In the Laboratory edited by
Cost-Effective Teacher
Harold H. Harris
Demonstration of Absorbance Using Digital Color Image Analysis and Colored Solutions
University of Missouri—St. Louis St. Louis, MO 63121
This article describes a simple experiment in which the principle of absorbance may be demonstrated using digital color image analysis. Dilute yellow food coloring solutions in water were prepared in known relative concentrations and photographed in transparent cuvettes as a group placed against a diffuse fluorescent white light lightbox. Image analysis of the intensity of the complementary color (blue) for each solution produced data that conformed to the Beer–Lambert law. Methods and Results Food coloring solutions were prepared as follows: 1 drop of yellow food coloring (McCormick & Co., Inc.) was placed in 50 mL of water as a stock solution. From this solution
0.9 0.8
Absorbance
0.7 0.6
(with an assigned concentration of 100%), 4-mL solutions of known relative concentration were prepared by dilution of aliquots of the 100% solution in water (75%: 3 mL:1 mL; 50%: 2 mL:2 mL; 25%: 1 mL:3 mL; 0%: 0 mL:4 mL). As the yellow food coloring absorbs strongly in blue (Figure 1), an absorbance curve at 405 nm for this series of solutions was expectedly linear when measured using a conventional microtiter plate reader (Figure 2). To produce absorbance data by image analysis using a digital color camera, solutions were placed in transparent 1cm cuvettes and photographed against a fluorescent white light lightbox using a digital camera (Canon Powershot A50) using automatic settings. The lightbox utilizes a cylindrical fluorescent light bulb that shines onto a reflector below a frosted white glass, producing an apparently uniform brightness of light across the majority of its width. Using a bitmap image cropped from the original photograph (Figure 3), the light intensities (integer 0–255) for the red, green, and blue components of the image color for pixels within the fluid segment for each cuvette were recorded (Table 1) using image analysis
0.5 0.4 0.3 0.2 0.1 0.0 400
450
500
550
600
650
700
Wavelength / nm Figure 1. Absorbance versus wavelength scan of a dilute aqueous solution of yellow food coloring made using a spectrophotometer (Hitachi U200, 20-nm steps). Reference cell contains water. Figure 3. Contrast-enhanced grayscale version of the camera image used for data analysis. Left to right: 100%, 75%, 50%, 25%, 0% relative concentration. (See the online PDF for a color version.)
1.4
Absorbance (405 nm)
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Shane K. Kohl, James D. Landmark, and Douglas F. Stickle* Department of Pathology & Microbiology, University of Nebraska Medical Center, Omaha, NE 68198-3135; *
[email protected] 1.2 1.0
Table 1. Red, Green, and Blue Intensity Data from Image Analysis
0.8
Concentration (%)
Red
Green
Blue
000
194
215
192
025
196
219
095
0.2
050
197
220
044
0.0
075
199
216
022
100
196
211
010
0.6
y = 0.0128x + 0.0284 R 2 = 0.9998
0.4
0
20
40
60
80
100
Relative Concentration (%) Figure 2. Absorbance versus relative concentration of the yellow solutions using a microtiter plate reader (Bio-Tek ELx808).
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NOTE: Image analysis from solutions shown in Figure 3. Data are the average values for R, G, and B (rounded to the nearest integer) of area (100 pixels) at approximately center width and center height of the fluid level of each cuvette.
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In the Laboratory 1.4 1.2 1.0
log(I0 /I)
software as previously described (1). Despite the likely broad bandwidth of the camera for the three colors (nominally, blue = 400–500 nm, green = 500–600 nm, red = 600–700 nm), the intensity of the complementary color (blue) decreased exponentially with the concentration of the food coloring (Figure 4), resulting in a linear absorbance curve (Figure 5) according to the principles of the Beer–Lambert law (2). Hazards There are no particular hazards associated with the experiment. However, protective clothing and eyewear should be worn in the laboratory as a matter of standard practice.
0.8 0.6
y = 0.0128x − 0.0065 R 2 = 0.9996
0.4 0.2 0.0 0
20
40
60
80
100
Relative Concentration (%)
Discussion There are numerous previous demonstrations or discussions of the Beer–Lambert law in this Journal (e.g., refs 3– 10; additional entries can be easily found using the JCE Online search engine). At a more elementary level, the experiment demonstrates the absorbance of light for a colored solution by its complementary color (11). Additionally, the primary data demonstrate the concept of a standard curve from which the relative concentration of an unknown could be determined. A number of caveats about the demonstration should be noted. First, this is a simple demonstration that intentionally used a single-component solution; image analysis using only red, green, and blue intensity data could not distinguish single sharp absorbance peaks in complex solutions. Thus, a camera and image analysis could not generally substitute for a spectrophotometer except under such special conditions. Second, while the experiment worked well with our available lightbox, other lightbox arrangements might for many reasons be found to be unsuitable. For instance, a lightbox utilizing a point light source is likely to be unsuitable for a group camera shot of the solutions, although single camera shots for each solution (with fixed rather than automatic camera settings) might produce suitable data. As an alternative to a lightbox, transparency scanner images of solutions in a transparent microtiter plate can produce equally usable data (Figures 6 and 7). In either setup, it is probably important that the background light intensity should be such that the intensity of the 0% solution is unsaturated (< 255).
Figure 5. Absorbance plot for blue light intensity by image analysis for Figure 3: I0 is the blue light intensity for the 0% solution and I is the blue light intensity for the series of solutions.
Figure 6. Contrast-enhanced grayscale transparency scanner image of the yellow solutions in a flat-bottom transparent plastic microtiter plate (triplicate aliquots, 200 µL) made using a transparency scanner (Hewlett-Packard Scanjet 7400c). Top to bottom rows: 100%, 75%, 50%, 25%, 0% relative concentration. (See page 515 as well as the online PDF for a color version.)
250
0.5
0.4
150
log(I0 /I)
Blue Intensity
200
100
50
0.3
0.2
y = 0.0047x − 0.005 R 2 = 0.9994
0.1
0 0
20
40
60
80
100
0.0 0
20
Relative Concentration (%) Figure 4. Pixel color intensity plot for blue (data from Table 1). Line: single exponential curve fit.
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40
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Relative Concentration (%) Figure 7. Absorbance plot for blue light intensity by image analysis for Figure 6.
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Third, it is of primary importance in the demonstration that the dilutions of the stock solution are made accurately. Last, for data collection, note that commercial image software packages typically have the capability to show red, green, and blue pixel color component data; the program ImageJ (12) can also produce equivalent data. As an associated point of discussion for this demonstration, students might be encouraged to learn about the chemical composition and history of food coloring (e.g., see refs 13 and 14 ). Literature Cited 1. Mathews, K. R.; Landmark, J. D.; Stickle, D. F. J. Chem Educ. 2004, 81, 702–704. 2. Cantor, C. R.; Schimmel, P. R. Biophysical Chemistry Part II: Techniques for the Study of Structure and Function; W. H. Freeman and Company: New York, 1980; p 364.
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3. Gordon, J.; Harman, S. A. J. Chem Educ. 2002, 79, 611–612. 4. Stewart, S. A.; Sommer, A. J. J. Chem Educ. 1999, 76, 399– 400. 5. Calloway, D. J. Chem Educ. 1997, 74, 744. 6. Ricci, R. W.; Ditzler, M.; Nestor, L. P. J. Chem Educ. 1994, 71, 983–985. 7. Bowman, L. H. J. Chem Educ. 1982, 59, 154. 8. Swinehart, D. F. J. Chem Educ. 1962, 39, 333. 9. Holleran, E. M. J. Chem Educ. 1955, 32, 636. 10. Lohman, F. H. J. Chem Educ. 1955, 32, 155. 11. Suding, H. L.; Buccigross, J. M. J. Chem Educ. 1994, 71, 798– 799. 12. ImageJ image analysis software is available for free download at: http://rsb.info.nih.gov/ij/ (accessed Dec 2005). 13. U.S. FDA Color Additives. http://vm.cfsan.fda.gov/~dms/coltoc.html (accessed Dec 2005). 14. Gilman, V. Chem Eng News 2003, 81, 34. http://pubs.acs.org/ cen/whatstuff/stuff/8134foodcoloring.html (accessed Dec 2005).
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