Nonlinear multivariate modeling of strand mechanical properties with near-infrared spectroscopy

Abstract

The purpose of this research was to determine if nonlinear calibrations of near-infrared spectra could improve the prediction of strand mechanical properties. Strands similar in dimension to strands utilized in an oriented strand board composite process were prepared and tested for mechanical properties in three-point bending and then calibrated to near-infrared reflectance spectroscopy. It was found that an additional 7% to 16% of the variation in mechanical properties could be accounted for when second-and third-order terms were applied. Interpretation of models identified the magnitude of importance that various wood polymers play on mechanical properties and this interpretation was validated through wet chemistry. This work is significant because it demonstrates the potential of using near-infrared spectroscopy to monitor shifts in strand mechanical properties prior to wood composite manufacture and it helps to provide the fundamental relationship between near-infrared models, wood chemistry, and the prediction of mechanical properties.Keywords: near-infrared, NIR, spectroscopy, strand, flake, biomass, composite, chemistry, strength, stiffness, elasticity résumé Le but de cette recherche est de déterminer si l' étalonnage non-linéaire de spectres proche infrarouge peut améliorer la prédic-tion des propriétés mécaniques des copeaux de bois. Des copeaux de dimensions similaires à ceux utilisés dans le processus de fabrication des panneaux à copeaux orientés ont été préparés et leurs propriétés mécaniques testées en flexion à trois points puis étalonnées au moyen de la spectrométrie proche infrarouge en réflectance. Il a été trouvé que 7% à 16% de variation additionnelle des propriétés mécaniques pouvaient être prises en compte en appliquant des termes du deuxième et troisième degré. L'interprétation des modèles a permis d'identifier l'importance que différents polymères du bois jouent sur les propriétés mécaniques et cette interprétation a été validée au moyen de tests chimiques. Ce travail est important parce qu'il démontre le potentiel de l'utilisation de la spectrométrie proche infrarouge pour contrôler les changements dans les propriétés mécaniques des copeaux avant la fabrication des panneaux et aide à fournir une relation fondamentale entre les modèles proche infrarouge, la chimie du bois et la prédiction des propriétés mécaniques.

Monitoring the Chemistry and Monosaccharide Ratio of Eucalyptus Dunnii Wood by near Infrared Spectroscopy

“…For example, in juvenile wood from Pinus palustris, when the microfibril angle exceeded ca 30°, the plastic deformation in the lignin matrix became significant in the contribution to rupture. 26 When principal component non-linear regression was utilised to model the modulus of rupture, hemicelluloseassociated wavelengths in the near infrared region were found to be significant for prediction, 27 as it has been found that xylose is tightly bound to the cellulose microfibrils even after partial hydrolysis. 28 Xylose would thus be important in the transfer of stress between cellulose fibrils, with more xylose along the glucose chain equating to a more uniform stress distribution.…”

Near Infrared Spectroscopy Calibration for Wood Chemistry: Which Chemometric Technique Is Best for Prediction and Interpretation?

“…In most cases, the predictive capacity of the NIR model has been the focus of discussion with partial least squares (PLS) working better than principal components regression (PCR) for improved r 2 and other predictive diagnostics. However, more and more scientists are using the coefficients/loadings within the models to interpret the relationship between wood chemistry functional groups and key traits including tensile strength [ 23 , 24 ], bending [ 11 , 25 ], calorific content [ 26 ], among others. But currently, it is unknown if PLS loading plots are statistically similar to that obtained from PCR.…”

Aquaphotomics monitoring of strawberry fruit during cold storage – A comparison of two cooling systems

“…Structural water; associated with starch or cellulose(140,141) and other polymers(106,142,143), associated with sugars(142,(144)(145)(146), associated with proteins(147) or amino compounds(148), associated with membrane structure, influenced by temperature(117), related to mechanical properties(106), indicator of fermentation(149), indicative of vegetative growth stage(142), indicator of crystallinity(118, 150), indicator of preservation of tissues, damage(113) Currently available information and the tentative functionality of corresponding water species in biological and aqueous systems.…”