四种算法用于近红外测定制浆材材性的对比研究

采集了常见制浆材(桉木、相思木及杨木)样品的近红外光谱,测定了样品的基本密度、综纤维素、木质素和苯醇抽出物含量,用人为控制水分的方法测定了样品的水分含量。对原始光谱进行预处理后,分别运用偏最小二乘法(PLS)、LASSO算法、支持向量机法(SVR)和人工神经网络法(BP-ANN)建立基本密度、水分含量、综纤维素、木质素和苯醇抽出物含量的预测模型。对预测模型进行独立验证,结果显示:LASSO算法建立的基本密度和综纤维素模型性能最优,其预测均方根误差(RMSEP)分别为0.006 3 g/cm~3和0.49%,绝对偏差(AD)范围分别为-0.008 8~0.009 6 g/cm~3和-0.85%~0.87%;PLS建立的水分含量模型及苯醇抽出物模型最优,RMSEP值分别为1.21%和0.24%,AD范围分别为-1.99%~2.03%和-0.35%~0.38%;SVR建立的木质素模型最优,RMSEP值为0.43%,AD范围为-0.76%~0.74%,均满足制浆造纸工业中对误差的要求。     

基于近红外光谱技术的热处理竹材物理力学性能

探讨了近红外光谱(NIRs)技术对实现热处理毛竹分选和性能在线检测的可能性。采集了3种不同温度(150,180和210℃)热处理及未处理毛竹的径切面近红外光谱信息,应用主成分分析方法与偏最小二乘法对竹材进行分类,并建立了热处理竹材的材色、密度以及力学性能预测模型。结果表明:1)近红外光谱二阶导数谱图在7 004和6 452 cm-1等吸收带处很好地反映了竹材热处理对应化学成分的变化,表明了近红外光谱变化与化学成分变化的一致性,也说明了NIRs用于快速分析热处理竹材材性的可能性; 2)热处理竹材在主成分得分图中呈明显的聚类分布特征,说明了NIRs技术对于热处理竹材良好的分类能力; 3)材色预测模型的模型参数R2≥0.93、RPD均大于3.90,表现出了非常好的材色预测性能。气干密度、绝干密度以及抗弯强度预测模型的R2分别为0.83,0.85和0.82,RPD分别为2.42,2.59和2.34,能够满足竹材性能的评估精度要求。     

近红外光谱法快速测定速生桉木化学成分含量

用常规方法测定了104个速生桉木样品的综纤维素、聚戊糖、酸不溶木素及苯醇抽出物含量并采集了样品的近红外光谱。对原始光谱进行多元散射校正后,运用偏最小二乘法和交互验证的方法,确定最佳主成分数并建立样品相关化学成分含量的校正模型。独立验证中综纤维素、聚戊糖、酸不溶木素和苯醇抽出物模型的决定系数 Rval2分别为0.9067、0.9033、0.9504、0.9570;预测均方根误差(RMSEP)分别为0.33%、0.50%、0.31%、0.17%;相对分析误差(RPD)值分别为3.22、3.20、4.43、4.73;绝对偏差(AD)分别为?0.53%~0.60%、?0.95%~0.77%、?0.55%~0.52%、?0.22%~0.29%,4个校正模型较好地预测了验证集样品的化学成分含量,基本满足制浆造纸工业中快速测定速生桉木原料的需求。     

近红外光谱法快速测定制浆材化学成分含量

为实现制浆材化学成分含量的快速测定与实时分析,用常规方法测定了120个制浆材样品的综纤维素、聚戊糖、酸不溶木素及苯醇抽出物含量,并采集了样品的近红外光谱。对原始光谱进行多元散射校正后,运用偏最小二乘法和交互验证的方法,根据主成分数与PRESS值的关系,确定最佳主成分数分别为9,10,8,9,据此建立样品相关化学成分含量的校正模型。独立验证中综纤维素、聚戊糖、酸不溶木素和苯醇抽出物模型的决定系数R2val分别为0.918 8,0.949 3,0.946 6和0.928 4,预测均方根误差(RMSEP)分别为0.70%,0.75%,0.72%和0.24%,相对分析误差(RPD)值分别为3.50,4.44,4.33和3.74,绝对偏差(AD)分别为-0.95%~1.22%,-1.42%~1.29%,-1.39%~1.14%和-0.34%~0.39%,4个校正模型较好地预测了验证集样品的化学成分含量,基本满足制浆造纸工业中快速测定的需求。     

四川两种竹材理化性质及纤维形态分析

为有效利用四川的乡土竹种慈竹和绵竹,测定分析了2个竹种的理化性质和纤维形态,并与毛竹及常见的阔叶材和针叶材做了对比。结果表明：1）在化学成分上,2个竹种的抽提物含量均小于毛竹,而介于针叶材和阔叶材之间,2个竹种的综纤维素含量和纤维素含量均高于毛竹,木质素含量与毛竹接近,但灰分含量远高于毛竹、阔叶材和针叶材;2）在物理力学特性上,2个竹种竹材密度略低于毛竹,顺纹抗压强度均明显高于毛竹,且优于强度较高的阔叶材马占相思木,2个竹种的抗弯弹性模量和抗弯强度均明显高于毛竹,抗剪强度与毛竹接近,表明2个竹种力学强度均较大,可以用作结构用竹或建筑用竹;3）在纤维形态上,慈竹和绵竹的平均纤维长度分别为0.63和0.67 mm,均小于毛竹,且纤维长度多为500~1 000和1 000~1 500 μm,2个竹种的纤维长宽比均在45以下,表明慈竹和绵竹均不适于作为造纸原料。     

腐朽过程中毛竹主要化学成分的变化

以毛竹为原料,选择1种白腐菌和2种褐腐菌对竹材进行腐朽试验,利用X射线衍射和傅里叶红外光谱等手段,测定竹材的失重率、相对结晶度和化学官能团。结果表明,随腐朽时间的延长,竹材的失重率不断增加,结晶度不断下降。通过对腐朽竹材主要官能团的观察,发现白腐菌的侵蚀能造成竹材主成分的分解,其中对木质素的分解能力更强。褐腐菌的侵蚀主要破坏竹材综纤维素。     

湿地松木材近红外光谱与其结晶度的相关性

对湿地松木材近红外光谱与X射线衍射法测定的木材结晶度之间的相关性进行分析,并结合近红外光谱分析技术的基本理论,探讨降低光谱范围和选择相关光谱信息对近红外光谱预测木材结晶度的影响.结果表明:1)降低参与建模的近红外光谱范围仍然可以得到比较理想的近红外光谱模型与预测结果,当选用2 000～2 500 nm区域的光谱建立模型时,预测值与实测值的相关系数r达到0.943;2)当选择光谱范围更小但与木材纤维素吸收峰密切相关的光谱数据(1 400～1 660 nm或2 020～2 250 nm)进行建模时,模型的预测效果并未降低(r＞0.947),甚至仅采用7个光谱数据也可以得到比较理想的预测结果,预测相关系数r可达到0.930,说明采用更少的但与木材纤维素吸收峰密切相关的光谱信息,所建立的预测模型仍可得到比较理想的预测效果,这将有利于低成本、便携式近红外光谱仪的开发.     

不同种源毛竹材纤维形态和化学成分的变异

对不同种源毛竹材纤维形态和化学成分进行测定和分析,揭示了不同种源毛竹材纤维形态和化学成分的变异规律。结果表明:浙江衢县种源毛竹材纤维长度、长宽比和纤维素含量均大于其它5个毛竹种源。不同种源毛竹材纤维长度、纤维宽度和长宽比差异均极显著。培育毛竹纸浆材应优先选择浙江衢县种源。     

基于近红外光谱及 BP 神经网络分析法磁预测森林土壤有机碳含量

为快速测定森林土壤的有机碳含量,从取自小兴安岭带岭林业局东方红林场的120个土壤样品中采集350～2500 nm的土壤近红外光谱数据,对光谱做一定的预处理后,运用主成分分析法压缩提取前8个主成分,结合BP神经网络非线性方法建立土壤有机碳含量的预测模型并进行验证。结果表明,验证集的相关系数为0.78002,均方根误差为0.5002,预测集的相关系数为0.84941,均方根误差为0.4538。应用近红外光谱技术及BP神经网络非线性方法建模可以有效地预测土壤的有机碳含量,为野外大面积快速测定森林土壤碳含量提供了技术依据。     

支持向量机结合近红外光谱法测定杉木木质素的含量

采用支持向量机(SVM)结合近红外光谱(NIR)技术建立测定杉木中木质素的定量分析模型。以47个杉木样品作为实验材料,用常规方法测定了样品中木质素的含量,用近红外光谱仪采集相应的光谱,对光谱数据进行平滑、求导、小波压缩以及归一化,结合支持向量机,以径向基(RBF)作为核函数,建立了测定杉木中木质素含量的模型。校正相对误差的平方和为0.007433,预测相对误差的平方和为0.001219。结果表明,该方法测量比较准确,可以用于杉木中木质素含量的预测。     

Rapid assessment of coniferous biomass lignin–carbohydrates with near-infrared spectroscopy

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.     

萃取法提取薄荷油的化学成分比较

采用水蒸气蒸馏(SD)法和超临界CO2萃取(SCDE)法从薄荷中提取挥发油,并用GC-MS技术对其化学成分进行了分析.SD法提取薄荷油的出油率为1.15%,SCDE法提取薄荷油的出油率为2.43%.GC-MS分析表明,SD法提取的薄荷油中含44种化学成分,占总挥发油的97%以上,其中薄荷醇相对含量为69.4%;SCDE法提取的挥发油中含38种化学成分,占总挥发油的92%以上,其中薄荷醇相对含量为61.8%.     

Quantifying lignin and holocellulose content in coniferous decayed wood using near-infrared reflectance spectroscopy

To determine the independent decomposition rates of lignin and cellulose of decayed woody debris, a technique for the rapid analysis of lignin and cellulose is required. We applied a near-infrared spectroscopy (NIRS) technique to measure the lignin and holocellulose content in decayed wood. We succeeded in creating partial least-squares (PLS) models to estimate the lignin and holocellulose content in the decayed wood of five species using NIR spectra. Although the accuracy was acceptable for the estimation of a five-species mixed model (R ² = 0.970 for lignin and R ² = 0.962 for holocellulose), it was further improved when the model was applied to each species independently. This combination of NIRS and a PLS model is a valuable tool for the determination of the lignin and holocellulose content in decayed wood. The technique is time efficient (3 min per sample) and non-hazardous (no acid treatment is required).     

Prediction of mechanical properties of Chinese fir wood by near infrared spectroscopy

Mechanical properties and the visible and near infrared (NIR) (350–2500 nm) spectra obtained from longitudinal and transverse face of 155 small clear wood samples of Chinese fir (Cunninghamia lanceolata) were measured, and 103 of them were used to establish calibration models. Calibrations were tested on an independent set (52 samples). Differences between calibrations developed by using the longitudinal and transverse face were small. The calibrations developed by using NIR spectra (350–2500 nm) collected from transverse face were slightly inferior to those developed by using NIR spectra collected from longitudinal face. When reducing the spectral range to between 780 and 1050 nm, the calibrations developed by using NIR spectra collected from longitudinal face were slightly inferior to those developed by using NIR spectra collected from transverse face, and reducing the spectral range causes no decrease in the quality of the models developed using NIR spectra collected from transverse face. Partial lease square (PLS) modeling and test showed that calibrations developed using the visible and NIR spectra from transverse and longitudinal faces and calibrations developed by using the reducing spectral range (780–1050 nm) from the transverse face were moderate, and have a RPD range from 1.51 to 1.90. It is concluded that NIR spectroscopy can be used as an initial screening. __________ Translated from Journal of Northwest Forestry University, 2007, 22(5): 149–154 [译自: 西北林学院学报]     

Effects of peeling and steam-heating treatment on basic properties of two types of bamboo culms (<Emphasis Type="Italic">Phyllostachys makinoi</Emphasis> and <Emphasis Type="Italic">Phyllostachys pubescens</Emphasis>)

Epidermal peeling (EPT) and steam-heating (SHT) treatments are two widely processing methods in bamboo industry. Moso bamboo (Phyllostachys pubescens Mazel) and makino bamboo (Phyllostachys makinoi Hayata) are important economical bamboo species in Taiwan and China. The subject of this study was to access the changes of chemical and mechanical properties in moso and makino bamboo culms, which were collected from Taiwan and China after EPT and SHT. As regard to chemical properties, the amounts of extractives and ash were increased both in moso and makino bamboos after EPT and SHT. In contrast, the contains of holocellulose and α-cellulose were decreased after EPT and SHT for two bamboos. Moso bamboo collected from China contained the lowest cellulose content but the highest amount of hemicellulose by SHT. The lignin contents of all samples were no significant different after SHT, and it might due to the structure of lignin did not destroy at 120 °C. For the mechanical properties, the density of all makino and moso bamboo samples was reduced after SHT; moreover, the decreasing trend of density was similar to the reducing of holocellulose, α-cellulose, hemicellulose, and equilibrium moisture content (EMC). All bamboo samples without EPT presented the highest modulus of elasticity (MOE) and modulus of rupture (MOR) whether SHT or not. Both MOE and MOR of all bamboo samples were decreased after SHT. The integrity of the bamboo skin is important for the dimensional stability of the bamboo, and the water absorption ability would be increased after EPT; however, SHT decreased the water absorption of bamboo.     

粗皮桉木材力学性质的近红外光谱方法预测

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。     

Use of near infrared spectroscopy to measure the chemical and mechanical properties of solid wood

Near infrared (NIR) spectroscopy (500 nm–2400 nm), coupled with multivariate analytic (MVA) statistical techniques, have been used to predict the chemical and mechanical properties of solid loblolly pine wood. The samples were selected from different radial locations and heights of three loblolly pine trees grown in Arkansas. The chemical composition and mechanical properties were measured with traditional wet chemical techniques and three point bending tests, respectively. The microfibril angle was measured with x-ray scattering. These chemical and mechanical properties were correlated with the NIR spectra using projection to latent structures (PLS) models. The correlations were very strong, with the correlation coefficients generally above 0.80. The mechanical properties could also be predicted using a reduced spectral range (650 nm–1150 nm) that should allow for field measurements of these properties using handheld NIR spectrometers.