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]     

Rapid,non-destructive carbon analysis of forest soils using neutron-induced gamma-ray spectroscopy

Forest soils are pivotal to understanding global carbon (C) cycling and evaluating policies for mitigating global change. However, they are very difficult to monitor because of the heterogeneity of soil characteristics, the difficulty of representative sampling, and the slow time scale of response to environmental change. Here we demonstrate that use of gamma-ray spectroscopy facilitates in situ non-destructive analysis of C and other elements in forest soils. In this approach the element-specific gamma-rays are induced by fast and thermal neutrons interacting with the nuclei of the elements present in the soil. Background gamma-rays emanating from naturally occurring radionuclides in the forest are recorded as well. We applied this approach in a mature northern hardwood forest on glacial till soils at the Bartlett Experimental Forest in New Hampshire, USA. The inelastic neutron scattering (INS) system yielded strong signals in gamma-ray counts/h, from C and other elements present in the soil matrix that included silicon, oxygen, hydrogen, iron, aluminum, manganese and potassium. The INS sensitivity for carbon was 20.656 counts h⁻¹ kg⁻¹ C m⁻² based on current net C gamma-ray counts and the data for the O horizon and mineral soil to a depth of 30 cm obtained from a nearby quantitative soil pit (7.35 kg C m⁻²). We estimate the minimum detectable change to be ∼0.34 kg C m⁻², which is ∼5% of the current soil C content, and the minimum detectable limit to be ∼0.23 kg C m⁻². Eight % reproducibility from 11 measurements was limited, in part, by the large variability in the system counting geometry due to the uneven forest microtopography. The INS approach has the potential to revolutionize belowground monitoring of C and other elements, because the possibility of detecting a 5% change in forest soils has not been possible with destructive sampling methods.     

杉木种子园种实害虫的综合治理

本文概述了杉木种子园主要种实害虫的综合治理措施。以虫情监测为基础,结合采种摘除虫害球果及强度修枝等林业技术,适时应用０．０５％溴氰菊酯油烟剂防治成虫。通过５年综合治理,使杉木种子园的球果虫害率明显下降,种子产量有较大提高,取得了明显的经济、社会和生态效益。     

Surface quality sensing of trembling aspen (Populus tremuloides Michx.) veneer products by near infrared spectroscopy

Abstract

The potential of near infrared spectroscopy (NIRS) to estimate wood moisture content (MC), surface energy characteristics and adhesive bond strength were evaluated on aspen (Populus tremuloides Michx.) veneer subjected to different drying times. For samples dried progressively at 103°C, the best MC prediction model was for the total MC range (0–100%) with an R² value of 0.68. However, exposure at 180°C produced surface colour changes, and the CIE L*a*b* colour parameters measuring colour changes were better estimated using the 400–900 nm spectral data than the 1100–2400 nm spectral data. Increased exposure time at 180°C resulted in lower wettability and, hence, larger contact angles, especially when ethylene glycol was used as probe solvent. Lap shear strength tests on veneers showed that adhesion by phenol formaldehyde resins was impaired by the high temperature exposure; however, the lap shear strength test had high variability so there was not always a clear relationship between contact angle and lap shear strength test.     

Rapid assessment of wood chemical properties and pulp yield of Eucalyptus camaldulensis in Thailand tree plantations by near infrared spectroscopy for improving wood selection for high quality pulp

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.     

Determination of specific gravity of green Pinus taeda samples by near infrared spectroscopy: comparison of pre-processing methods using multivariate figures of merit

Near infrared diffuse reflectance was used for the determination of specific gravity in green Pinus taeda L. wood samples representing simulated increment cores obtained at breast height and merchantable green logs. The effects of using three pre-processing methods (second derivative, multiplicative scatter correction, and orthogonal signal correction) to reduce the scatter observed in the original spectra were evaluated. The effectiveness of each method was assessed in terms of the average predictive ability of the models and in terms of multivariate figures of merit derived from net analyte signal theory. Specific gravity was successfully modeled using green wood samples. No differences in predictive ability among models were found, although more parsimonious regressions were obtained using transformed spectra. The incorporation of figures of merit for the characterization of calibration models proved to be a valuable tool for understanding the effects of the pre-processing alternatives on the final results.     

无性系、立地、郁闭度对杉木种子园产量和质量的影响

分析了无性系、立地、林分郁闭度等因子对杉木种子园产量和质量的影响，结果表明：无性系、坡向、郁闭度对杉木种子园产量有显著影响，对种子质量也有影响。杉木种子园宜选择阳坡、半阳坡，采用优质高产无性系建园；抓好密度和郁闭度管理，林分郁闭度以小于0.6为宜。     

成年杉木种子园提质改造无性系选择及容器苗培育技术研究

为提高20世纪80年代后期营建的1.5代杉木种子园遗传品质和种子产量,以子代材积增益、当代种子产量均高为标准,选择用于成年种子园提质改造的优良无性系。经综合评价,选择出了靖大30、靖大35、广洋45等可用于杉木成年种子园提质改造的优良无性系20个。采用随机区组设计的方法开展优良无性系容器育苗试验。结果表明:以高度17 cm、直径19 cm规格的容器,按体积比配置70%泥炭土、25%黄心土、5%珍珠岩的混合基质培育容器砧木苗,在砧木保留3轮底枝的部位进行嫁接,切接或舌接法培育2年生容器嫁接苗成活率达90%以上、苗高达93 cm以上。     

古建木构件化学组分近红外光谱分析

在材种鉴定的基础上,通过近红外光谱(NIRS)定性分析了建成约600 a的木造古建筑木构件的化学组分,结合木构件化学组分定量分析,与现代木材相比较,探讨了近红外光谱技术评价木构件老化的可行性。结果表明:近红外二阶导数特征性谱带反映了木材纤维素以及半纤维素和木质素的基团信息,而其差谱反映出木构件与对照样化学组分变化。这些光谱特征与传统的化学组分定量分析的结果非常一致:纤维素和半纤维素相对含量减少而木质素相对含量增加,与各种组分谱带差谱的增减相对应。此外,在5 882,5 587和5 464 cm-1等谱带处反映的纤维素结晶和半结晶区的光谱信息,差谱观察到木构件与现代材落叶松之间化学组分的不变或减少,其结果与X射线衍射(XRD)方法获得的木材结晶度分析结果相一致。通过NIRS定性分析木构件化学组分及结晶度变化,接近于现场检测方法,使用便携式NIRS,在古建筑木构件端头裸露部位获取光谱信息,能够实现现场对木材化学组分的无损定性评价。本实验结果也表明,除了常规的红外光谱(FT-IR)、XRD分析技术,NIRS技术对于木构件老化状况的评价是一种有潜力的无损检测方法。     

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。     

杉木种子园建园技术研究初探

本文着重论述杉木种子园建园中关于建园材料、园址选择、规划设计、子代测定、建园技术、技术档案的收集等问题。     

Genetic variation analysis and comprehensive evaluation of wood property traits of 20-year-old Chinese fir clone

This work focuses on the genetic variation of Chinese fir clones in the radial direction. Four 20-year-old Chinese fir clones were selected in Kaihua Forest Farm, Zhejiang, China, and the differences and genetic characteristics were studied. Clonal repeatability, genotype coefficient of variable, and phenotypical coefficient of variable were calculated to light on the genetic variation on the radial direction. Results showed significant differences (P?<?0.05) between the clones and annual rings of the same clone. The clonal repeatability of the ten wood properties is ranged from 0.5 to 0.8, wherein the fiber length, elastic modulus, and total dry density are higher than 0.7. For all the measured traits, the phenotypic variation of clones is greater than that of the genetic variation. Overall, the measured wood traits, especially the mechanical and physical properties, are strongly controlled by heredity, which means they are potentially helpful for genetic improvement of wood properties and optimal breeding. Furthermore, the clonal repeatability of the measured traits varies between annual rings, and the physical and mechanical properties are relatively stable. The principal component analysis results reveal that the clone of Kai 13 has the highest score.

     

杉木第一代种子园自由授粉子代表型性状的多样性

杉木是我国南方最重要的乡土针叶树种之一,广泛分布于我国亚热带的南方17个省区,经长期的自然选择和人工选择,不同产地的杉木个体在表型性状方面存在不同程度的变异。项目组对不同育种世代种子园自由授粉子代表型性状的多样性进行了研究。其中,对杉木第一代种子园自由授粉子代表型性状多样性分析表明,杉木第一代种子园自由授粉子代的生长、结实、形质等表型性状存在较为丰富的变异,表型性状在家系间的差异均达显著或极显著水平。通过主成分分析和聚类分析,当距离阀值为3.5时,63个家系明显地被划分为4大类,当距离阀值为2.5时,可以进一步细分为8个亚类。第1大类包括14个家系,以来自湖北的家系为主;第2大类包括17个家系,以来自湖南和贵州的家系为主;第3大类包括17个家系,以来自广东和福建的家系为主;第4大类包括15个家系,以来自福建的家系为主。家系的分类与家系的地理分布基本一致,说明根据表型性状对杉木第一代种子园自由授粉子代家系进行分类是可行的。家系的分类将为杉木优良材料的选择、育种群体的构建、人工控制授粉以及长期遗传改良策略的制定提供参考。根据分类结果,对家系的变异系数进行合并后求平均值,发现不同类和亚类的变异系数值相差较大,不同亚类变异系数的变化范围为16.2%~24.8%。来自湖北咸宁家系的变异系数较大,来自福建三明和建阳家系的变异系数较小。     

杉木生长,材性兼优种源选择的研究

经对杉木中心产区优良种源的中间试验研究表明,种源间生长与木材基本密度性状有一定差异,根据对１２年木材基本密度性状和９年材积生长性状的测定结果,初步选出广西那坡,贵州锦屏,贵州榕江等生长,材性兼优的种源。其木材基本密度与广西融水优良种源相近,材积生长比融水种源增加４７．０％￣８３．６％,遗传增益达１３．４１％￣２３．８６％。     

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.     

湖南杉木人工林近自然经营问题探讨

德国人工林在19世纪,与湖南杉木人工林有相似之处,采用单一树种营造大面积人工林,造成地力消耗很大,无法实现林木的可持续利用。本文从杉木经营历史,分析了现有栽培制度下的炼山、幼林抚育、轮伐期短、林分结构单一等现状所导致的杉木人工林生产力下降、林地地力衰退。本研究引进德国森林近自然经营理念及原则改造杉木人工林,分别对杉木幼林、中林、成林进行第1代目标树经营,为第2代目标树形成创造有利条件,使林地地力得到恢复,达到可持续经营的目的,同时获得较大经济效益。     

Application of near infrared spectroscopy for authentication of <Emphasis Type="Italic">Picea abies</Emphasis> seed provenance

Authentication of seed provenance is an importance issue to avoid the negative impact of poor adaptation of progenies when planted outside their natural environmental conditions. The objective of this study was to evaluate the potential of near infrared (NIR) spectroscopy as rapid and non-destructive method for authentication of Picea abies L. Karst seed provenances. For this purpose, five seed lots from Sweden, Finland, Poland and Lithuania each were used. NIR reflectance spectra were recorded on individual seeds (n = 150 seeds × 5 seed lots × 4 provenances = 3000 seeds) using XDS Rapid Content Analyzer from 780 to 2500 nm with a resolution of 0.5 nm. Classification model was developed by orthogonal projection to latent structures-discriminant analysis. The performance of the computed classification model was validated using two test sets—internal (the same seed lots as the model but excluded during model development; n = 600 seeds) and external (seed lots not included in the model; n = 1158 seeds). For the internal test, the model correctly recognized 99% of Swedish, Finnish and Polish samples and 97% of Lithuanian seeds. For the external test samples, the model correctly assigned 81% of Swedish, 96% of Finnish, 98% of Lithuanian and 93% of Polish seeds to their respective classes. The mean classification accuracy was 99 and 95% for internal and external test set, respectively. The spectral differences among seed lots were attributed to differences in chemical composition of seeds, presumably fatty acids and proteins, which are the dominant storage reserves in P. abies seeds. In conclusion, the results demonstrate that NIR spectroscopy is a very promising method for monitoring putative seed provenances and in seed certification.     

Nondestructive estimation of wood chemical composition of sections of radial wood strips by diffuse reflectance near infrared spectroscopy

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.     

Development of chemometric models based on near infrared spectroscopy and thermogravimetric analysis for predicting the treatment level of furfurylated Scots pine

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.