Literature DB >> 27879171

Detection and quantification of adulterants in milk powder using a high-throughput Raman chemical imaging technique.

Jianwei Qin1, Moon S Kim1, Kuanglin Chao1, Sagar Dhakal1, Hoonsoo Lee1, Byoung-Kwan Cho2, Changyeun Mo3.   

Abstract

Milk is a vulnerable target for economically motivated adulteration. In this study, a line-scan high-throughput Raman imaging system was used to authenticate milk powder. A 5 W 785 nm line laser (240 mm long and 1 mm wide) was used as a Raman excitation source. The system was used to acquire hyperspectral Raman images in a wave number range of 103-2881 cm-1 from the skimmed milk powder mixed with two nitrogen-rich adulterants (i.e., melamine and urea) at eight concentrations (w/w) from 50 to 10,000 ppm. The powdered samples were put in sample holders with a surface area of 150 ×100 mm and a depth of 2 mm for push-broom image acquisition. Varying fluorescence signals from the milk powder were removed using a correction method based on adaptive iteratively reweighted penalised least squares. Image classifications were conducted using a simple thresholding method applied to single-band fluorescence-corrected images at unique Raman peaks selected for melamine (673 cm-1) and urea (1009 cm-1). Chemical images were generated by combining individual binary images of melamine and urea to visualise identification, spatial distribution and morphological features of the two adulterant particles in the milk powder. Limits of detection for both melamine and urea were estimated in the order of 50 ppm. High correlations were found between pixel concentrations (i.e., percentages of the adulterant pixels in the chemical images) and mass concentrations of melamine and urea, demonstrating the potential of the high-throughput Raman chemical imaging method for the detection and quantification of adulterants in the milk powder.

Entities:  

Keywords:  Raman spectroscopy; adulteration; chemical imaging; food authentication; food safety; melamine; milk powder; urea

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Year:  2016        PMID: 27879171     DOI: 10.1080/19440049.2016.1263880

Source DB:  PubMed          Journal:  Food Addit Contam Part A Chem Anal Control Expo Risk Assess        ISSN: 1944-0057


  2 in total

1.  Calibration and testing of a Raman hyperspectral imaging system to reveal powdered food adulteration.

Authors:  Santosh Lohumi; Hoonsoo Lee; Moon S Kim; Jianwei Qin; Lalit Mohan Kandpal; Hyungjin Bae; Anisur Rahman; Byoung-Kwan Cho
Journal:  PLoS One       Date:  2018-04-30       Impact factor: 3.240

Review 2.  Applications of Fluorescence Spectroscopy, RGB- and MultiSpectral Imaging for Quality Determinations of White Meat: A Review.

Authors:  Ke-Jun Fan; Wen-Hao Su
Journal:  Biosensors (Basel)       Date:  2022-01-28
  2 in total

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