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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #318398

Research Project: DEVELOPMENT OF SENSING AND INSTRUMENTATION TECHNOLOGIES FOR FOOD SAFETY AND SANITATION INSPECTION IN FRESH FRUIT AND VEGETABLE PROCESSING

Location: Environmental Microbial & Food Safety Laboratory

Title: Spatially offset Raman spectroscopy based on a line-scan hyperspectral Raman system

Author
item Qin, Jianwei - Tony
item Chao, Kuanglin - Kevin Chao
item Kim, Moon

Submitted to: ASABE Annual International Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 7/2/2015
Publication Date: 7/14/2015
Citation: Qin, J., Chao, K., Kim, M.S. 2015. Spatially offset Raman spectroscopy based on a line-scan hyperspectral Raman system. ASABE Paper No. 152190172. American Society of Agricultural Biologists and Engineers, St. Joseph, MI.

Interpretive Summary: Spatially offset Raman spectroscopy (SORS) was developed for noninvasively acquiring internal subsurface information of a sample by detecting Raman signals at a series of surface positions offset from the point of laser excitation. As source-detector distance increases, the contribution of Raman signals from deeper internal layers gradually outweighs that from the top layer. Current SORS measurement methods generally use a single fiber optic probe that is moved in steps away from the excitation point to acquire the series of Raman spectra, or use an array of fiber optic probes arranged at fixed intervals along a predetermined maximum distance from the excitation source. This study presents a new method that provides options for greater flexibility, precision, and efficiency for carrying out SORS measurements by using a line-scan macro-scale hyperspectral Raman imaging system. The line-scan approach uses a single scan to simultaneously collect a linear series of Raman spectra with options for a broad offset range (distance from excitation) and narrow offset intervals (the measurements of the series can be very close together if desired). Using the line-scan hyperspectral Raman imaging system allows for greater flexibility in the data while simplifying and shortening the collection process, compared to movement of single probes or using fixed-situation probe arrays. Spatial profiles extracted from the Raman scattering images can be utilized to determine the optimal spatial range used in SORS data analysis. This new method of SORS measurement was demonstrated by measuring Raman scattering signals of melamine powder placed underneath layers of butter between 1 and 10 mm thick. The SORS measurement technique developed in this study shows promise for use in applications for subsurface food safety and quality inspection. This information should be useful for agencies responsible for inspecting and interdicting adulterated or contaminated food stuffs.

Technical Abstract: Spatially offset Raman spectroscopy (SORS) is a technique that can obtain subsurface layered information by collecting Raman spectra from a series of surface positions laterally offset from the excitation laser. The current methods of SORS measurement are typically either slow due to mechanical movement of a single fiber probe, or restricted in the possible offset range and interval that can be selected using a fiber probe array. This study proposes a new method to conduct SORS measurement based on a newly-developed line-scan hyperspectral Raman imaging system. A 785 nm point laser was used as an excitation source. A detection module consisting of an imaging spectrograph and a CCD camera was used to acquire line-shape SORS data in a spectral region of -592 to 3015 cm-1. Using a single scan, the system allowed simultaneous collection of a series of Raman spectra in a broad offset range (e.g., 0–36 mm in two sides of the incident laser) with a narrow interval (e.g., 0.07 mm). Four layered samples were created by placing butter slices with thicknesses of 1, 4, 7, and 10 mm on melamine powder, providing different individual Raman characteristics to test the line-scan SORS technique. Self-modeling mixture analysis was used to analyze the SORS data. Raman spectra from butter and melamine were successfully separated and retrieved for all four layered butter-on-melamine samples. The line-scan SORS measurement technique provides a flexible and efficient method for subsurface evaluation with potential application for food safety and quality inspection.