Fourier Transform Infrared Studies of Heterogeneity, Photodegradation, and Lignin/Hemicellulose Ratios within Hardwoods and Softwoods

Orton, Christopher R.; Parkinson, Dilworth Y.; Evans, Philip D.; Owen, Noel L.

doi:10.1366/0003702042475385

Cited by 24 publications

(10 citation statements)

References 8 publications

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“…Characteristic peak of hemicellulose, 1731 cm −1 , due to carbonyl (ester linkage), is retained after the delignification process. However, the carbonyls can be attributed to carbonyls in lignin 38 and carboxylation during the delignification process 35 . After delignification, characteristics peaks for lignin, 1590 cm -1 and 1510 cm -1 37 , which belongs to aromatic symmetric and aromatic asymmetric stretching, cannot be observed.…”

Section: Compositional Analysismentioning

confidence: 99%

Cellulose nanofibrils: a rapid adsorbent for the removal of methylene blue

et al. 2015

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Cellulose nanofibrils (CNF) were prepared from kenaf core (KC) using acidified-chlorite bleaching method and followed by disintegration using high speed blender. The effects of disintegration time and acid treatment on the defibrillation of holocellulose were studied. Hemicellulose was found to facilitate defibrillation, as CNF without any acid treatment was fully defibrillated after 30 min. The adsorption kinetics of CNF toward cationic dye cannot be accurately determined due to its quick adsorption performance, in which the equilibrium is achieved immediately after 1 min of contact time. The effects of acid treatment on holocellulose, pH, adsorbent dosage, temperature and dye concentration were studied and optimized. Adsorption data were fitted to both Langmuir and Freundlich models where Langmuir model was found to be the better model to describe the adsorption process. Maximum adsorption capacity was found to be 122.2 mg/g at pH 9, 20 °C for the non-acid treated CNF. The CNF can be regenerated by desorption at low pH where, as much as 70 % of dye adsorbed can be desorbed after 6 cycles of adsorptiondesorption cycle.

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Section: Compositional Analysismentioning

confidence: 99%

Cellulose nanofibrils: a rapid adsorbent for the removal of methylene blue

et al. 2015

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“…The more common methods in the literature consider the vibrational spectroscopy (near-infrared range (NIR) [3], mid-infrared (MIR) range [4], [5], and Raman spectroscopy [6], [7]). Differently, fluorescence spectroscopy can also be considered.…”

Section: Previous Workmentioning

confidence: 99%

A low-cost neural-based approach for wood types classification

Labati

Gamassi

Piuri

et al. 2009

2009 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications

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In many applications such as the furniture and the wood panel production, the classification of wood kinds can provide relevant information concerning the aspect, the properties and the preparation procedures of the products. Usually, the wood kind classification is made by trained operators, but this solution suffers of important drawbacks: it is time consuming and it has low repeatability/accuracy since the classification is related to the operator experience and fatigue. In the literature, some attempts to solve this applicative problem by automatic systems are present, but, unfortunately, these solutions present complex measures and setups. In this paper, we present a novel approach for wood kinds classification based on a neural network system which exploits the emitted spectrum of the wood samples filtered with a bank of low-cost optical filters coupled with a set of photo detectors. The structure of the proposed system can be directly implemented in an embedded low-cost system. The results of the system simulations are very satisfactory and they demonstrate that this approach is feasible and very promising.

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“…Recently, the wood spectral reflectance characteristics are also exploited for the species classification. The more common schemes in the literature consider the vibration spectroscopy [6,7] and the Raman spectroscopy [8]. For example, Piuri and Scotti present a scheme for the wood species classification based on the analysis of fluorescence spectra [9].…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Wood Defect and Species Detection with 3D Laser Scanning Scheme

Zhao

Xiao

2016

International Journal of Optics

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Wood grading and wood price are mainly connected with the wood defect and wood species. In this paper, a wood defect quantitative detection scheme and a wood species qualitative identification scheme are proposed simultaneously based on 3D laser scanning point cloud. First, an Artec 3D scanner is used to scan the wood surface to get the 3D point cloud. Each 3D point contains its X, Y, and Z coordinate and its RGB color information. After preprocessing, the Z coordinate value of current point is compared with the set threshold to judge whether it is a defect point (i.e., cavity, worm tunnel, and crack). Second, a deep preferred search algorithm is used to segment the retained defect points marked with different colors. The integration algorithm is used to calculate the surface area and volume of every defect. Finally, wood species identification is performed with the wood surface’s color information. The color moments of scanned points are used for classification, but the defect points are not used. Experiments indicate that our scheme can accurately measure the surface areas and volumes of cavity, worm tunnel, and crack on wood surface with measurement error less than 5% and it can also reach a wood species recognition accuracy of 95%.

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Fourier Transform Infrared Studies of Heterogeneity, Photodegradation, and Lignin/Hemicellulose Ratios within Hardwoods and Softwoods

Cited by 24 publications

References 8 publications

Cellulose nanofibrils: a rapid adsorbent for the removal of methylene blue

Cellulose nanofibrils: a rapid adsorbent for the removal of methylene blue

A low-cost neural-based approach for wood types classification

Simultaneous Wood Defect and Species Detection with 3D Laser Scanning Scheme

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