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Proceedings Paper

In-situ identification of meat from different animal species by shifted excitation Raman difference spectroscopy
Author(s): Kay Sowoidnich; Heinz-Detlef Kronfeldt
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Paper Abstract

The identification of food products and the detection of adulteration are of global interest for food safety and quality control. We present a non-invasive in-situ approach for the differentiation of meat from selected animal species using microsystem diode laser based shifted excitation Raman difference spectroscopy (SERDS) at 671 nm and 785 nm. In that way, the fingerprint Raman spectra can be used for identification without a disturbing fluorescence background masking Raman signals often occurring in the investigation of biological samples. Two miniaturized SERDS measurement heads including the diode laser and all optical elements are fiber-optically coupled to compact laboratory spectrometers. To realize two slightly shifted excitation wavelengths necessary for SERDS the 671 nm laser (spectral shift: 0.7 nm, optical power: 50 mW) comprises two separate laser cavities each with a volume Bragg grating for frequency selection whereas the 785 nm light source (spectral shift: 0.5 nm, optical power: 110 mW) is a distributed feedback laser. For our investigations we chose the most consumed meat types in the US and Europe, i.e. chicken and turkey as white meat as well as pork and beef as red meat species. The applied optical powers were sufficient to detect meat Raman spectra with integration times of 10 seconds pointing out the ability for a rapid discrimination of meat samples. Principal components analysis was applied to the SERDS spectra to reveal spectral differences between the animals suitable for their identification. The results will be discussed with respect to specific characteristics of the analyzed meat species.

Paper Details

Date Published: 5 May 2012
PDF: 8 pages
Proc. SPIE 8369, Sensing for Agriculture and Food Quality and Safety IV, 83690J (5 May 2012); doi: 10.1117/12.918259
Show Author Affiliations
Kay Sowoidnich, Technische Univ. Berlin (Germany)
Heinz-Detlef Kronfeldt, Technische Univ. Berlin (Germany)


Published in SPIE Proceedings Vol. 8369:
Sensing for Agriculture and Food Quality and Safety IV
Moon S. Kim; Shu-I Tu; Kuanglin Chao, Editor(s)

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