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Proceedings Paper

Design of smartphone-based spectrometer to assess fresh meat color
Author(s): Youngkee Jung; Hyun-Wook Kim; Yuan H. Brad Kim; Euiwon Bae
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Paper Abstract

Based on its integrated camera, new optical attachment, and inherent computing power, we propose an instrument design and validation that can potentially provide an objective and accurate method to determine surface meat color change and myoglobin redox forms using a smartphone-based spectrometer. System is designed to be used as a reflection spectrometer which mimics the conventional spectrometry commonly used for meat color assessment. We utilize a 3D printing technique to make an optical cradle which holds all of the optical components for light collection, collimation, dispersion, and a suitable chamber. A light, which reflects a sample, enters a pinhole and is subsequently collimated by a convex lens. A diffraction grating spreads the wavelength over the camera’s pixels to display a high resolution of spectrum. Pixel values in the smartphone image are translated to calibrate the wavelength values through three laser pointers which have different wavelength; 405, 532, 650 nm. Using an in-house app, the camera images are converted into a spectrum in the visible wavelength range based on the exterior light source. A controlled experiment simulating the refrigeration and shelving of the meat has been conducted and the results showed the capability to accurately measure the color change in quantitative and spectroscopic manner. We expect that this technology can be adapted to any smartphone and used to conduct a field-deployable color spectrum assay as a more practical application tool for various food sectors.

Paper Details

Date Published: 17 February 2017
PDF: 8 pages
Proc. SPIE 10072, Optical Diagnostics and Sensing XVII: Toward Point-of-Care Diagnostics, 1007213 (17 February 2017); doi: 10.1117/12.2253414
Show Author Affiliations
Youngkee Jung, Purdue Univ. (United States)
Hyun-Wook Kim, Purdue Univ. (United States)
Yuan H. Brad Kim, Purdue Univ. (United States)
Euiwon Bae, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 10072:
Optical Diagnostics and Sensing XVII: Toward Point-of-Care Diagnostics
Gerard L. Coté, Editor(s)

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