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Food Dye Analysis, Lab Reports of Chemistry

Colorimetry and Absorbance-Based Methods Using a Smartphone Camera by Joel F. Destino.

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Food Dye Analysis by Colorimetry and Absorbance-Based Methods Using a Smartphone Camera
Joel F. Destino, Creighton University
1. Overview
This experiment was designed as an at-home lab experiment where students use a smartphone
camera (or other digital camera) to obtain an external calibration and quantitate food dyes in consumer
beverages or other foods. This experiment can be adapted for a range of educational levels, depending on
the background information given how to create the setup and a linear range. This work is based mainly
on an experiment and information reported in the article by Destino and Cunningham “At-Home
Colorimetric and Absorbance-Based Analyses: An Opportunity for Inquiry-Based, Laboratory-Style
Learning(under revision at J. Chem. Educ.). There are also several similar exercises previously
published for in-class colorimetric analysis using a smartphone camera.1–3
The following information provides general instructions, suggested materials, experimental setup,
and analysis instructions. The information provided can be used as a starting point for instructors
developing an at-home or in-lab experiment for students.
Active Learning Goals: Students could design studies that…
Evaluate the precision of different solution preparation schemes
Evaluate the effect of experimental setup (e.g., sample path length, back lighting, etc.)
Evaluate the linearity of the external calibration
Compare calibration curves for different signals
Evaluate the precision of the instrument
Measure food dye (or other chromophore) concentration in consumer beverages (or other
samples)
Test and compare against a traditional spectrophotometer devices with the same samples
Perform statistical analysis on their and other student data (see next section)
Topics of discussion and data analysis:
Discussion of analytical figures of merit (precision, linear range, linearity, sensitivity)
Data and statistical analysis comparison of different sample preparation schemes, signals,
setups/instruments, or other variables
Discussion of accuracy and precision of solution preparation tools, visible light absorption, Beer-
Lambert Law, spectrophotometry, method development, and statistical analysis
Discussion on food dyes (or other analytes) in consumer goods
Rel. Conc. Green Dye (ppm)
0.0 95.0 189.0 370.0 714.0
Tria l 1Tria l 2Tria l 3
Smartphone
or
Digital
Camera
Blank 107 212 415 797
Rel. Conc. Green Dye (ppm)
0.0 95.0 189.0 370.0 714.0
Tria l 1Tria l 2Tria l 3
y = 1.97E-04x -1.69E-02
R² = 9.96E-01
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0200 400 600 800
G/T
G/T Linear Range
y = 4.79E-04x + 1.89E-03
R² = 9.99E-01
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0200 400 600 800
Absorbance
Rel. Conc. Green Dye (ppm)
R Absorption Linear Range
Experiment Results Analysis
Figure 1: Overview scheme for at-home colorimetric and absorbance-based method development.
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Food Dye Analysis by Colorimetry and Absorbance-Based Methods Using a Smartphone Camera Joel F. Destino, Creighton University

1. Overview This experiment was designed as an at-home lab experiment where students use a smartphone camera (or other digital camera) to obtain an external calibration and quantitate food dyes in consumer beverages or other foods. This experiment can be adapted for a range of educational levels, depending on the background information given how to create the setup and a linear range. This work is based mainly on an experiment and information reported in the article by Destino and Cunningham “At-Home Colorimetric and Absorbance-Based Analyses: An Opportunity for Inquiry-Based, Laboratory-Style Learning” (under revision at J. Chem. Educ. ). There are also several similar exercises previously published for in-class colorimetric analysis using a smartphone camera.^1 –^3 The following information provides general instructions, suggested materials, experimental setup, and analysis instructions. The information provided can be used as a starting point for instructors developing an at-home or in-lab experiment for students. Active Learning Goals: Students could design studies that… - Evaluate the precision of different solution preparation schemes - Evaluate the effect of experimental setup (e.g., sample path length, back lighting, etc.) - Evaluate the linearity of the external calibration - Compare calibration curves for different signals - Evaluate the precision of the instrument - Measure food dye (or other chromophore) concentration in consumer beverages (or other samples) - Test and compare against a traditional spectrophotometer devices with the same samples - Perform statistical analysis on their and other student data (see next section) Topics of discussion and data analysis: - Discussion of analytical figures of merit (precision, linear range, linearity, sensitivity) - Data and statistical analysis – comparison of different sample preparation schemes, signals, setups/instruments, or other variables - Discussion of accuracy and precision of solution preparation tools, visible light absorption, Beer- Lambert Law, spectrophotometry, method development, and statistical analysis - Discussion on food dyes (or other analytes) in consumer goods Rel. Conc. Green Dye (ppm) 0.0 95.0 189.0 370.0 714. Trial 1 Trial 2 Trial 3 Smartphone or Digital Camera Blank 107 212 415 797 Rel. Conc. Green Dye (ppm) 0.0 95.0 189.0 370.0 714. Trial 1 Trial 2 Trial 3 y = 1.97E R² = 9.96E-04x - 1.69E- 01 - 02

0 200 400 600 800 G/T G/T Linear Range y = 4.79E R² = 9.99E-04x + 1.89E- 01 - 03

0 200 400 600 800 Absorbance Rel. Conc. Green Dye (ppm) R Absorption Linear Range Experiment Results Analysis Figure 1 : Overview scheme for at-home colorimetric and absorbance-based method development.

2. Background and Relevance Real-world chemistry examples, such as those found in the home or nature, are ideal when helping students connect chemical concepts to everyday life. They also help motivate students and inspire interest in chemistry. Synthetic food dyes and colorants are convenient for chemical education because they can be found in a wide range of everyday products. Many colorimetric and spectrophotometric analyses are reported using FDA-approved food dyes, and their spectroscopic and chromatographic properties are well known.^4 Thus, given their familiarity, ubiquity, and well-documented properties, food dyes are ideal analytes for performing at-home chemical analysis. 3. Basics of Colorimetry and Beer’s Law The term colorimetry generally describes any technique used to determine the concentration of a visibly colored analyte in solution. This can be accomplished by measuring the color the sample appears, or by measuring the light absorbed using Beer-Lambert law. Historically, colorimeters were typically absorbance-based photometers designed to measure the absorbance at one of a few different wavelengths, either by use of filters or different light sources.^5 By the historical definition, spectrophotometry is a subcategory of colorimetry, specific to absorbance-based analysis using a dispersive element, such as a monochromator. For the sake of this experiment, colorimetry will be defined by the former definition— a method to determine analyte concentration based on the color the sample appears. While analysis based directly on Beer-Lambert phenomena will be referred to as “absorbance-based”. The Beer–Lambert law, also known as Beer's law, relates the loss of transmitted light (absorbance, or A) to the concentration (C) and the optical path length (b) the light travels, as given by equation 1. A = 𝜀bC (𝜀 is molar absorptivity) Equation 1 Depending on the nature of your at-home assignment, you may adapt the experiment to focus on chemistry, theory, or analysis and method development. For more information on all three, see David Harvey’s text on “Spectroscopy Based on Absorption”.^6 For more information on the chemistry and basic theory, see William Reusch’s webpage on “Visible and Ultraviolet Spectroscopy”^7. For quantitative analysis, you may also want to talk about camera sensors. Smartphone cameras are able to generate R, G, and B images because they have individual pixels that sensitive those wavelengths of light. Thus, by using a smartphone camera, you have low-resolution (effectively, 3- channel) spectral discrimination. For more information on color processing and imaging, see Mark Fairchild’s webpage on “How Do Digital Cameras Detect Color?”.^8 4. Experimental-Materials and Solution Preparation Standard Reagents The experiment has been validated for samples containing FD&C Red 40 (a.k.a., allura red), Yellow 5 (a.k.a., tartrazine), and Blue 1 (a.k.a. erioglaucine). It could be adapted for others. Allura Red AC, TCI America™, 5 g; FD&C Red 40; $23. https://www.fishersci.com/shop/products/allura-red-ac-tci-america- 2/A09435G#?keyword=25956- 17 - 6 Erioglaucine disodium salt, pure, ACROS Organics™, 5 g; FD&C Blue 1; $23. https://www.fishersci.com/shop/products/erioglaucine-disodium-salt-pure-acros-organics- 2/AC Tartrazine, Alfa Aesar™, 25 g; FD&C Yellow 5; $18. https://www.fishersci.com/shop/products/tartrazine-8/AAA1768214#?keyword=1934- 21 - 0

Unknown Samples The experiment can be designed to determine the concentration of a FD&C in a common consumer product. Potential common consumer products containing FD&C Red 40, Yellow 5, and Blue 1 are listed. Note: transparent (i.e., non-opaque samples) are preferred, as transmission loss due to scatter can be problematic for absorbance-based analysis. Common consumer food coloring options: Wilton®^ Red, Yellow, Green and Blue Food Coloring - 1oz; $2. https://www.target.com/p/wilton-red-yellow-green-and-blue-food-coloring-1oz/-/A- 53701700 *Blue coloring contains solely FD&C Blue 1, all other colors are mixtures of multiple dyes. Wilton®^ blue coloring was used for samples appearing in Figure 4. McCormick®^ 4ct Assorted Food Color and Egg Dye - 1oz; $3. https://www.target.com/p/mccormick-4ct-assorted-food-color-and-egg-dye-1oz/-/A- 13353207 *All colors are mixtures of multiple dyes. Betty Crocker®^ Classic Gel Food Colors - 4 CT; $8. https://www.amazon.com/Betty-Crocker-Classic-Food-Colors/dp/B004PXNV2M

  • The only ingredients listed are yellow 5, blue 1, red 40. Presumably all but green coloring are single dye. Other food colorings containing a single dye: Wilton®^ Icing Color, Red (no-taste), 1oz; FD&C Red 40; $1. https://www.walmart.com/ip/Wilton-Icing-Color-Red-no-taste-1oz/24107796?selected=true Wilton®^ Sky Blue Icing Color, 1 oz; FD&C Blue 1; $1. https://www.walmart.com/ip/Wilton-Sky-Blue-Icing-Color- 1 - oz/24107658?selected=true Wilton®^ Lemon Yellow Icing Color, 1 oz; FD&C Yellow 5; $8. https://www.walmart.com/ip/Wilton-Lemon-Yellow-Icing-Color- 1 - oz/24107648?selected=true (Some) Common consumer goods with food coloring for analysis at-home: Sports Drinks POWERADE®, Blue Raspberry Cherry AND Zero Sugar Mixed Berry (FD&C Blue 1); Fruit Punch AND Zero Sugar Fruit Punch (FD&C Red 40); Lemon Lime (FD&C Yellow 5) https://www.coca-colaproductfacts.com/en/products/powerade/blue-raspberry-cherry/32-oz/ https://www.coca-colaproductfacts.com/en/products/powerade-zero/mixed-berry/32-oz/ https://www.coca-colaproductfacts.com/en/products/powerade/fruit-punch/32-oz/ https://www.coca-colaproductfacts.com/en/products/powerade-zero/fruit-punch/32-oz/ https://www.coca-colaproductfacts.com/en/products/powerade/lemon-lime/32-oz/ Gatorade®, Cool Blue (FD&C Blue 1); Fruit Punch (FD&C Red 40); Lemon Lime (FD&C Yellow 5) Liquid: https://www.gatorade.com/products/sports-drinks/frost-thirst-quencher-variety- 20 - fl-oz- 24 - pack https://www.gatorade.com/products/sports-drinks/thirst-quencher-original-variety- 20 - fl-oz- 24 - pack Powder: https://www.gatorade.com/products/sports-drinks/frost-thirst-quencher-powder-glacier-freeze- 50 - 9 - oz-canister

https://www.gatorade.com/products/sports-drinks/thirst-quencher-powder-lemon-lime- 50 - 9 - oz- canister https://www.gatorade.com/products/sports-drinks/thirst-quencher-powder-fruit-punch- 50 - 9 - oz- canister Candy Blue Candy-Filled Straws (FD&C Blue 1) https://www.orientaltrading.com/blue-candy-filled-straws-a2-13645044.fltr?keyword=candy- filled-straws Red, Hot Pink, and Light Pink Candy-Filled Straws (FD&C Red 40) https://www.orientaltrading.com/hot-pink-candy-filled-straws-a2- 13645032.fltr?keyword=Hot+Pink+Candy-Filled+Straws Lik•m•aid®^ Fun Dip, Cherry (FD&C Red 40 as a lake: i.e., a metal salt) https://www.amazon.com/FUN-DIP-Lik-Aid-48ct/dp/B0007OVWKG Ready-to-Use Gel Icings Wilton Ready-to-Use Icing Tube, Red; FD&C Red 40 https://www.walmart.com/ip/Wilton-Ready-to-Use-Icing-Tube-Red- 4 - 25oz/ Great Value Decorating Gel, Blue; FD&C Blue 1 https://www.walmart.com/ip/Great-Value-Blue-Decorating-Gel- 0 - 67oz/269533074?selected=true

Comments On Experimental Setup

  • Pathlength is important. Students using containers with larger pathlengths or non- square pathlengths will need to be aware of this when it comes to determining concentration ranges and image analysis plans, respectively. It could negatively impact their results.
  • Backlighting must be consistent, but not necessarily on the brightest setting. Too much light will wash out weakly absorbing samples. And inconsistent backlighting will make it impossible to compare across multiple images. This can be avoided by using multiple sample containers all in one image as shown in Figure 4. Capturing photos in the same day is highly recommended, and analyzing the data before cleaning up the setup is also recommended.
  • Let the unknown assist with determing standard concentration range. If developing a method for an unknown, guide students to optimize setup conditions for the unknown, then making standards that appear to closely bookend the color of the unknown. RGB Analysis There are several ways to measure R, G, and B intensities using mobile phone applications and software.1,3,9,10^ In this study, R, G, and B intensities in the photographs were measured using ImageJ.^11 There are numerous ways to obtain R-G-B intensities even within ImageJ. You may choose to let students discover their own method. RGB Analysis: Sampled Region Procedure
    • Open photo in ImageJ (FIJI version^12 ).
    • Select area you would like to measure/sample. Ideally, this should be the same sized area for every sample!
    • Go to “Analyze” tab.
    • Select “Color Histogram”.
    • Obtain the data shown and record in a table and record in your notebook.
    • Repeat for each sample. 0.00 2.39 4.70 9.50 G2-LL G2-Orange MD Figure 4. At-home method with the second setup using disposable cuvettes and gravimetric solution prep. A stock yellow food dye with known concentration was used. Resulting photograph depicts yellow food dye-containing samples of various relative concentrations prepared at home using a white computer screen as a backlight. Figure 5. Screenshot of R-G-B photo of three sample objects being analyzed using ImageJ with selected area sampling.

Data Analysis Once data is obtained, students can explore colorimetric signals by plotting the raw R, G, and B intensities as a function of concentration, with or without prompt. From the data, students should be able to identify a concentration-dependent response and reflect on observed trends. Students should also be able to identify that the transmitted white light is composed of approximately equal intensities of R, G, and B, and determine what color is complementary to the color the sample appears/being absorbed. For example, chromophores that appear green do so because they absorb red light. Therefore, the amount of green light (G) relative to the total light transmitted measured (T) (given by, T = R + G + B) increases as a function of the concentration of dye. This observation reinforces visible-light absorption learning objectives covered in other parts of the course (i.e., lecture, readings, prelab assignments). Furthermore, to more clearly show changes relative to a blank, blank subtraction can be used. Thus, in combination, the concentration-dependent R, G, and B intensity data can be transformed by normalizing to T and subtracting the blank signal. This math is shown in Tables 4 and 5. For colorimetric analysis, average color intensities (i.e., B intensities for FD&C Blue 1 solutions) were plotted as a function of relative dye concentration. For absorbance-based analysis, complementary average color intensities (i.e., R intensities for green food dye solutions) were used to calculate absorbance (A) using equation S1. Where I is given by the R intensity for a given a sample, and I 0 is the R intensity for a blank. Various signal normalization and background subtraction methods were also calculated. Raw data for the results presented in Figures 2 and 6A are given in Tables 4 and 5. 𝐴 = −𝑙𝑜𝑔 ( ! !!^ )^ Equation 2 Table 4: R, G, and B Intensity Statistics (means and standard deviations, n = 3) of Green Dye Solutions Shown in Figure 2 and Plotted in Figure 6A* Rel. Conc. Green (ppm dye) 𝑥̅"^ 𝑠"^ 𝑥̅#^ 𝑠#^ 𝑥̅$^ 𝑠$^ 𝑥̅^ %^ 𝑠% 0 (Blank) 187.4 4.41 183.7 5.81 164.4 7.29 535.5 17. 107 167.2 8.47 178.6 7.25 163.6 8.95 509.4 24. 212 147.0 12.38 175.4 8.26 161.6 9.47 484.0 30. 415 117.0 6.13 171.9 11.28 130.5 9.97 419.4 27. 797 78.2 7.47 160.5 6.88 93.7 9.61 332.4 23. Table 5: Colorimetric and Absorbance Statistics (means and standard deviations, n = 3) of Green Dye Solutions Shown in Figure 2 and Plotted in Figure 6A* Rel. Conc. Green (ppm dye) Colorimetric Absorbance-Based 𝑥̅#/% 𝑥̅#/% Blank Subtracted 𝑠#/% 𝑥'̅," 𝑠'," 0 (Blank) 0.34 0.00 0.000 0.000 0. 107 0.35 0.01 0.003 0.050 0. 212 0.36 0.02 0.005 0.106 0. 415 0.41 0.07 0.003 0.205 0. 797 0.48 0.14 0.014 0.381 0. *Note:

  • R, G, and B represent red, green, and blue intensities, respectively.
  • T represents total intensity (R + G + B). A, R represents absorbance values calculated from red intensities.

straightforward and the concentrations of FD&C yellow # 5, or tartrazine, were determined to be 5.02, 3.31, and 6.44 ppm for G2-Lemon Lime, G2-Orange, and Mountain Dew, respectively.iii In conclusion, results demonstrate that smartphone cameras can be used to conduct colorimetric and absorbance-based analyses of food dye-containing samples at home. For all methods, smartphone colorimetric and absorbance-based analyses consistently exhibit a linear range over one order of magnitude- though this may potentially be improved by further adjusting the setup.

7. References (1) Knutson, C. M.; Hilker, A. P.; Tolstyka, Z. P.; Anderson, C. B.; Wilbon, P. A.; Mathers, R. T.; Wentzel, M. T.; Perkins, A. L.; Wissinger, J. E. Dyeing to Degrade: A Bioplastics Experiment for College and High School Classrooms. Journal of Chemical Education. 2019, 96 (11), 2565–2573. (2) Campos, A. R.; Knutson, C. M.; Knutson, T. R.; Mozzetti, A. R.; Haynes, C. L.; Penn, R. L. Quantifying Gold Nanoparticle Concentration in a Dietary Supplement Using Smartphone Colorimetry and Google Applications. Journal of Chemical Education. 2016, 93 (2), 318–321. (3) Kuntzleman, T. S.; Jacobson, E. C. Teaching Beer’s Law and Absorption Spectrophotometry with a Smart Phone: A Substantially Simplified Protocol. Journal of Chemical Education. 2016, 93 (7), 1249 – 1252. (4) Sharma, V.; McKone, H. T.; Markow, P. G. A Global Perspective on the History, Use, and Identification of Synthetic Food Dyes. Journal of Chemical Education. 2011, 88 (1), 24–28. (5) Mellon, M. G. Fisher Award Address: A Century of Colorimetry. Analytical Chemistry. 1952, 24 (6), 924–931. (6) Harvey, D. Spectroscopy Based on Absorption. In Analytical Chemistry 2.0 ; Creative Commons, 2019; p Ch. 10, Section 2. (7) Reusch, W. Visible and Ultraviolet Spectroscopy https://www2.chemistry.msu.edu/faculty/reusch/VirtTxtJml/Spectrpy/UV-Vis/spectrum.htm. (8) Fairchild, M. How Do Digital Cameras Detect Colors? http://www.rit- mcsl.org/fairchild/WhyIsColor/Questions/6-4.html. (9) Rathod, B. B.; Murthy, S.; Bandyopadhyay, S. Is This Solution Pink Enough? A Smartphone Tutor to Resolve the Eternal Question in Phenolphthalein-Based Titration. Journal of Chemical Education. 2019, 96 (3), 486–494. (10) Šafranko, S.; Živković, P.; Stanković, A.; Medvidović-Kosanović, M.; Széchenyi, A.; Jokić, S. Designing ColorX, Image Processing Software for Colorimetric Determination of Concentration, to Facilitate Students’ Investigation of Analytical Chemistry Concepts Using Digital Imaging Technology. Journal of Chemical Education. 2018, 96 (9), 1928–1937. (11) Schneider, C. A.; Rasband, W. S.; Eliceiri, K. W. NIH Image to ImageJ: 25 Years of Image Analysis. Nature Methods. 2012, 9 (7), 671–675. (12) Schindelin, J.; Arganda-Carreras, I.; Frise, E.; Kaynig, V.; Longair, M.; Pietzsch, T.; Preibisch, S.; Rueden, C.; Saalfeld, S.; Schmid, B.; Tinevez, J.-Y.; White, D. J.; Hartenstein, V.; Eliceiri, K.; Tomancak, P.; Cardona, A. Fiji: An Open-Source Platform for Biological-Image Analysis. Nature Methods. 2012, 9 (7), 676–682. Acknowledgements Thank you to Katie Cunningham, a hardworking quantitative analysis student that helped make this experiment development possible. iii (^) Note: the accuracy of these values was not validated by any other method or literature.