Click on “Download PDF” for the PDF version or on the title for the HTML version. If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options. Spatially Offset Raman Spectroscopy based on a Line-Scan Hyperspectral Raman SystemPublished by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org Citation: 2015 ASABE Annual International Meeting 152190172.(doi:10.13031/aim.20152190172)Authors: Jianwei Qin, Moon S Kim, Moon S. Kim Keywords: Butter; Food safety; Melamine; Raman spectroscopy; SORS; Subsurface detection. 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. Currently optical fiber probes are used as major tools in SORS measurement, which are either slow (single fiber probe with mechanical movement) or restricted in selecting offset range and interval (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, which has potential to be used for food safety and quality inspection. (Download PDF) (Export to EndNotes)
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