A review of recent application of near infrared spectroscopy to wood science and technology

Tsuchikawa, Satoru; Kobori, Hikaru

doi:10.1007/s10086-015-1467-x

Cited by 243 publications

(132 citation statements)

References 53 publications

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“…To date, there are a range of available methods for assessment of lignocellulosic biomass reviewed in [13]. Among the available platforms, near-infrared (NIR) spectroscopy-based methods have been used widely for assessing biomass since they offer nondestructive analysis (reducing hazardous risks and allowing samples to be re-used for other purposes), a relatively low cost per sample and require minimal technical skill reviewed in [13][14][15]. To develop NIR spectroscopic models, paired spectra and reference values (obtained through traditional analytical methods) are combined using chemometric technique partial least squares (PLS) regression.…”

Section: Introductionmentioning

confidence: 99%

High-Throughput Profiling of the Fiber and Sugar Composition of Sugarcane Biomass

et al. 2016

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Lignocellulosic biomass from sugarcane (Saccharum spp. hybrids) could potentially be a major feedstock for second-generation biofuel production. Consequently, selecting sugarcane varieties with favorable biomass characteristics, typically less enzymatic recalcitrance and better saccharification yield without sugaryield penalty, will be important in sugarcane breeding. Economical and high-throughput techniques for profiling the major biomass components of this complex system will facilitate selection of clones with ideal lignocellulosic composition from large numbers of genotypes in breeding programs. We used a combined high-throughput profiling approach to evaluate the biomass composition of samples from a sugarcane germplasm collection. This employed near-infrared (NIR) spectroscopy for fiber characterization and high-performance liquid chromatography (HPLC) for determining the sugar content in juice. The results for 331 samples, from a diverse sugarcane population of 186 genotypes, derived from 143 parents of different genetic backgrounds, showed that high-quality NIR spectroscopic predictions were feasible for cellulose, hemicellulose, lignin, and extractives values in fiber, and sugars in juice were suitably analyzed by HPLC. The analysis of total biomass indicated that this NIR-and HPLC-based highthroughput method allowed a robust phenotypic assessment of a large number of samples for the key biomass traits in the sugarcane system, including total dry biomass, fiber, sugar content, and theoretical ethanol yields, and could potentially become the method of choice for sugarcane germplasm screening in breeding programs targeting the support of biofuel production.

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Section: Introductionmentioning

confidence: 99%

High-Throughput Profiling of the Fiber and Sugar Composition of Sugarcane Biomass

et al. 2016

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“…NIR spectroscopy with aid of multivariate statistics and computational systems is useful for quantitative but even more for qualitative applications, including classification of wood and other biological materials (Tsuchikawa & Kobori, 2015). In summary, the technique relies on developing a calibration that relates the NIR spectra of a large number of wood samples to their known chemical constitution, for example pulp yield or cellulose content (Raymond, 2002).…”

Section: Near Infrared Spectroscopy In Forest Sectormentioning

confidence: 99%

“…Tsuchikawa et al (1992) have investigated the effect of the surface-structure of wood on NIR spectroscopy. The first study involving NIR spectra and wood density was probably presented by Thygesen (1994).…”

Section: Wood Characterizationmentioning

confidence: 99%

“…Many review articles describing a range of applications of NIR spectroscopy in the forest and wood researches are available. Schimleck et al (2000), So et al (2004), Tsuchikawa (2007), Tsuchikawa & Schwanninger (2013) and Tsuchikawa & Kobori (2015) presented complete review papers on NIR spectroscopy applications in wood research where recent technical and scientific reports have been widely presented and discussed. Leblon et al (2013) listed the researches on NIR spectroscopy for real-time monitoring specifically moisture content and wood density.…”

Section: Application Reviews and Spectra Interpretation Of Wood Compomentioning

confidence: 99%

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Challenges in the use of Near Infrared Spectroscopy for improving wood quality: A review

2018

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Aims of study: Forestry-related companies require quality monitoring methods capable to pass a large number of samples. This review paper is dealing with the utilization of near infrared (NIR) technique for wood analysis.Area of study: We have a global point of view for NIR applications and characterization of different kind of wood species is considered.Material and methods: NIR spectroscopy is a fast, non-destructive technique, applicable to any biological material, demanding little or no sample preparation. NIR spectroscopy and multivariate analysis serve well in laboratories where the conditions are controlled. The main challenges to NIR spectroscopy technique in field conditions are moisture content and portability.Results: In this review, the methods and challenges for successfully applying NIR spectroscopy in the field of wood characterization are presented. Portable equipment need to record NIR spectra with low noise and low sensitivity to temperature and humidity variations of the air in forest environments. Studies concerning the sample preparation effects on the robustness of the calibrations are thus required.Research highlights: This paper examines traditional applications and practical aspects as well as innovative modern adaptations applied, for example, in hyperspectral imaging and genetic studies.Additional keywords: Near Infrared Spectroscopy; wood properties; moisture; pulp; camera hyperspectral, genetic studies. Abbreviations used: MC (moisture content); PCR (principal component regression); PLS (least squares regression); R² (coefficient of determination); RMSECV (root mean square error of cross validation); r²p (determination coefficient in test set validation); RDP (ratio of performance to deviation); UV (ultraviolet); S/G (syringyl to guaiacyl ratio).

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“…It is a powerful analytical tool used in the wood industry for predicting chemical composition of wood (Poke and Raymond 2006), classifying the type of fungal decay in wood (Fackler et al 2007;Yang et al 2008), discriminating blue-stained wood (Via et al 2008), and identifying wood species (Tsuchikawa et al 2003;Shou et al 2014). Recently, NIRS has been used to detect knots on wood surfaces.…”

Section: Introductionmentioning

confidence: 99%

Detection of Knot Defects on Coniferous Wood Surface Using Near Infrared Spectroscopy and Chemometrics

et al. 2016

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Lumber pieces usually contain defects such as knots, which strongly affect the strength and stiffness. To develop a model for rapid, accurate grading of lumbers based on knots, Douglas fir, spruce-pine-fir (SPF), Chinese hemlock, and Dragon spruce were used. The experiments explored the effects of modelling methods and spectral preprocess methods for knot detection, and investigated the feasibility of using a model built within one species to discriminate the samples from other species, using a novel variable selection method-random frog (RF)-to select effective wavelengths. The results showed that least squares-support vector machines coupled with first derivative preprocessed spectra achieved best performance for both single and mixed models. Models built within Dragon spruce could be used to classify knot samples from SPF and Chinese hemlock but not Douglas fir, and vice versa. Eight effective wavelengths (1314 nm, 1358 nm, 1409 nm, 1340 nm, 1260 nm, 1586 nm, 1288 nm, and 1402 nm) were selected by RF to build effective wavelengths based models. The sensitivity, specificity, and accuracy in the validation set were 98.49%, 93.42%, and 96.30%, respectively. Good results could be obtained when using data at just eight wavelengths, as an alternative to evaluating the whole spectrum.

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A review of recent application of near infrared spectroscopy to wood science and technology

Cited by 243 publications

References 53 publications

High-Throughput Profiling of the Fiber and Sugar Composition of Sugarcane Biomass

High-Throughput Profiling of the Fiber and Sugar Composition of Sugarcane Biomass

Challenges in the use of Near Infrared Spectroscopy for improving wood quality: A review

Detection of Knot Defects on Coniferous Wood Surface Using Near Infrared Spectroscopy and Chemometrics

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