal. Upravlenie Biomed. Sist., 2007, vol. 6, no. 4, p. 1015. 18. Gorbunova, M.O., Kononova, A.Yu., and Vtulkina, V.E., Voda: Khim. Ekol., 2014, no. 12, p. 83. 19. Egorov, V.M., Extended Abstracts of Cand. Sci. (Chem.) Dissertation, Moscow: Moscow State Univ., 2008. 20. Belyaeva, E.I., Zrelova, L.V., Marchenko, D.Yu., and Dedov, A.G., Pet. Chem., 2015, vol. 55, no. 1. 74. 21. Kumpanenko, I.V., Roshchin, A.V., Marchenko, D.Yu., Khalfin, T.M., Ostrovskaya, V.M., Bloshenko, A.V., and Usin, V.V., Russ. J. Phys. Chem. B, 2012, vol. 6, no. 5, p. 659. 22. Baidicheva, O.V., Rudakova, L.V., and Rudakov, O.B., Butlerov. Soobshch., 2008, vol. 13, no. 2, p. 50. 23. Rudakov, O.B., Rudakova, L.V., Kudukhova, I.G., Golovinskii, P.A., Khorokhordina, E.A., and Groshev, E.N., Analitika Kontrol’, 2012, vol. 16, no. 4, p. 368. 24. Kudukhova, I.G., Rudakova, L.V., Rudakov, O.B., and Nazarov, V.M., Voda: Khim. Ekol., 2011, no. 12, p. 89. JOURNAL OF ANALYTICAL CHEMISTRY

Vol. 72

1135

25. Lomova, T.S., Khripushin, V.V., Bolotov, V.M., Baidicheva, OV., and Rudakov, O.B., Pivo Napitki, 2008, no. 2, p. 42. 26. Grudpan, K., Kolev, S.D., Lapanantnopakhun, S., McKelvie, I.D., and Wongwilai, W., Talanta, 2015, vol. 136, p. 84. 27. Vashist, S.K., Mudanyali, O., Schneider, E.M., Zengerle, R., and Ozcan, A., Anal. BioAnal. Chem., 2014, vol. 406, p. 3263. 28. Chen, Y., Zilberman, Y., Mostafalu, P., and Sonkusale, S.R., Biosens. Bioelectron., 2015, vol. 67, p. 477. 29. Abbaspour, A. and Khajehzadeh, A., Anal. Methods, 2012, vol. 4, p. 923. 30. Feng, L., Li, H., Li, X., Chen, L., Shen, Z., and Guan, Y., Anal. Chim. Acta, 2012, vol. 743, p. 1. 31. Feng, L., Zhang, Y., Wen, L., Shen, Z., and Guan, Y., Talanta, 2011, vol. 84, p. 913. 32. Mentele, M.M., Cunningham, J., Koehler, K., Volckens, J., and Henry, C.S., Anal. Chem., 2012, vol. 84, p. 4474. 33. Feng, L., Zhang, Y., Wen, L.Y., Chen, L., Shen, Z., and Guan, Y.F., Analyst, 2011, vol. 136, p. 4197. 34. Paciornik, S., Yallouz, A.V., Campos, R.C., and Gannerman, D., J. Braz. Chem. Soc., 2006, vol. 17, p. 156. 35. Cantrell, K., Erenas, M.M., Orbe-Paya, I., and Capitan-Vallvey, L.F., Anal. Chem., 2010, vol. 82, p. 531. 36. Erenas, M.M., Pineiro, O., Pegalajar, M.C., Cuellar, M.P., de Orbe Paya, I., and Capitan-Vallvey, L.F., Anal. Chim. Acta, 2011, vol. 694, p. 128. 37. Erenas, M.M., Pegalajar, M.C., Cuellar, M.P., de Orbe Paya, I., and Capitan-Vallvey, L.F., Sens. Actuators, B, 2011, vol. 156, p. 976. 38. Shokrollahi, A. and Shokrollahi, N., Quim. Nova, 2014, vol. 37, p. 1589. 39. Palacios, M.A., Wang, Z., Montes, V.A., Zyryanov, G.V., Hausch, B.J., Jursikova, K., and Anzenbacher, J., Chem. Commun., 2007, vol. 36, p. 3708. 40. Ariza-Avidad, M., Cuellar, M.P., Salinas-Castillo, A., Pegalajar, M.C., Vukovic, J., and CapitanVallvey, L.F., Anal. Chim. Acta, 2013, vol. 783, p. 56. 41. Soldat, D.J., Barak, P., and Lepore, B.J., J. Chem. Educ., 2009, vol. 86, p. 617. 42. Klasner, S., Price, A., Hoeman, K., Wilson, R., Bell, K., and Culbertson, C., Anal. BioAnal. Chem., 2010, vol. 397, p. 1821. 43. Jayawardane, B.M., Wei, S., McKelvie, I.D., and Kolev, S.D., Anal. Chem., 2014, vol. 86, p. 7274. 44. Abbaspour, A., Mirahmadi, E., and Khajehzadeh, A., Anal. Methods, 2010, vol. 2, p. 349. 45. Maejima, K., Tomikawa, S., Suzuki, K., and Citterio, D., RSC Adv., 2013, vol. 3, p. 9258. 46. Sen, A., Albarella, J.D., Carey, J.R., Kim, P., and McNamara, W.B., Sens. Actuators, B, 2008, vol. 134, p. 234. 47. Davis, B.W., Burris, A.J., Niamnont, N., Hare, C.D., Chen, C.Y., Sukwattanasinitt, M., and Cheng, Q., Langmuir, 2014, vol. 30, p. 9616. 48. Kompany-Zareh, M. and Mirzaei, S., Anal. Chim. Acta, 2004, vol. 521, p. 231.

No. 11

2017

1136

APYARI et al.

49. Song, Y., Gyarmati, P., Araujo, A.C., Lundeberg, J., Brumer, H., and Stahl, P.L., Anal. Chem., 2014, vol. 86, p. 1575. 50. Ornatska, M., Sharpe, E., Andreescu, D., and Andreescu, S., Anal. Chem., 2011, vol. 83, p. 4273. 51. Yang, X., Forouzan, O., Brown, T.P., and Shevkoplyas, S.S., Lab Chip, 2012, vol. 12, p. 274. 52. Maattanen, A., Fors, D., Wang, S., Valtakari, D., Ihalainen, P., and Peltonen, J., Sens. Actuators, B, 2011, vol. 160, p. 1404. 53. Cassano, C. and Fan, Z.H., Microfluid. Nanofluid., 2013, vol. 15, p. 173. 54. Yang, X., Piety, N.Z., Vignes, S.M., Benton, M.S., Kanter, J., and Shevkoplyas, S.S., Clin. Chem., 2013, vol. 59, p. 1506. 55. Qian, S. and Lin, H., Anal. Bioanal. Chem., 2014, vol. 406, p. 1903. 56. Abbaspour, A., Valizadeh, H., and Khajehzadeh, A., Anal. Methods, 2011, vol. 3, p. 1405. 57. Shokrollahi, A. and Roozestan, T., Anal. Methods, 2013, vol. 5, p. 4824. 58. Sun, J.P., Hou, C.Y., Feng, J., and Wang, X., J. Food Qual., 2008, vol. 31, p. 250. 59. Abe, K., Suzuki, K., and Citterio, D., Anal. Chem., 2008, vol. 80, p. 6928. 60. Shokrollahi, A., Abbaspour, A., Azami Ardekani, Z., Malekhosseini, Z., and Alizadeh, A., Anal. Methods, 2012, vol. 4, p. 502. 61. Abbaspour, A., Khajehzadeh, A., and Noori, A., Anal. Sci., 2008, vol. 24, p. 721. 62. Lin, H., Jang, M., and Suslick, K.S., J. Am. Chem. Soc., 2011, vol. 133, p. 16786. 63. Pyatkova, L.N., Shishkin, Yu.L., Apyari, V.V., and Dmitrienko, S.G., Abstracts of Papers, II Vseros. simpozium “Test-metody khimicheskogo analiza” (II AllRussian Conf. on Test Methods of Chemical Analysis), Saratov, 2004, p. 81. 64. Lyra, W.D.S., Santos, V.B., Dionizio, A.G.G., Martins, V.L., Almeida, L.F., Nobrega, Gaiao E., Diniz, P.H.G.D., Silva, E.C., and Araujo, M.C.U., Talanta, 2009, vol. 77, p. 1584. 65. Lopez-Molinero, A., Tejedor Cubero, V., Domingo Irigoyen, R., and Sipiera Piazuelo, D., Talanta, 2013, vol. 103, p. 236. 66. Minamisawa, R.A., Santos, L.E.R., Parada, M.A., Daghastanli, K.R.P., Ciancaglini, P., and De Almeida, A., Instrum. Sci. Technol., 2008, vol. 36, p. 97. 67. Suzuki, Y., Endo, M., Jin, J., Iwase, K., and Iwatsuki, M., Anal. Sci., 2006, vol. 22, p. 411. 68. Nitinaivinij, K., Parnklang, T., Thammacharoen, C., Ekgasit, S., and Wongravee, K., Anal. Methods, 2014, vol. 6, p. 9816. 69. Niu, L.Y., Li, H., Feng, L., Guan, Y.S., Chen, Y.Z., Duan, C.F., Wu, L.Z., Guan, Y.F., Tung, C.H., and Yang, Q.Z., Anal. Chim. Acta, 2013, vol. 775, p. 93. 70. Ariza-Avidad, M., Salinas-Castillo, A., Cuellar, M.P., Agudo-Acemel, M., Pegalajar, M.C., and CapitanVallvey, L.F., Anal. Chem., 2014, vol. 86, p. 8634. 71. Zamora, L.L., Lopez, P.A., Fos, G.M.A., Algarra, R.M., N., Romero, A.M.M., and Calatayud, J.M.N., Talanta, 2011, vol. 83, p. 1575.

72. Wang, X.D., Meier, R.J., Link, M., and Wolfbeis, O.S., Angew. Chem., Int. Ed. Engl., 2010, vol. 49, p. 4907. 73. Meier, R.J., Schreml, S., Wang, X.D., Landthaler, M., Babilas, P., and Wolfbeis, O.S., Angew. Chem., Int. Ed. Engl., 2011, vol. 50, p. 10893. 74. Larsen, M., Borisov, S.M., Grunwald, B., Klimant, I., and Glud, R.N., Limnol. Oceanogr. Methods, 2011, vol. 9, p. 348. 75. Ariza-Avidad, M., Agudo-Acemel, M., Salinas-Castillo, A., and Capitan-Vallvey, L.F., Anal. Chim. Acta, 2015, vol. 872, p. 55. 76. Lopez-Molinero, A., Linan, D., Sipiera, D., and Falcon, R., Microchem. J., 2010, vol. 96, p. 380. 77. Cai, L., Wu, Y., Xu, C., and Chen, Z., J. Chem. Educ., 2013, vol. 90, p. 232. 78. Choodum, A. and Nic Daeid, N., Drug Test. Anal., 2011, vol. 3, p. 277. 79. Banerjee, S.S., Roychowdhury, A., Taneja, N., Janrao, R., Khandare, J., and Paul, D., Sens. Actuators, B, 2013, vol. 186, p. 439. 80. Dani, D.N., Bannur, S.V., Kulgod, S.V., and Sainis, J.K., Physiol. Mol. Biol. Plants, 2005, vol. 11, p. 321. 81. Alimelli, A., Filippini, D., Paolesse, R., Moretti, S., Ciolfi, G., D’Amico, A., Lundstrom, I., and Di Natale, C., Anal. Chim. Acta, 2007, vol. 597, p. 103. 82. Lima, M.B., Andrade, S.I., Barreto, I.S., Almeida, L.F., and Araujo-Nobrega, J., Microchem. J., 2013, vol. 106, p. 238. 83. Choodum, A., Kanatharana, P., Wongniramaikul, W., and Nicdaeid N., Forensic Sci. Int., 2012, vol. 222, p. 340. 84. Chen, Y.Y., Unnikrishnan, B., Li, Y.J., and Huang, C.C., Analyst, 2014, vol. 139, p. 5977. 85. Sumriddetchkajorn, S., Chaitavon, K., and Intaravanne, Y., Sens. Actuators, B, 2013, vol. 182, p. 592. 86. Wei, Q., Nagi, R., Sadeghi, K., Feng, S., Yan, E., Ki, S.J., Caire, R., Tseng, D., and Ozcan, A., ACS Nano, 2014, vol. 8, p. 1121. 87. El Kaoutit, H., Estevez, P., Garcia, F.C., Serna, F., and Garcia, J.M., Anal. Methods, 2013, vol. 5, p. 54. 88. Garcia, A., Erenas, M.M., Marinetto, E.D., Abad, C.A., de Orbe-Paya, I., Palma, A.J., and Capitan-Vallvey, L.F., Sens. Actuators, B, 2011, vol. 156, p. 350. 89. Moraes, E.P., Silva, N.S.A., de Morais, C.D., Neves, L.S.D., and Lima, K.M.G., J. Chem. Educ., 2014, vol. 91, p. 1958. 90. Lopez-Ruiz, N., Curto, V.F., Erenas, M.M., BenitoLopez, F., Diamond, D., Palma, A.J., and CapitanVallvey, L.F., Anal. Chem., 2014, vol. 86, p. 9554. 91. Lopez-Ruiz, N., Martinez-Olmos, A., Perez de Vargas Sansalvador, I.M., Fernandez-Ramos, M.D., Carvajal, M.A., Capitan-Vallvey, L.F., and Palma, A.J., Sens. Actuators, B, 2012, vols. 171–172, p. 938. 92. Coskun, A.F., Wong, J., Khodadadi, D., Nagi, R., Tey, A., and Ozcan, A., Lab Chip, 2013, vol. 13, p. 636. 93. Salles, M.O., Meloni, G.N., de Araujo, W.R., and Paixao, T.R.L.C., Anal. Methods, 2014, vol. 6, p. 2047. 94. Lee, S., Oncescu, V., Mancuso, M., Mehta, S., and Erickson, D., Lab Chip, 2014, vol. 14, p. 1437.

JOURNAL OF ANALYTICAL CHEMISTRY

Vol. 72

No. 11

2017

USE OF HOUSEHOLD COLOR-RECORDING DEVICES 95. Choi, S., Kim, S., Yang, J.S., Lee, J.H., Joo, C., and Jung, H.I., Sens. Biosens. Res., 2014, vol. 2, p. 8. 96. Iqbal, Z. and Bjorklund, R.B., Int. J. Food Sci. Technol., 2011, vol. 46, p. 2428. 97. Oncescu, V., Mancuso, M., and Erickson, D., Lab Chip, 2014, vol. 14, p. 759. 98. Delaney, J.L., Doeven, E.H., Harsant, A.J., and Hogan, C.F., Anal. Chim. Acta, 2013, vol. 803, p. 123. 99. Thom, N.K., Lewis, G.G., Yeung, K., and Phillips, S.T., RSC Adv., 2014, vol. 4, p. 1334. 100. Chun, H.J., Park, Y.M., Han, Y.D., Jang, Y.H., and Yoon, H.C., BioChip J., 2014, vol. 8, p. 218. 101. Murdock, R.C., Shen, L., Griffin, D.K., KelleyLoughnane, N., Papautsky, I., and Hagen, J.A., Anal. Chem., 2013, vol. 85, p. 11634. 102. Ozdalga, E., Ozdalga, A., and Ahuja, N., J. Med. Internet Res., 2012, vol. 14. 103. Gorocs, Z. and Ozcan, A., Lab Chip, 2014, vol. 14, p. 3248. 104. Apyari, V.V., Dmitrienko, S.G., Batov, I.V., and Zolotov, Yu.A., J. Anal. Chem., 2011, vol. 66, p. 144. 105. Apyari, V.V., Dmitrienko, S.G., and Zolotov, Yu.A., Sens. Actuators, B, 2013, vol. 188, p. 1109. 106. Marchenko, D.Yu., Petrov, S.I., Sandzhieva, D.A., and Dedov, A.G., Khim. Tekhnol., 2015, vol. 16, no. 3, p. 186. 107. Ostrovskaya, V.M., Prokopenko, O.A., Sereda, V.V., and Marchenko, D.Yu., Abstracts of Papers, III Vseros. konferentsiya “Analitika Rossii 2009” (III All-Rus-

JOURNAL OF ANALYTICAL CHEMISTRY

Vol. 72

1137

sian Conf. on Analytical Chemistry in Russia), Krasnodar, 2009, p. 147. 108. Apyari, V.V., Batov, I.V., and Dmitrienko, S.G., Abstracts of Papers, S”ezd analitikov Rossii i Shkoly molodykh uchenykh “Analiticheskaya khimiya — novye metody i vozmozhnosti” (Conf. of Analytical Chemists of Russia and the School of Young Scientists “Analytical Chemistry: New Methods and Possibilities”), Moscow, 2010, p. 25. 109. Ramazanova, G.R., Tikhomirova, T.I., and Apyari, V.V., Abstracts of Papers, I Int. Caparica Conf. on Chromogenic and Emissive Materials IC3EM 2014, Caparica, Portugal, 2014, p. 227. 110. Ostrovskaya, V.M., Prokopenko, O.A., and Man’shev, D.A., Tr. 25 Gos. Nauchn.-Issled. Inst. Khimmotolog. Ministerstva Oborony Ross. Fed. (Proc. 25th State Sci. Research Inst. of Chemometology of the Ministry of Defense of the Russian Federation), Moscow, 2010, no. 56, p. 227. 111. Sakaue, H., Ozaki, T., and Ishikawa, H., Sensors (Basel), 2009, vol. 9, p. 4151. 112. Lee, D., Chou, W.P., Yeh, S.H., Chen, P.J., and Chen, P.H., Biosens. Bioelectron., 2011, vol. 26, p. 4349. 113. Askim, J.R., Mahmoudi, M., and Suslick, K.S., Chem. Soc. Rev., 2013, vol. 42, p. 8649.

No. 11

Translated by O. Zhukova

2017