The Relationship between near Infrared Spectroscopy and Surface Color of Eight Rosewoods

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Abstract:

Rosewood is a kind of precious wood. Accurate wood species identification is a time consuming task for highly trained human experts. The development of cost effective techniques for automatic wood identification is a desirable goal. Wood color is one of the crucial factors to identify wood species. The color parameters (CIE L*, a* and b*) of eight rosewoods and the relationship between near infrared spectroscopy (NIR) and the color parameters were investigated in this paper. The results showed there was significant correlation between near infrared spectroscopy and color parameters. The correlation coefficients between laboratory-measured and NIR-predicted L*, a* and b* values were 0.93~0.99. The results will be helpful to develop a new method of rosewood identification through near infrared spectroscopy coupled with multivariate data analysis.

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Periodical:

Advanced Materials Research (Volumes 479-481)

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1772-1776

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February 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Osborne B G, Fearn T. Near infrared spectroscopy in food analysis. Longman, UK, (1998)

Google Scholar

[2] Faughey G J, Sharma H S S. A preliminary evaluation of near infrared spectroscopy for assessing physical and chemical characteristics of flax fibre. Journal of Near Infrared Spectroscopy, 2000,8(1):61-69

DOI: 10.1255/jnirs.265

Google Scholar

[3] Conway J M, Norris K H, Bodwell C E. A new method for the estimation of body composition: infrared interactance. American Journal of Clinical Nutrition, 1984, 40(6):1123-1130

DOI: 10.1093/ajcn/40.6.1123

Google Scholar

[4] Yano T, Matsushige H, Suehara K -I et al. Measurement of the concentrations of glucose and lactic acid in peritoneal dialysis solutions using near-infrared spectroscopy. Journal of Bioscience and Bioengineering, 2000, 90(5): 540-544

DOI: 10.1016/s1389-1723(01)80037-2

Google Scholar

[5] Batten G D. An appreciation of the contribution of NIR to agriculture.Journal of Near Infrared Spectroscopy, 1998,6(1):105-114

DOI: 10.1255/jnirs.127

Google Scholar

[6] Wright J A, Birkett M D, Gambino M J T. Prediction of pulp yield and cellulose content from samples using near infrared reflectance spectroscopy. TAPPI Journal,1990, 73(8):164-166

Google Scholar

[7] Tsuchikawa S. A review of recent near infrared research for wood and paper. Applied Spectroscopy Reviews, 2007, 42: 43-71.

DOI: 10.1080/05704920601036707

Google Scholar

[8] Chi-Leung So, Brian K. Via, Leslie H. Groom, et al. Near infrared spectroscopy in the forest products industry. Forest Products Journal, 2004,54(3):6-16

Google Scholar

[9] Tsuchikawa S, Inoue K, Noma J. Application of near-infrared spectroscopy to wood discrimination. Journal of Wood Science, 2003,49(1):29-35

DOI: 10.1007/s100860300005

Google Scholar

[10] Per Otto Flæte, Erlend Ystrøm Haartveit, Kjell Vadla. As a Near infrared spectroscopy with multivariate statistical modeling as a tool for differentiation of wood from spruce species with similar appearance. New Zealand Journal of Forestry Science, 2006, 36(2/3): 382–392

Google Scholar

[11] Satoru Tsuchikawa, Kaori Yamato, Kinuyo Inoue. Discriminant analysis of wood-based materials using near-infrared spectroscopy[J], Journal of Wood Science, 2003, 49:275–280

DOI: 10.1007/s10086-002-0471-0

Google Scholar