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Indicators02:39

Indicators

Certain organic substances change color in dilute solution when the hydronium ion concentration reaches a particular value. For example, phenolphthalein is a colorless substance in any aqueous solution with a hydronium ion concentration greater than 5.0 × 10−9 M (pH < 8.3). In more basic solutions where the hydronium ion concentration is less than 5.0 × 10−9 M (pH > 8.3), it is red or pink. Substances such as phenolphthalein, which can be used to determine the pH of a solution, are called...

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Quantification of Colorimetric Data for Paper-Based Analytical Devices.

Yoshiki Soda1, Eric Bakker1

  • 1Department of Inorganic and Analytical Chemistry , University of Geneva , Quai Ernest-Ansermet 30 , CH-1211 Geneva , Switzerland.

ACS Sensors
|November 21, 2019
PubMed
Summary
This summary is machine-generated.

Image analysis for colorimetric measurements on paper-based analytical devices (PADs) can provide quantitative concentration data. Removing gamma correction enables accurate absorbance values, crucial for reliable chemical and biological assays.

Keywords:
RGB analysisbackground light correctioncolorimetrygamma correctionpaper-based analytical devicesscannersmartphone analysis

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Area of Science:

  • Analytical Chemistry
  • Spectroscopy
  • Biomedical Engineering

Background:

  • Colorimetric measurements using image analysis (RGB/HSV data) are common in optical indicator assays and paper-based analytical devices (PADs).
  • Quantitative correlation between color data and concentration is often overlooked in PAD research, hindering their analytical potential and understanding of paper-based reactions.
  • Traditional spectrophotometry is the benchmark for quantitative colorimetric analysis.

Purpose of the Study:

  • To discuss the computation of image color data into colorimetric absorbance values.
  • To demonstrate the linear correlation between computed absorbance and dye concentration.
  • To compare image-based colorimetry with traditional spectrophotometry for analytical applications.

Main Methods:

  • Utilized image analysis to obtain RGB or HSV data from colorimetric assays.
  • Removed gamma correction from image data to compute absorbance values.
  • Employed Thioflavin T (ThT), Neutral Red (NR), and Orange IV as model dye systems.
  • Performed absorbance measurements in solution and reflectance measurements on paper spots.
  • Compared image data-derived absorbance with traditional spectrophotometry.

Main Results:

  • Absorbance measurements in solution showed good correlation with image data when gamma correction was removed, adhering to Beer's Law.
  • The developed approach allowed for correction of color cast and variable background, improving field measurement accuracy.
  • Reflectance measurements on paper color spots also demonstrated quantitative correlation between spectroscopy and imaging devices.
  • Deviations from Beer's Law were observed on paper and attributed to dye-substrate interactions.

Conclusions:

  • Image color data can be reliably converted to quantitative absorbance values, comparable to spectrophotometry.
  • Removing gamma correction is essential for accurate colorimetric quantitation from images.
  • This method enhances the analytical capabilities of paper-based devices and aids in understanding paper-based chemical reactions.