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Proceedings Paper

Development of a Raman chemical image detection algorithm for authenticating dry milk
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Paper Abstract

This research developed a Raman chemical imaging method for detecting multiple adulterants in skim milk powder. Ammonium sulfate, dicyandiamide, melamine, and urea were mixed into the milk powder as chemical adulterants in the concentration range of 0.1–5.0%. A Raman imaging system using a 785-nm laser acquired hyperspectral images in the wavenumber range of 102–2538 cm–1 for a 25×25 mm2 area of each mixture. A polynomial curve-fitting method was used to correct fluorescence background in the Raman images. An image classification method was developed based on single-band fluorescence-free images at unique Raman peaks of the adulterants. Raman chemical images were created to visualize identification and distribution of the multiple adulterant particles in the milk powder. Linear relationship was found between adulterant pixel number and adulterant concentration, demonstrating the potential of the Raman chemical imaging for quantitative analysis of the adulterants in the milk powder.

Paper Details

Date Published: 29 May 2013
PDF: 10 pages
Proc. SPIE 8721, Sensing for Agriculture and Food Quality and Safety V, 872102 (29 May 2013); doi: 10.1117/12.2015258
Show Author Affiliations
Jianwei Qin, Agricultural Research Service (United States)
Kuanglin Chao, Agricultural Research Service (United States)
Moon S. Kim, Agricultural Research Service (United States)


Published in SPIE Proceedings Vol. 8721:
Sensing for Agriculture and Food Quality and Safety V
Moon S. Kim; Shu-I Tu; Kuanglin Chao, Editor(s)

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