Scientific Research and Essays

  • Abbreviation: Sci. Res. Essays
  • Language: English
  • ISSN: 1992-2248
  • DOI: 10.5897/SRE
  • Start Year: 2006
  • Published Articles: 2754

Full Length Research Paper

Estimation of Pinus brutia Ten. wood density from Fourier Transform Infrared (FTIR) spectroscopic bands by Artificial Neural Network (ANN)

Bilgin Guller* and Samim Yasar  
  Department of Forest Products Engineering, Faculty of Forestry, Suleyman Demirel University, Isparta-32260, Turkey.
Email: [email protected]

  •  Accepted: 03 June 2010
  •  Published: 04 July 2010

Abstract

In this study, the rapid Fourier transform infrared (FTIR) spectroscopic method was used to indirectly measure the wood density of Pinus brutia Ten. samples. A model was constructed to relate FTIR data to wood density determined by laboratory analysis, through the application of artificial neural network (ANN) modelling approach to a set of calibration observations. The proposed model with two hidden neurons performed very good to estimate the wood density with high correlation R2 values of 0.9833 for training and 0.9814 for testing, respectively, and with a low prediction error of 0.71% in the validation. This analysis showed that ANN coupled with FTIR spectroscopy could be used to accurately predict the density of wood samples.

 

Key words: Wood density, Fourier transform infrared (FTIR) spectroscopy, Artificial neural network (ANN), Pinus brutia.