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1.
The main objective of this research was to construct accurate near-infrared reflectance (NIR) models of wood chemistry. Wet chemistry procedures and high-performance liquid chromatography methods were employed to analyze the chemical composition of southern pine. The NIR spectra were collected from 21 wood samples, which were milled down to different particle size classes. NIR calibration and prediction models were established using two modeling methods with different pretreatments. Furthermore, the spectrum range used in the NIR models was refined to achieve higher prediction accuracy. Results showed that NIR model precision could be improved considerably by decreasing the particle size to a very fine powder coupled with a targeted spectrum range. Superior prediction models for lignin and holocellulose content were constructed, while models for extractives and cellulose contents were also strong.  相似文献   

2.
试验以采集的100份桉树不同组合杂交子代的木芯及木粉样品作为研究对象,以常规方法测定所取木材样品的木材密度、纤维长度和纤维宽度并用 Polychromix 手持式近红外仪采集了自然风干状态木粉的近红外光谱信息。光谱数据的处理及建模用 Unscrambler 9.7软件完成。建模结果显示：木材密度、纤维长度和纤维宽度的预测精度均可达90%以上。建模过程中,木材密度较纤维长度和纤维宽度所需的校正样本集数量要多,说明要达到一定的预测精度,纤维长度和纤维宽度其所建模型的预测范围会相应变小。  相似文献   

3.
《Southern Forests》2013,75(3-4):181-189
Near-infrared (NIR) scanning technology is regarded as a potential tool for rapid determination of wood properties, which can substitute time-consuming and costly traditional methods. Pinus patula is the most important softwood species in South Africa, and this study is aimed at developing NIR calibration models for quick prediction of its pulp yield and chemical composition. A total of 85 trees from 17 plots, covering the range of site conditions in the Mpumalanga escarpment area, were sampled. Two samples were taken from each tree: a 1 m billet above breast height and a 20 mm disc at breast height. The billet was pulped using the kraft pulping process to determine pulp yield. The disc was ground into sawdust and the chemical composition was determined using conventional wet chemistry. Sawdust was scanned on a NIR spectrophotometer to produce NIR spectra. Calibration models to predict pulp yield, cellulose and lignin content were developed by applying chemometrics and partial least squares regression. Validation and determination of prediction accuracy of the models were performed using independent data. The prediction of cellulose and lignin were acceptable with correlations of determinations (r 2) of 0.71 and 0.70 respectively. Standard errors of prediction were generally low (less that 0.86) for all the models. The prediction r 2 for both total and screened pulp yield were only 0.62. Although the cellulose and lignin models can be used with confidence, the expansion of the sample size for follow-up research must be considered in order to increase the variability of tested wood properties and improve the prediction strength of the models. The NIR calibration provided in this study can contribute to the efficient examination of forest site-to-wood quality relationships that would enhance precision forest management and wood processing efficiency.  相似文献   

4.
《Southern Forests》2013,75(2):107-111
Near-infrared spectroscopy has been used to develop calibration models for the rapid determination of kraft pulp yield (KPY) and lignin in Eucalyptus camaldulensis and Leucaena leucocephala. The correlation coefficient for cross-validation is 0.90 for KPY and 0.95 for lignin prediction, while the root mean square error for cross-validation for KPY and lignin prediction are 1.46 and 0.77, respectively. The method has been validated with 37 samples of E. camaldulensis and 18 samples of L. leucocephala. The root mean square error of prediction for KPY (1.53) is higher than for lignin (0.77). The method is rapid and can be used for screening a large number of samples.  相似文献   

5.
The use of furfuryl alcohol (FA) as a wood modification agent has been known for decades. An independent and reliable analytical method to determine the level of furfurylation is not available. This article reports the use of near infrared spectroscopy (NIR) and thermogravimetric analysis (TGA) to make partial least square prediction models for determining the furfurylation level (the percentage of FA polymer formed within the wood structure). A total of 115 individual samples of furfurylated Scots pine (Pinus sylvestris) originating from 115 production batches were used for modelling. As much as 81 samples were randomly selected for the calibration set and 34 samples for the validation set. Both NIR and TGA gave good predictions when validated by a separate test set. The r 2 for NIR and TGA are 0.93 and 0.94, respectively, and the root mean square errors of predictions are 1.025 and 0.958, respectively. However, the number of principal components for the NIR and TGA models is two and six, respectively. The NIR method is preferred because only two principal components are used and sampling is fast.  相似文献   

6.
A rapid, non-destructive, in-line method suitable for sorting green hem-fir timbers (115-mm square) based on moisture content was established by near-infrared (NIR) spectroscopy. The accuracy of NIR sorting was compared with a commercial capacitance-type moisture meter. Mixedspecies samples consisting of three moisture classes were assessed in this study. The NIR-based prediction model showed positive correlation with the actual calculated values as determined by oven-drying, regardless of knots, surface roughness, and the mix of two wood species. NIR proved to be capable of detecting the moisture content between all pairs of the three moisture groups, whereas the capacitance-type moisture meter failed to establish a significant difference between middle- and high-moisture groups. These findings clearly demonstrate that NIR spectroscopy has a potential to estimate average moisture of green timber indirectly, although it inherently gives only surface moisture content values, as it is limited by scan depth.  相似文献   

7.
粗皮桉木材力学性质的近红外光谱方法预测   总被引：1，自引：0，他引：1  
以人工林粗皮桉木材为研究对象,采用常规力学测试方法和近红外光谱方法对其无疵小试样力学性质进行研究。用近红外光谱仪采集试样表面的近红外光谱,对采集的近红外漫反射光谱进行导数预处理并对不同波段光谱建立校正模型,以1/3试样作为预测集对校正模型进行验证。结果表明:二阶导数预处理、350～25000nm全光谱波段、径切面和弦切面平均光谱值对粗皮桉木材力学性质模型预测效果最好。抗弯弹性模量和抗弯强度、顺纹抗压强度的实测值与近红外光谱方法的预测值存在较好的相关性,相关系数均大于0.88,相对分析误差大于2.0,表明利用近红外光谱方法预测人工林粗皮桉木材力学性质效果较好。  相似文献   

8.
Determination of quality parameters such as lignin and extractive content of wood samples by wet chemistry analyses takes a long time. Near-infrared (NIR) spectroscopy coupled with multivariate calibration offers a fast and nondestructive alternative to obtain reliable results. However, due to the complexity of the NIR spectra, some wavelength selection is generally required to improve the predictive ability of multivariate calibration methods. Pinus brutia Ten. is the most growing pine species in Turkey. Its rotation period is around 80 years; the forest products industry has widely accepted the use of Pinus brutia Ten. because of its ability to grow on a wide range of sites and its suitability to produce desirable products. Pinus brutia Ten. is widely used in construction, window door panel, floor covering, etc. Determination of lignin and extractive content of wood provides information to tree breeders on when to cut and how much chemicals are needed for the pulping and bleaching process. In this study, 58 samples of Pinus brutia Ten. trees were collected in Isparta region of Turkey, and their lignin and extractive content were determined with standard reference (TAPPI) methods. Then, the same samples were scanned with near-infrared spectrometer between 1,000 and 2,500 nm in diffuse reflectance mode, and multivariate calibration models were built with genetic inverse least squares method for both lignin and extractive content using the concentration information obtained from wet standard reference method. Overall, standard error of calibration (SEC) and standard error of prediction (SEP) ranged between 0.35% (w/w) and 2.40% (w/w).  相似文献   

9.
Tracheid coarseness, specific surface, wall thickness, perimeter, and radial and tangential diameter from 119 radial strips of Pinus taeda L. (loblolly pine) trees grown on 14 sites in three physiographic regions of Georgia (USA) were measured by SilviScan. NIR spectra were also collected in 10 mm increments from the radial longitudinal surface of each strip and split into calibration (9 sites, 729 spectra) and prediction sets (6 sites, 225 spectra). NIR spectra (untreated and mathematically treated first and second derivative and multiplicative scatter correction) were correlated with tracheid properties to develop calibrations for the estimation of these properties. Strong correlations were obtained for properties related to density, the strongest R 2 being 0.80 (coarseness), 0.78 (specific surface) and 0.84 (wall thickness). When applied to the test set, good relationships were obtained for the density-related properties (R p 2 ranged from 0.68 to 0.86), but the accuracy of predictions varied depending on math treatment. The addition of a small number of cores from the prediction set (one core per new site) to the calibration set improved the accuracy of predictions and, importantly, minimized the differences obtained with the various math treatments. These results suggest that density related properties can be estimated by NIR with sufficient accuracy to be used in operational settings.  相似文献   

10.
The visible and near infrared （NIR） （350-2500 nm） spectra and the MOE of 438 small clear wood samples from Chinese fir, eucalyptus and poplar 72 were measured. Using partial least-square （PLS） modeling, the NIR spectra could be used to predict MOE and MOR of the clear-wood samples from Chinese fir and eucalyptus solid wood. NIR spectra could only be used to Predict MOE but not MOR of poplar clear-wood samples. With the exception of MoR of poplar clear-wood samples, the correlations between NIR and the mechanical properties are very strong, and the calibration and test correlation coefficients are both above 0.80.  相似文献   

11.
Five Populus x euramericana wood samples representing three different sites were selected and nearinfrared （NIR） spectra were obtained. For these sections, basis weight, brightness and three mechanical properties （tensile index, tearing index and bursting index） were determined by standard analytical methods. Calibrations were developed for each paper property using the NIR spectra, data on paper properties, using partial least squares （PLS） regression. The results show that the coefficients of correlation of calibration and validation for basis weight were 0.8824 and 0.8299, respectively; the standard error of calibration （SEC） and prediction （SEP） were 1.150 and 1.170, respectively. In testing for brightness, the correlation coefficient of calibration was 0.9621 and for validation 0.9612, while the SEC and SEP were 0.997 and 1.300, respectively; paper brightness and NIR spectroscopy were highly correlated. NIR spectroscopy can be used to predict tensile, tearing and bursting indices of paper samples rapidly. We found that the paper properties fitted by NIR and GB methods were highly correlated. The coefficients of correlation of calibration and validation for basis weight exceeded 0.8000, while the SEC and SEP were very small. These results reveal that the five paper properties of Populus x euramericana and those predicted by the NIR model were highly correlated. We conclude that the NIR models can be used for the prediction of paper properties.  相似文献   

12.
Near-infrared (NIR) spectroscopy has been demonstrated as a means for rapid nondestructive determination of the chemical composition and final pulp yield of Eucalyptus camaldulensis in Thailand tree plantations. Multiple linear regression (MLR) analysis and partial least squares (PLS) analysis were introduced to develop statistical models in terms of calibration equations for total pulp yield, screened pulp yield, and contents of -cellulose, pentosans, and lignin in wood. In MLR analysis, a reasonably good calibration equation was found only for pentosans (standard error of prediction (SEP): 0.98%). The PLS analysis improved the accuracy of prediction for every criterion variable, especially for pentosans (SEP: 0.91%) and lignin (SEP: 0.52%). Also, in the case of screened pulp yield, we were able to use such a statistical result as an indicator of the characteristics of the pulp and paper. Thus, NIR spectroscopy could be satisfactorily used as an effective assessment technique for Eucalyptus camaldulensis plantation trees.  相似文献   

13.
Near Infrared (NIR) and Fluorescence (FS) spectroscopy were investigated for their ability to rapidly separate three Canadian softwoods: balsam fir, western hemlock, and white spruce. NIR and FS spectral data were used to develop classification models using soft independent modeling of class analogies (SIMCA) method. For each wood species, spectra of 90 wood specimens were collected over a wavelength window of 800–2,500?nm for NIR spectral data and a wavelength range of 380–540 and 380–705?nm for FS spectral data. Raw spectra and first-derivative-transformed spectra were used to develop NIR calibration models to separate the three wood species using the wavelength ranges, 800–2,500, 1,100–2,200, and 1,300–2,000?nm, by the SIMCA method. Similarly, FS raw spectral data were also used to develop FS calibrations using wavelength ranges of 380–540 and 380–705?nm. Principal component analysis models were made for each class from the calibration set consisting of 65 specimens of each of the three wood species. Specimens not present in the calibration set (27 specimens of each wood species) were tested for classification according to the SIMCA method at a 5 and 25% significance level. Type I error associated with the models developed with NIR spectral data ranged from 0 to 19 and 0 to 52% for the 5 and 25% significance levels, respectively, while type II error ranged from 2 to 50 and 0 to 19%, respectively. When tested at a 5% significance level, there was no significant improvement in NIR models developed with first-derivative-transformed spectra over models developed with raw spectra. Type I error associated with the models developed with Fluorescence spectral data ranged from 0 to 4 and 7 to 30% for the 5 and 25% significance levels, respectively, while type II error ranged from 1 to 9 and 0 to 1%, respectively. There were no significant differences in performance of FS models developed with spectra using wavelength ranges of 380–540 and 380–705?nm.  相似文献   

14.
采用偏最小二乘法(PLS)建立测定八角茴香中莽草酸含量的近红外(NIR)光谱定量分析模型.应用多种光谱预处理方法分别对八角茴香固体粉末样品的NIR光谱进行预处理,并采用预处理后的光谱建立定量分析模型,每个模型均经过选择最有效的光谱区域和最适主因子数进行优化.经过比较各个模型的内部交互验证均方根误差(RMSECV)和交互验证预测值与真实值间的相关系数(RV),外部预测均方根误差(RMSEP),选取最优的模型,结果表明定量分析模型稳健性好和测定精度高,在中药有效成分定量分析方面有很好的应用前景.  相似文献   

15.
Feasibility of near-infrared (NIR) spectroscopy for developing multi-species model for plantation timber was explored for estimation of holocellulose in un-extracted milled wood samples. Six commonly planted species of Eucalyptus tereticornis, E. camaldulensis, E. grandis, Leucaena leucocephala, Dalbergia sissoo and Populus deltoides from a wide range of locations and varying age groups were taken for the present study. Few samples of E. hybrid between E. tereticornis and E. camaldulensis were also included in the study to make the model useful for practical application. NIR models were evaluated using partial least squares regression (PLSR-1—full cross-validation, PLSR-2—cross-validation which leaves more than one out) and by dividing the samples into calibration and prediction (test) sets and interchanging them from calibration to prediction sets. The predictive ability of the model was assessed by calculating four ratios of multivariate statistics for individual species model and combined species models. A final combined model for all the species having component range of 76.14–63.03 % and standard deviation of 2.586 % was developed in the spectral range of 7502–4246 cm?1 wave number using 1st derivative plus multiplicative scatter correction using factor of nine by removing samples with outliers found in all the PLSR-2 evaluation steps and in most of the models. The model remained stable even when 30 % of the samples were left out with no outlier detected.  相似文献   

16.
Density and fiber length belong to the parameters that are used by the pulping industry as indicators of wood quality for different industrial processes and final paper products. The feasibility of Fourier transform near-infrared (FT-NIR) spectroscopy for the non-destructive evaluation of fiber length and air-dry density of fast-growing E. camaldulensis from Thailand was investigated using 50 samples. NIR spectra taken from solid wood and air-dry density as well as fiber length were used for partial least squares (PLS) regression analyses. It is the first time that the fiber length of E. camaldulensis solid wood could be predicted with high accuracy and precision and that the ratios of performance to deviation (RPD) obtained are the first that fully fulfill the requirements of AACC Method 39-00 (AACC 1999) for screening in breeding programs (RPD?≥?2.5). The RPDs for cross-validation (test set validation) of the NIR-PLS-R models of 3.3 (3.8) for air-dry density and 3.5 (3.9) for fiber length allow drawing the conclusion that the models are at least applicable for screening in breeding programs as they lie in-between screening (RPD?≥?2.5) and quality control (RPD?≥?5). Even when 40% of the samples were removed in cross-validation of the air-dry density model, the RPD is 3.2, which confirms that the model is robust, stable, and well qualified for prediction. The good model statistics obtained in this study might be due to the fact that measurement sites for the measurement of NIR spectra, air-dry density, and fiber lengths were strictly coincided.  相似文献   

17.
The use of calibrated near infrared (NIR) spectroscopy for predicting the chemical composition of Pinus taeda L. (loblolly pine) wood samples is investigated. Seventeen P. taeda radial strips, representing seven different sites were selected and NIR spectra were obtained from the radial longitudinal face of each strip. The spectra were obtained in 12.5 mm sections from pre-determined positions that represented juvenile wood (close to pith), transition wood (zone between juvenile and mature wood), and mature wood (close to bark). For these sections, cellulose, hemicellulose, lignin (acid soluble and insoluble), arabinan, galactan, glucan, mannan, and xylan contents were determined by standard analytical chemistry methods. Calibrations were developed for each chemical constituent using the NIR spectra, wood chemistry data and partial least squares (PLS) regression. Relationships were variable with the best results being obtained for cellulose, glucan, xylan, mannan, and lignin. Prediction errors were high and may be a consequence of the diverse origins of the samples in the test set. Further research with a larger number of samples is required to determine if prediction errors can be reduced.  相似文献   

18.
应用NIR及主成分回归预测落叶松密度的研究   总被引：1，自引：0，他引：1  
运用近红外光谱主成分回归法对落叶松样品密度进行研究，校正集的相关系数（R）为0．86，校正集标准误差（SEC）为0．01，预测集的相关系数（R）为0．89，预测集标准误差（SEP）为0．02，对未参与建模的12个未知样品进行密度预测，相关系数达0．95。研究表明，近红外光谱能够快速、准确地对落叶松样品密度进行预测，这为快速检测落叶松木材材性提供了一种新方法。  相似文献   

19.
Here, we evaluated the application of near-infrared (NIR) spectroscopy for estimating the degradation level of archeological wood samples from the Tohyamago area, the dendrochronological ages of which were also determined. The wood samples were radially cut from three logs obtained from the Tohyamago area. NIR reflectance spectra were measured from the tangential faces of air- and oven-dried wood samples using a Fourier transform NIR spectrophotometer. The second derivative spectra within the wavenumber range of 6400–5200 cm?1, in which the effect of moisture content in wood is suspected to be insignificant, showed a characteristic behavior with age. By comparing the second derivative spectral change in our wood samples with that in wood degraded by aging, thermal treatment, fungal attack, and lightning reported in the literature, we found that the second derivative spectra of wood samples from one log was similar to those of wood degraded by hygro-thermal treatment, whereas those of wood samples from another log was similar to those of wood degraded by brown-rot fungi. The physical and chemical properties of archeological wood were well predicted using a combination of partial least square regression analysis and NIR spectroscopy.  相似文献   

20.
The use of calibrated near infrared (NIR) spectroscopy for measuring and predicting the advancement of wood decay in Pinus spp. sapwood wafers that were subjected to Gloeophyllum trabeum for periods ranging from 1 to 10 days was investigated. NIR spectra were obtained from the center of the cross-sectional face of each sample before and after decay tests. Mass loss and compression tests were also used to measure the progression of decay. Calibrations were created from NIR spectra, mass loss, and compression strength data using untreated and mathematically treated (multiplicative scatter correction and first and second derivative) spectra. Strong relationships were derived from the calibrations with the strongest R 2 values being 0.98 (mass loss) and 0.97 (compression strength). Calibrations for mass loss showed the strongest statistics for predicting wood decay of a separate test set (0.85 raw, second derivative to 0.76 multiplicative scatter correction (MSC), while predictions for compression strength of the decayed samples resulted in R 2 of 0.69 (raw) to 0.54 (MSC). Calibrations created from the amount of time the samples were decayed showed strong statistics, indicating that NIR spectroscopy can predict the early stages of wood decay.  相似文献   

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