In the Laboratory

644 Journal of Chemical Education • Vol. 83 No. 4 April 2006 • www.JCE.DivCHED.org

This article describes a simple experiment in which theprinciple of absorbance may be demonstrated using digitalcolor image analysis. Dilute yellow food coloring solutions inwater were prepared in known relative concentrations and pho-tographed in transparent cuvettes as a group placed against adiffuse fluorescent white light lightbox. Image analysis of theintensity of the complementary color (blue) for each solutionproduced data that conformed to the Beer–Lambert law.

Methods and ResultsFood coloring solutions were prepared as follows: 1 drop

of yellow food coloring (McCormick & Co., Inc.) was placedin 50 mL of water as a stock solution. From this solution

(with an assigned concentration of 100%), 4-mL solutionsof known relative concentration were prepared by dilutionof 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). Asthe yellow food coloring absorbs strongly in blue (Figure 1),an absorbance curve at 405 nm for this series of solutionswas expectedly linear when measured using a conventionalmicrotiter plate reader (Figure 2).

To produce absorbance data by image analysis using adigital color camera, solutions were placed in transparent 1-cm cuvettes and photographed against a fluorescent white lightlightbox using a digital camera (Canon Powershot A50) us-ing automatic settings. The lightbox utilizes a cylindrical fluo-rescent light bulb that shines onto a reflector below a frostedwhite glass, producing an apparently uniform brightness oflight across the majority of its width. Using a bitmap imagecropped from the original photograph (Figure 3), the lightintensities (integer 0–255) for the red, green, and blue com-ponents of the image color for pixels within the fluid segmentfor each cuvette were recorded (Table 1) using image analysis

Demonstration of Absorbance Using Digital ColorImage Analysis and Colored SolutionsShane K. Kohl, James D. Landmark, and Douglas F. Stickle*Department of Pathology & Microbiology, University of Nebraska Medical Center, Omaha, NE 68198-3135;*dstickle@unmc.edu

Cost-Effective Teacheredited by

Harold H. HarrisUniversity of Missouri—St. Louis

St. Louis, MO 63121

Figure 3. Contrast-enhanced grayscale version of the camera im-age used for data analysis. Left to right: 100%, 75%, 50%, 25%,0% relative concentration. (See the online PDF for a color version.)

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)%(noitartnecnoC deR neerG eulB

00 0 491 512 291

0 52 691 912 0 59

0 05 791 022 0 44

0 57 991 612 0 22

001 691 112 0 01

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Figure 1. Absorbance versus wavelength scan of a dilute aqueoussolution of yellow food coloring made using a spectrophotometer(Hitachi U200, 20-nm steps). Reference cell contains water.

Abs

orba

nce

Wavelength / nm

0.9

0.7

0.8

0.6

0.5

0.4

0.3

0.2

0.1

0.0400 450 500 550 600 650 700

Figure 2. Absorbance versus relative concentration of the yellowsolutions using a microtiter plate reader (Bio-Tek ELx808).

Abs

orba

nce

(405

nm

)

Relative Concentration (%)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0 20 40 60 80 100

y = 0.0128x + 0.0284R2 = 0.9998

In the Laboratory

www.JCE.DivCHED.org • Vol. 83 No. 4 April 2006 • Journal of Chemical Education 645

software as previously described (1). Despite the likely broadbandwidth 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 ex-ponentially with the concentration of the food coloring (Fig-ure 4), resulting in a linear absorbance curve (Figure 5)according to the principles of the Beer–Lambert law (2).

HazardsThere are no particular hazards associated with the ex-

periment. However, protective clothing and eyewear shouldbe worn in the laboratory as a matter of standard practice.

Discussion

There are numerous previous demonstrations or discus-sions of the Beer–Lambert law in this Journal (e.g., refs 3–10; additional entries can be easily found using the JCEOnline search engine). At a more elementary level, the ex-periment demonstrates the absorbance of light for a coloredsolution by its complementary color (11). Additionally, theprimary data demonstrate the concept of a standard curvefrom which the relative concentration of an unknown couldbe determined.

A number of caveats about the demonstration shouldbe noted. First, this is a simple demonstration that inten-tionally used a single-component solution; image analysisusing only red, green, and blue intensity data could not dis-tinguish single sharp absorbance peaks in complex solutions.Thus, a camera and image analysis could not generally sub-stitute for a spectrophotometer except under such special con-ditions. Second, while the experiment worked well with ouravailable lightbox, other lightbox arrangements might formany reasons be found to be unsuitable. For instance, alightbox utilizing a point light source is likely to be unsuit-able for a group camera shot of the solutions, although singlecamera shots for each solution (with fixed rather than auto-matic camera settings) might produce suitable data. As analternative to a lightbox, transparency scanner images of so-lutions in a transparent microtiter plate can produce equallyusable data (Figures 6 and 7). In either setup, it is probablyimportant that the background light intensity should be suchthat the intensity of the 0% solution is unsaturated (< 255).

Figure 4. Pixel color intensity plot for blue (data from Table 1).Line: single exponential curve fit.

Blu

e In

tens

ity

Relative Concentration (%)

0

50

100

150

200

250

0 20 40 60 80 100

Figure 7. Absorbance plot for blue light intensity by image analy-sis for Figure 6.

Relative Concentration (%)

0.0

0.1

0.2

0.3

0.4

0.5

y = 0.0047x − 0.005R2 = 0.9994

0 20 40 60 80 100

log

(I0/I

)

Figure 5. Absorbance plot for blue light intensity by image analy-sis for Figure 3: I0 is the blue light intensity for the 0% solution andI is the blue light intensity for the series of solutions.

log

(I0/I

)

Relative Concentration (%)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

y = 0.0128x − 0.0065R2 = 0.9996

0 20 40 60 80 100

Figure 6. Contrast-enhanced grayscale transparency scanner im-age of the yellow solutions in a flat-bottom transparent plasticmicrotiter plate (triplicate aliquots, 200 µL) made using a trans-parency scanner (Hewlett-Packard Scanjet 7400c). Top to bot-tom rows: 100%, 75%, 50%, 25%, 0% relative concentration.(See page 515 as well as the online PDF for a color version.)

In the Laboratory

646 Journal of Chemical Education • Vol. 83 No. 4 April 2006 • www.JCE.DivCHED.org

Third, it is of primary importance in the demonstration thatthe dilutions of the stock solution are made accurately. Last,for data collection, note that commercial image software pack-ages typically have the capability to show red, green, and bluepixel color component data; the program ImageJ (12) can alsoproduce equivalent data.

As an associated point of discussion for this demonstra-tion, students might be encouraged to learn about the chemi-cal composition and history of food coloring (e.g., see refs13 and 14 ).

Literature Cited

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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/col-

toc.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).