In the Laboratory edited by
Cost-Effective Teacher
Harold H. Harris University of Missouri—St. Louis St. Louis, MO 63121
Microscale Colorimetric Analysis Using a Desktop Scanner and Automated Digital Image Analysis Douglas J. Soldat,* Phillip Barak, and Brian J. Lepore† Department of Soil Science, University of Wisconsin–Madison, Madison, WI 53706; *
[email protected] In recent decades, several standard colorimetric reactions for chemical analysis have been miniaturized to microwells on microplates, including methods useful for environmental measurements. Advantages of method miniaturization are a reduction in reagents required, improved safety, reduced waste stream, and increased sample throughput. However, the widespread use of microscale techniques employing microplates in classroom settings is likely limited by the cost of microplate readers, currently around $10,000 for a basic unit. Recently, Kohl et al. (1) showed that the principle of absorbance could be easily demonstrated using colored solutions and digital image analysis. However, the authors speculated that a camera and image analysis could not generally substitute for a spectrophotometer except under special conditions. Although spectrophotometers read peaks of specific wavelengths, absorbance spectra tend to be relatively broad, and measurements at specific wavelengths are highly autocorrelated with those of nearby neighbors, which implies that broadband intensity data of red, green, and blue channels may be adequate for digital colorimetric quantification. According to the Beer–Lambert law, the absorption of light by a compound is equal to the product of the molar absorptivity, the path length of the sample, and the concentration of the compound in the solution. Absorbance can be calculated as
A = − log
I I0
where A is the absorbance, I is the intensity of the light after passing through the solutions, and I0 is the intensity of the light before passing through the solutions. Although the ultimate definition of color and color space resides with the CIE (International Commission on Illumination) colorimetric system based on CIE XYZ tristimulus values, the coding of digital color images in digital photography and scanning more often uses a linear RGB system that is more familiar to the modern, computer-savvy student and instructor (2). The linear RGB color model uses intensity data from three channels (red, green, and blue) to form a single color for each pixel. Numerically, the color is represented by three numbers. In a 24-bit color image, there are 28, or 256, possible values (0–255) for each of the red, green, and blue channels. When white light is transmitted through a colored sample, absorbance of an image can be calculated using red, green, and blue channel data by taking the log of the maximum intensity (255) divided by the actual red, green, or blue value from the image. For example, the absorbance in the red channel of an 8-bit image with a red †Current address: Biological Systems Engineering, University of Wisconsin–Madison, Madison, WI 53706.
channel value of 159 is
A = − log
159 255
= 0. 205
In this article, we demonstrate that digital image analysis of a scanned microplate image can substitute for a spectrophotometer for several common quantitative microscale procedures. This finding allows for cost effective and microscale quantification of several compounds to be demonstrated in the laboratory. Additionally, popular teaching and learning activities such as water-quality monitoring can now be performed accurately and inexpensively using digital image analysis. Materials and Methods To demonstrate that digital image analysis can substitute for a spectrophotometer for quantitative colorimetric analysis, we prepared standard curves for previously published colorimetric methods for microscale determination of ammonium (3), bromide (4), nitrate (5), and phosphate (6, 7) ions. Standard microplates, each with an 8 × 12 array of flat-bottomed 350 µL microwells, were prepared with appropriate standards and color development solutions using an electronic 12-channel pipet. Using the transparency scanner feature (Figure 1) of a commercially available desktop scanner (Epson Perfection 4990
Figure 1. Scanner operating in transparency mode with white light from the lid passing through the 96-well microplates to the light sensors below. The template with cut-outs positions the microplates consistently and blocks stray light. During the scanning operation, the scanner lid is closed and parallel to the scannerbed.
© Division of Chemical Education • www.JCE.DivCHED.org • Vol. 86 No. 5 May 2009 • Journal of Chemical Education
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red
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Intensity of Pixel Figure 2. Image produced by a transparency scan of a microplate with ammonium standards (0–20 mg L–1 N in NH4+) developed according to Sims et al. (3). Parallax due to the sensor location on the vertical axis is apparent in the left- and rightmost columns and suggests the use of ellipses rather than spheres to describe regions of interest within each microwell. (Shown in color on p 533.)
Figure 3. Results of image analysis by ImageJ of an elliptical selection of a microwell on a microplate determining nitrate by Szechrome NAS. The red and green channels were more tightly grouped than the blue channel, and the red and green channels were also more sensitive to changes in nitrate concentration than the blue channel (see Figure 4).
Photo, Long Beach, CA, $449), a 200 dpi, 48-bit (216 values per primary color) digital image of the 96-microwell plates (available from Fisher Scientific) was obtained. We built a simple opaque polycarbonate template that covers the entire scanner bed with a cut-out to hold microplates in the same location (Figure 1) so that the scanned images could be cropped automatically to the size of the microplate with the software provided by the scanner manufacturer. The scanned image was saved in TIFF format, a lossless format. An example of a scanned image is shown in Figure 2. The scanned microplate image was opened with public domain image analysis software, ImageJ version 1.40 (8). This software splits all pixels within an image into their red, green, and blue components. To automate the image analysis process, we developed a custom macro.1 This macro initially requires as input the x and y coordinates (in pixels) of the top left micro well, the number of rows and columns of microwells on the microplate, the number of pixels between them, and the size and eccentricity of the elliptical region of interest for each microwell. Use of a template to hold microplates in a repeatable location on the scanner ensures that these values do not need to be re adjusted for subsequent scans. An elliptical region of interest was chosen because the three-dimensional objects viewed from the central axis of the scanner created a slight overlap of the image of walls and well bottoms. The magnitude of the overlap increased with distance from the central axis of the scanner bed (Figure 2). When conducting image analysis on the scanned images, one could either analyze pixels in a smaller circle avoiding the image of the walls or use an ellipse as the region of interest instead of a complete circle; we chose the latter option because it allowed a greater number of pixels to be analyzed per well without changing the scanner resolution. The macro was designed to export the mean, median, and mode values of red, green, and blue color channels from a 424-pixel ellipsoid at the center of each microplate well into
an ImageJ results spreadsheet. These values were then manually transferred to a standard electronic spreadsheet. After examining the images and their central tendencies for the effects of occasional bubbles and dust particles, we selected median values for red, green, and blue channels of the region of interest to calculate absorbance values, as described in the introduction. The macro is written as a text file, which permits simple editing of the fields to further customization. For comparison, we measured absorbance values for each microplate with a standard microplate reader (Bio-Tek Powerwave XS microplate scanner; Winooski, VT, $12,400) at the appropriate wavelength for each method, within five minutes of the digital scan.
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Hazards The use of a desktop scanner as a microplate reader presents no innate hazards. A method for analyzing phosphate is presented in the online material with the following hazards: Ammonium molybdate is an irritant to eyes, skin, and the respiratory system. Antimony potassium tartrate is toxic and can be fatal if swallowed. It is also an irritant to eyes, skin, and the respiratory system. Monopotassium phosphate is an irritant to eyes, skin, and the respiratory system. Sulfuric acid is corrosive and inhalation can produce damaging effects to the upper respiratory tract. Ingestion or contact with skin can cause severe burns. Contact with eyes can cause severe burns or blindness. Results Image analysis of the colorimetric reactions in the microplates produced tightly clustered red, green, and blue values for each microwell (Figure 3), which allowed for collection of single central values of each to be transformed into absorbance. The minimum requirement for a transparency scanner image
Journal of Chemical Education • Vol. 86 No. 5 May 2009 • www.JCE.DivCHED.org • © Division of Chemical Education
In the Laboratory
B
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Figure 4. Calibration curves created using absorbance values from red, green, or blue channels in scanned images for the colorimetric reactions of (A) ammonium by the phenate method, (B) phosphate by ascorbic acid, (C) nitrate with Szechrome NAS, and (D) bromide by phenol red.
as a substitute for traditional absorbance measurements is the ability to produce calibration curves using at least one of either the red, green, or blue channels for established colorimetric reactions. For ammonium, bromide, nitrate, and phosphate ions, this clearly occurs as seen in Figure 4. In some cases, such as phosphate, all three primaries were correlated with analyte concentration and the line with steepest slope should be chosen as the most sensitive. In other cases, one or more of the primaries are relatively unresponsive to the analyte concentration, but in all cases at least one of the three primaries was correlated with analyte concentration. The primary color that is most sensitive for each analytical method generally follows the standard wavelength chosen for analysis by spectrophotometry. For example, the red primary (~630 nm) is close to the wavelength usually used for ammonium by phenate, 667 nm, and green (~530 nm) is close to that used for bromide analysis by phenol red, 575 nm. Interestingly, the phosphate measurements, usually read at a wavelength of 850 nm, that is, in the infrared range,
are found here to be quite usable with the red primary owing to the broad absorbance peak of the colored complex. Somewhat more difficult to explain to students is the inverse nature of the color measured. For example, for ammonium ion analysis, the yellow blank is the result of the addition of red and green primaries. As the absorption of the red wavelengths increases with increasing ammonium concentrations, the remaining mixture appears greener. For these colorimetric reactions, the use of a scanner operating in transparency mode may be favorably compared to the dedicated microplate reader (Figure 5), sometimes matching the exceptional dynamic range of the microplate reader but at a much lower cost. Conclusions The results of this study indicate that digital image analysis can replace a microplate reader for several microscale
© Division of Chemical Education • www.JCE.DivCHED.org • Vol. 86 No. 5 May 2009 • Journal of Chemical Education
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Figure 5. Relationship between absorbance of the red, green, or blue channel compared to absorbance as determined by microplate reader at the appropriate wavelength for (A) ammonium by the phenate method and bromide by phenol red and (B) nitrate with Szechrome NAS and phosphate by ascorbic acid.
quantitative colorimetric reactions. This finding has several important implications. First, quantitative microscale analysis can be introduced inexpensively into the teaching and learning laboratories, allowing students to gain experience with microscale techniques and analytical methods, and encouraging the use of multiple calibration curves on a single microplate for improved quality control of results. Second, digital image analysis can add extra value to the learning experience, especially during the conversions of red, green, and blue values into absorbance, which enables students to understand the principles behind absorbance and color science. The microscale nature of these methods leads to a reduction in reagents and waste, especially for alkaline or acid reagents, and a reduction in cost when the reagents are relatively expensive. In addition, this method has the potential to be made portable for analyzing results in remote locations by operating the scanner on a generator or storage battery with an inverter, neither of which is likely to work for a standard microplate reader. We have chosen to present here results pertaining to several ions of environmental interest—ammonium, nitrate, phosphate, and bromide—and expect these to bring water contamination and tracer studies within the reach of student and citizen scientists operating with a minimum of laboratory resources, but we have found similar results for chloride (9) and urea (10), and expect the technique to be more widely applicable to many timehonored colorimetric reactions at a microscale.
Literature Cited 1. Kohl, S. K.; Landmark, J. D.; Stickle, D. F. J. Chem. Educ. 2006, 83, 644–646. 2. Hearn, D.; Baker, M. P. Computer Graphics, 2nd ed.; Prentice Hall, Upper Saddle River, NJ, 1994. 3. Sims, G. K.; Ellsworth, T. R.; Mulvaney, R. L. Commun. Soil Sci. Plant Anal. 1995, 26, 303–316. 4. Lepore, B. J.; Barak, P. Soil Sci. Soc. Am. J., in press. 5. Rowe, R.; Todd, R.; Waide, J. Appl. Environ. Microbiol. 1977, 33, 675–680. 6. D’Angelo, E.; Crutchfield, J.; Vandiviere, M.; J. Environ. Qual. 2001, 30, 2206–2209. 7. Avila-Segura, M.; Lyne, J. W.; Meyer, J. M.; Barak, P. Commun. Soil Sci. Plant Anal. 2004, 35, 547–557. 8. ImageJ Home Page. http://rsb.info.nih.gov/ij/ (accessed Feb
2009).
9. Frankenberger, W. T., Jr.; Tabatabai, M. A.; Adriano, D. C.; Doner, H. E. Bromine, Chlorine, and Fluorine. In Methods of Soil Analysis: Part 3- Chemical Methods; Sparks, D. L., Ed.; ASACSSA-SSSA: Madison, WI, 1996; pp 833–867. 10. Greenman, N. S.; Mulvaney, R. L.; Sims, G. K. Commun. Soil Sci. Plant Anal. 1995, 26, 2519–2529.
Supporting JCE Online Material
http://www.jce.divched.org/Journal/Issues/2009/May/abs617.html Abstract and keywords
Note
Full text (PDF) Links to cited URLs and JCE article
1. The macro is available on the Internet at http://mywebspace. wisc.edu/pwbarak/web/AnalyzeMicroplateStatistics.txt (accessed Feb 2009).
Supplement Student and instructor notes for phosphate determination Macro file used to automate the image analysis process
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Journal of Chemical Education • Vol. 86 No. 5 May 2009 • www.JCE.DivCHED.org • © Division of Chemical Education
