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

Qin, Jianwei,Kim, Moon S.,Chao, Kuanglin,Dhakal, Sagar,Lee, Hoonsoo,Cho, Byoung-Kwan,Mo, Changyeun Informa UK (TaylorFrancis) 2017 Food additives & contaminants. Part A. Chemistry, Vol.34 No.2

<P>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 5W 785nm line laser (240mm long and 1mm wide) was used as a Raman excitation source. The system was used to acquire hyperspectral Raman images in a wave number range of 103-2881cm(-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 150x100mm and a depth of 2mm 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 (673cm(-1)) and urea (1009cm(-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.</P>

Quantitative Detection of Benzoyl Peroxide in Wheat Flour Using Line-Scan Macroscale Raman Chemical Imaging

Qin, Jianwei,Kim, Moon S.,Chao, Kuanglin,Gonzalez, Maria,Cho, Byoung-Kwan Society for Applied Spectroscopy 2017 Applied spectroscopy Vol.71 No.11

<P>A high-throughput Raman chemical imaging method was developed for direct inspection of benzoyl peroxide (BPO) mixed in wheat flour. A 5W, 785nm line laser (240mm long and 1mm wide) was used as a Raman excitation source in a push-broom Raman imaging system. Hyperspectral Raman images were collected in a wavenumber range of 103-2881cm(-1) from dry wheat flour mixed with BPO at eight concentrations (w/w) from 50 to 6400ppm. A sample holder with a sampling volume of 150x100x2mm(3) was used to present a thin layer (2mm thick) of the powdered sample for line-scan image acquisition with a spatial resolution of 0.2mm. A baseline correction method based on adaptive iteratively reweighted penalized least squares was used to remove the fluctuating fluorescence signals from the wheat flour. To isolate BPO particles from the flour background, a simple thresholding method was applied to the single-band fluorescence-free images at a unique Raman peak wavenumber (i.e., 1001cm(-1)) preselected for the BPO detection. Chemical images were created to detect and map the BPO particles. Limit of detection for the BPO was estimated in the order of 50ppm, which is on the same level with regulatory standards. Pixel concentrations were calculated from the percentages of the BPO pixels in the chemical images. High correlation was found between the pixel concentrations and the mass concentrations of the BPO, indicating that the Raman chemical imaging method can be used for quantitative detection of the BPO mixed in the wheat flour.</P>

Subsurface inspection of food safety and quality using line-scan spatially offset Raman spectroscopy technique

Qin, Jianwei,Kim, Moon S.,Chao, Kuanglin,Schmidt, Walter F.,Dhakal, Sagar,Cho, Byoung-Kwan,Peng, Yankun,Huang, Min Elsevier 2017 Food Control Vol.75 No.-

<P>Subsurface inspection of food and agricultural products is challenging for optical-based sensing techniques due to complex interactions between light and heterogeneous or layered samples. In this study, a method for subsurface food inspection was presented based on a newly developed line-scan spatially offset Raman spectroscopy (SORS) technique. A 785 nm point laser was used as a Raman excitation source. The line-shape SORS data from the sample was collected in a wavenumber range of 0-2815 cm(-1) using a detection module consisting of an imaging spectrograph and a CCD camera. Two layered samples, one by placing a 1 mm thick plastic sheet cut from original container on top of cane sugar and the other by placing a 5 mm thick carrot slice on top of melamine powder, were created to test the subsurface food inspection method. For each sample, a whole set of SORS data was acquired using one CCD exposure in an offset range of 0-36 mm (two sides of the incident laser point) with a spatial interval of 0.07 mm. Raman spectra from the cane sugar under the plastic sheet and the melamine powder under the carrot slice were successfully resolved using self-modeling mixture analysis (SMA) algorithms, demonstrating the potential of the technique for authenticating foods and ingredients through packaging and evaluating internal food safety and quality attributes. The line-scan SORS measurement technique provides a rapid and nondestructive method for subsurface inspection of food safety and quality. Published by Elsevier Ltd.</P>

Raman Chemical Imaging Technology for Food and Agricultural Applications

Qin, Jianwei,Kim, Moon S.,Chao, Kuanglin,Cho, Byoung-Kwan Korean Society for Agricultural Machinery 2017 바이오시스템공학 Vol.42 No.3

Purpose: This paper presents Raman chemical imaging technology for inspecting food and agricultural products. Methods The paper puts emphasis on introducing and demonstrating Raman imaging techniques for practical uses in food analysis. Results & Conclusions: The main topics include Raman scattering principles, Raman spectroscopy measurement techniques (e.g., backscattering Raman spectroscopy, transmission Raman spectroscopy, and spatially offset Raman spectroscopy), Raman image acquisition methods (i.e., point-scan, line-scan, and area-scan methods), Raman imaging instruments (e.g., excitation sources, wavelength separation devices, detectors, imaging systems, and calibration methods), and Raman image processing and analysis techniques (e.g., fluorescence correction, mixture analysis, target identification, spatial mapping, and quantitative analysis). Raman chemical imaging applications for food safety and quality evaluation are also reviewed.

Raman Chemical Imaging Technology for Food and Agricultural Applications

( Jianwei Qin ),( Moon S. Kim ),( Kuanglin Chao ),( Byoung-kwan Cho ) 한국농업기계학회 2017 바이오시스템공학 Vol.42 No.3

Purpose: This paper presents Raman chemical imaging technology for inspecting food and agricultural products. Methods The paper puts emphasis on introducing and demonstrating Raman imaging techniques for practical uses in food analysis. Results & Conclusions: The main topics include Raman scattering principles, Raman spectroscopy measurement techniques (e.g., backscattering Raman spectroscopy, transmission Raman spectroscopy, and spatially offset Raman spectroscopy), Raman image acquisition methods (i.e., point-scan, line-scan, and area-scan methods), Raman imaging instruments (e.g., excitation sources, wavelength separation devices, detectors, imaging systems, and calibration methods), and Raman image processing and analysis techniques (e.g., fluorescence correction, mixture analysis, target identification, spatial mapping, and quantitative analysis). Raman chemical imaging applications for food safety and quality evaluation are also reviewed.

Evaluation of SERS Nanoparticles to Detect Bacillus cereus and Bacillus thuringiensis

홍지화,Jianwei Qin,Jo Ann S. Van Kessel,오미래,Sagar Dhakal,이훈수,황찬송,Diane E. Chan,김동호,조현정,Moon S. Kim 한국농업기계학회 2018 바이오시스템공학 Vol.43 No.4

Purpose: This research evaluated five types of nanoparticles to develop a surface-enhanced Raman spectroscopy (SERS) method for the rapid detection of two Bacillus species (Bacillus cereus and Bacillus thuringiensis) that are commonly found on fresh produce, which can cause food poisoning. Methods: Bacterial concentrations were adjusted to a constant turbidity, and a total of 30 μL of each Bacillus cell suspension was prepared for each nanoparticle. A point-scan Raman system with laser light source of wavelength 785 nm was used to obtain SERS data. Results: There was no qualitative difference in the SERS data of B. cereus and B. thuringiensis for any of the five nanoparticles. Three gold nanoparticles, stabilized in either citrate buffer or ethanol, showed subtle differences in Raman intensities of two Bacillus species at 877.7 cm-1. Conclusions: Among the three types of nanoparticles, the gold nanoparticles stabilized in citrate buffer showed the lowest standard deviation, followed by gold nanoparticles stabilized in ethanol. This result supports the potential application of gold nanoparticles for SERS-based detection of B. cereus and B. thuringiensis.

Evaluation of SERS Nanoparticles to Detect Bacillus cereus and Bacillus thuringiensis

( Jeehwa Hong ),( Jianwei Qin ),( Jo Ann S. Van Kessel ),( Mirae Oh ),( Sagar Dhakal ),( Hoonsoo Lee ),( Chansong Hwang ),( Diane E. Chan ),( Dongho Kim ),( Hyunjeong Cho ),( Moon S. Kim ) 한국농업기계학회 2018 바이오시스템공학 Vol.43 No.4

Purpose: This research evaluated five types of nanoparticles to develop a surface-enhanced Raman spectroscopy (SERS) method for the rapid detection of two Bacillus species (Bacillus cereus and Bacillus thuringiensis) that are commonly found on fresh produce, which can cause food poisoning. Methods: Bacterial concentrations were adjusted to a constant turbidity, and a total of 30 μL of each Bacillus cell suspension was prepared for each nanoparticle. A point-scan Raman system with laser light source of wavelength 785 nm was used to obtain SERS data. Results: There was no qualitative difference in the SERS data of B. cereus and B. thuringiensis for any of the five nanoparticles. Three gold nanoparticles, stabilized in either citrate buffer or ethanol, showed subtle differences in Raman intensities of two Bacillus species at 877.7 cm-1. Conclusions: Among the three types of nanoparticles, the gold nanoparticles stabilized in citrate buffer showed the lowest standard deviation, followed by gold nanoparticles stabilized in ethanol. This result supports the potential application of gold nanoparticles for SERS-based detection of B. cereus and B. thuringiensis.

Evaluation of SERS Nanoparticles to Detect Bacillus cereus and Bacillus thuringiensis

Hong, Jeehwa,Qin, Jianwei,Van Kessel, Jo Ann S.,Oh, Mirae,Dhakal, Sagar,Lee, Hoonsoo,Hwang, Chansong,Chan, Diane E.,Kim, Dongho,Cho, Hyunjeong,Kim, Moon S. Korean Society for Agricultural Machinery 2018 바이오시스템공학 Vol.43 No.4

Purpose: This research evaluated five types of nanoparticles to develop a surface-enhanced Raman spectroscopy (SERS) method for the rapid detection of two Bacillus species (Bacillus cereus and Bacillus thuringiensis) that are commonly found on fresh produce, which can cause food poisoning. Methods: Bacterial concentrations were adjusted to a constant turbidity, and a total of $30{\mu}L$ of each Bacillus cell suspension was prepared for each nanoparticle. A point-scan Raman system with laser light source of wavelength 785 nm was used to obtain SERS data. Results: There was no qualitative difference in the SERS data of B. cereus and B. thuringiensis for any of the five nanoparticles. Three gold nanoparticles, stabilized in either citrate buffer or ethanol, showed subtle differences in Raman intensities of two Bacillus species at $877.7cm^{-1}$. Conclusions: Among the three types of nanoparticles, the gold nanoparticles stabilized in citrate buffer showed the lowest standard deviation, followed by gold nanoparticles stabilized in ethanol. This result supports the potential application of gold nanoparticles for SERS-based detection of B. cereus and B. thuringiensis.

Raman hyperspectral imaging and spectral similarity analysis for quantitative detection of multiple adulterants in wheat flour

Lohumi, Santosh,Lee, Hoonsoo,Kim, Moon S.,Qin, Jianwei,Cho, Byoung-Kwan Elsevier 2019 Biosystems engineering Vol.181 No.-

<P>Recent food safety incidents and public health concerns related to food adulteration drive the need for fast, sensitive, and reliable methods for the detection of food hazards and adulteration. Although Raman microscopy imaging has been used for quality and authenticity analysis of food products previously, the application of line-scan Raman imaging has emerged only recently. Here, we assess the applicability of line-scan Raman hyperspectral imaging (RHI) for simultaneous detection of three potential chemical adulterants in wheat flour (0.05–1.5% w/w). RHI of wheat flour samples were collected (0.2-mm step size, 1 s exposure time) in an aluminum sample holder using a 785-nm line laser to generate Raman scattering. Spectral angle mapping (SAM) was applied to the preprocessed data to distinguish adulterants' pixels from the flour background using the pure endmember as input extracted by independent component analysis. SAM images for each adulterant were converted to binary images to effectively visualise and quantitatively detect the adulterant pixels in wheat flour. The pixel-based calculated proportions of adulterants in wheat flour agreed with the concentrations added. The reproducibility of the developed technique was assessed for same samples measured at different times and the results demonstrated that RHI in combination with SAM provided a novel, elegant tool with potential for noninvasive quality and authenticity analyses of powdered foods.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Line-scan Raman imaging was used for detection of adulterants in wheat flour. </LI> <LI> Independent component analysis was used for endmember selection. </LI> <LI> SAM modeling of corrected data allows for quantification of adulterants. </LI> <LI> The two major advantages of Raman imaging are good reproducibility and fast. </LI> </UL> </P>

Through-packaging analysis of butter adulteration using line-scan spatially offset Raman spectroscopy

Lohumi, Santosh,Lee, Hoonsoo,Kim, Moon S.,Qin, Jianwei,Cho, Byoung-Kwan Springer-Verlag 2018 Analytical and Bioanalytical Chemistry Vol.410 No.22