Wide area illumination Raman scheme for simple and nondestructive discrimination of seawater cultured pearls
- Authors
- Park, Seok Chan; Kim, Minjung; Park, Jimin; Chung, Hoeil; Kim, Hea Yeon
- Issue Date
- Dec-2009
- Publisher
- WILEY
- Keywords
- pearl discrimination; aragonite; wide area illumination Raman scheme; discriminant partial least squares
- Citation
- JOURNAL OF RAMAN SPECTROSCOPY, v.40, no.12, pp.2187 - 2192
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOURNAL OF RAMAN SPECTROSCOPY
- Volume
- 40
- Number
- 12
- Start Page
- 2187
- End Page
- 2192
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/175748
- DOI
- 10.1002/jrs.2401
- ISSN
- 0377-0486
- Abstract
- Raman spectroscopy, along with discriminant partial least squares (PLS), was successfully used to discriminate among three different groups of cultured pearls (fresh water, Akoya and South seawater). The discrimination between Alkoya and South seawater pearls using XRF (X-ray fluorescence), one of the most frequently adopted analytical methods in pearl analysis, has been especially difficult owing to their similar mineral compositions. The selective Raman features helped in effectively discriminating between these two pearl groups. The difference in the intensities of the CaCO3 bands of Alkoya and South seawater pearls provided a valuable clue. Along with the selective Raman feature, a reproducible Raman spectral collection achieved using a wide area illumination (WAI) scheme played an important role in the determination of the pearl groups, although the pearls were hard-surfaced, round, solid samples of different sizes and surface shapes. Unwanted spectral variation originating from sensitivity to sample placement relative to the focal plane and from unsuccessful sample representation due to the probing of a localized area, factors that could possibly deteriorate Raman reproducibility, were substantially lessened using the WAI scheme. ATR (attenuated total reflection) IR spectroscopy requiring direct contact with the pearl could be inadequate for discrimination or classification where large numbers of repeating and reproducible measurements are required.
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