Please use this identifier to cite or link to this item:
|Type:||Artigo de periódico|
|Title:||Development And Validation Of Multivariate Models Employing Near-infrared Spectroscopy For Eucalyptus Wood Characteristics Estimations [desenvolvimento E Validação De Modelos Multivariados Empregando Espectroscopia No Infravermelho Próximo Para Estimativa De Características Da Madeira De Eucalipto Set]|
|Abstract:||Near-Infrared (NIR) Spectroscopy has been employed in the development of multivariate models in order to estimate the total lignin content, basic density and extractives in ethanol/toluene in eucalyptus wood sawdust. The multivariate evaluation made by means of Principal Components Analysis (PCA), of NIR spectra obtained for 926 wood samples, shows that the NIR spectroscopy recognizes the different genetic materials. This distinction among the spectra of several genetic materials must be considered when quantitative global multivariate models are developed. The Partial Least Square Regression (PLS) models to predict total lignin, basic density and extractive content in eucalyptus wood were developed and validated according to ASTM 1655-05. The results of the external validation, expressed by the Standard Error of Prediction (SEP) and by the correlation coefficient (r) between the results estimated by NIR spectroscopy and those obtained by the standard methods, carried out with additional 160 samples not employed in the modeling stage, were: Total Lignin, SEP = 1.2%, r = 0.800; Basic Density, SEP = 26 kg m-3, r = 0.930; Extractives, SEP = 0.38%, r = 0.864. The models were considered to be satisfactory according to ASTM 1655-05.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.