天然林五角槭木材纤维长度的时间序列分析

为获得时间序列模型对天然林五角槭木材纤维长度的数据拟合与预测效果,以其径向变异规律为研究对象,采用时间序列模型中的自回归移动平均模型(ARIMA)进行数据拟合和中短期预测。研究结果表明,采用模型ARIMA(0,1,1)可以对天然林五角槭木纤维长度进行数据拟合与预测,模型拟合数据效果较好,5年短期预测精度高于10年和20年中期预测精度。     

木材首饰商品零售企业的ARIMA需求预测研究

本研究利用ARIMA模型能够通过对有限时间长度的历史销售数据分析而实现精度较高的短期性预测的特点,针对珍贵木材首饰零售企业的具有代表性的、随机性需求的首饰进行数据的序列平稳化过程处理,而后进行模型的识别、参数估计和假设检验,最后进行预测,以检验ARIMA模型预测的准确度。结果表明,针对该类木材首饰而建立的ARIMA预测模型,其模型拟合优度和白噪声等参数值均具有统计学意义,预测结果也证明其短期预测的准确度较高。而未来控制库存的核心是对商品将来的需求进行有效的预测,因此利用ARIMA模型短期预测精度高的优点,可以为木材首饰零售行业短期库存控制提供决策和依据。     

山桂花人工林木材基本密度和纤维长度变异规律的研究

木材材性是林木育种方面的一项重要指标，其大小直接影响到木材制品的质量和利用，通过对山桂花人工林不同部位木材基本密度、管胞长度、生长轮宽度的变异分析，建立山桂花人工林木材材性变异规律的数学模型，圆盘基本密度与生长年轮的回归方程，纤维长度与生长年轮的回归方程以及基本密度、纤维长度的预测曲线方程。与实测值比较接近，预测曲线与实际变异趋势比较一致，其平均相对误差为1．94％、0．41％，相对标推误差为3．41％、2．12％，采用幼龄材基本密度能够有效地预测成熟材的材性。     

人工林红松木材生物轮密度动态模型建立与预测

本文根据人工林红松木材生长轮密度变异特点，采用时间序列分析法，建立了人工林红松木材生长轮密度的动态模型，对木材生长轮度进行近期预测，预测结果良好，此研究结果实现了木材生长轮内的材质预测，为人工林红松的定向培育提供理论依据。     

中国木材进口量走势及波动分析

文中采用2003年1月至2020年6月中国海关数据，研究中国针叶材和阔叶材进口量长期走势及短期波动；基于ARIMA模型，提出了拟合木材进口数据的一般分析流程，主要步骤包括数据呈现及方差平抑、数据平稳化处理、自相关检验、滞后项网格化搜索、残差项检验、预测分析等。研究发现:拟合针叶材进口最好的模型为ARIMA（1，0，1）（2，1，1）₁₂，预计针叶材进口返回长期趋势的时点不早于2021年3月；对阔叶材进口解释力最强的模型为ARIMA（0，1，2）（0，1，3）₁₂，2020年下半年阔叶材进口仍会延续总体下行的趋势，但于2021年达到新稳态；2020年木材总进口量估计下降1 000万m3，向1亿m3的关口回落。中国进口木材市场格局正由以趋势性增长为主转变为以波动性平衡为主，加强预测、做好预案有利于降低市场系统性风险。     

低山侧柏人工林单木冠幅预测模型及精度评价

以北京西山林场低山区调查的89块侧柏人工林样地数据为基础,采用一元线性回归模型、多元线性回归模型、其它模型对不同立地条件下的侧柏单木冠幅预测模型进行研究。结果显示:低山阳坡的侧柏人工林单木冠幅分布范围大于低山阴坡的,且低山阳坡的平均冠幅为3.05m也显著高于阴坡的2.83m;多元线性回归模型对低山阳坡和低山阴坡的侧柏人工林单木冠幅生长拟合精度最高,R2值分别为0.751和0.770;采用未进行建模的数据对筛选出的多元线性回归模型进行T检验,发现实测值和预测值差异不显著,残差服从正态分布,拟合效果良好。研究结果可对低山区侧柏人工林的冠幅生长动态进行精确预测,为侧柏人工林经营管理的数字化、动态化、精确化提供理论依据。     

长白山林区天然次生林胡桃楸的适宜生长空间

利用次生林主林层胡桃楸34株平均木(胸径为11.0～39.1 cm)的树干解析数据,结合反映植物生长空间的冠幅,进行5,10和15年抚育间隔期的单株材积定期生长量、林分蓄积增长量与生长空间关系的研究,建立不同抚育间隔期胡桃楸胸径与适宜生长空间关系的模型;利用林冠下层27株胡桃楸平均木(胸径为4.6～14.3 cm)的树干解析数据,评价适宜生长空间模型应用于被压状态胡桃楸时的生长促进效果.结果表明:1)3参数S型曲线模型和二项式模型分别能够很好反映胡桃楸前5,10和15年间单株材积定期生长量、林分蓄积增长量与冠幅的关系;2)不同抚育间隔期胡桃楸胸径与适宜生长空间关系的模型为幂函数模型(y=a×x~b);3)对数函数模型(y=a×ln(x)+b)能显著反映适宜生长空间下胸径与材积定期生长量的关系;4)适宜生长空间下胡桃楸5,10和15年材积定期生长量至少比生长空间受限条件下的林木提高97.8%,114.4%和128.5%.采用5,10,15年抚育间隔期时,不同胸径胡桃楸的适宜生长空间分别是相应胸径的0.256 6～0.368 7,0.344 1～0.447 1和0.449 1～0.504 6倍.     

樟树人工林株间株内材性变异及其材性预测的研究

樟树人工林株内纤维长度径向变异由髓心向外递增，而后趋于稳定；木材基本密度髓心处稍大，由髓心向外先稍递减而后递增，再趋于稳定；纤维长度和基本密度性状与生长轮年龄关系模型可用来预测其性状值。樟树木材幼龄期约为7－9a，株内细幼龄材基本密度较成熟材小1．0％－9．9％，株内幼龄材与成熟材基本密度差异多不显著；其浸提物含量幼龄材与成熟材之间差异不显著。纤维长度株内变异系数大于株间，木材基本密度均值和浸提物含量二性状则是株间变大于株内变异。生长速度对樟树木材纤维长度、基本密度、浸提物含量等性状影响不显著。     

天然林五角槭木材材质径向变异规律初探

以天然林五角槭的木材解剖性质为研究对象,分析其株内木材材质径向变异规律,对幼龄材与成熟材进行初步界定。结果表明:细胞壁厚、壁腔比、胞壁率和径、弦向直径幼龄期波动较大,成熟期波动减弱;木纤维长度符合Pan-shinⅠ模型,幼龄材拟合度较好;组织比量符合y=aebx变异模型;幼龄材和成熟材的界定年限为28～33a之间。     

香叶树人工林木材纤维形态特征的研究

通过对香叶树人工林木材纤维形态的测定表明：香叶树人工林木材在1～3 a间木纤维长度属短;在3～18 a间木纤维长度属中等长度。香叶树人工林木材在1～5 a间木纤维长宽比较小,在6～18 a间木纤维长宽比大于45。     

银杏落叶期叶片NDVI值2种拟合方法比较

【目的】对银杏Ginkgo biloba L.落叶期(9—12月)的叶片进行连续定期定点的高光谱测量,计算出能代表其生长状况和营养信息的高光谱参量NDVI值,通过选用两种不同的曲线拟合方法对其NDVI值进行宏观上的以时间为自变量的曲线拟合,选出最优拟合方法,更好地了解银杏落叶期叶片光谱特征参量NDVI值的变化趋势,从而更有效地对其进行决策和控制,为植被的大尺度遥感动态监测提供方法参考。【方法】利用SVC HR-1024I全波段地物光谱仪,选取三株健康、生长环境相同、长势相近的中龄银杏为叶片采集对象,对其落叶期冠层叶片进行定期定点定方位的高光谱观测。对获取的高光谱原始数据进行数据筛选与预处理后,通过计算得出叶片的NDVI值,分别采用二次函数拟合法和ARIMA时间序列拟合法对落叶期叶片的NDVI值进行曲线拟合,并对两种拟合方法的拟合结果进行比较,选出最适合银杏叶片落叶期NDVI值的拟合方法。【结果】二次函数拟合结果为NDVI=-0.0221T2+0.0547T+0.711,决定系数R2为0.926,但因拟合结果t值不显著,样本结果随机性大,不具广泛性;ARIMA时间序列拟合中ARIMA(2,1,2)模型估测结果与实际情况接近,R2为0.811,拟合效果较好。【结论】ARIMA时间序列拟合方法比二次行数拟合方法更适用于对银杏落叶期叶片的NDVI值进行拟合。     

桉树材性性状近红外预测模型的建立

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。     

ARIMA MODEL ON WOOD PROPERTIES VARIATION PATTERN OF KOREAN LARCH

INTRoDUCTIONItwasfOundthatthegoOdnssoffitwasnotgOodandthecOefficientofcorrelahonwaslowwhileuslngthemethodoflinearregressionanalysistoanalysesthewoodgrOwthnngvanahonpatternofPlantedLanxolgensis.ThewoodpowthringProPenieslnc1udesguwthringdenSty,grOWthringwidthandlatewoodpercentage.AslthewoodPrOpenies'parameters,mentionedasabove,thevariahont6ndencywassindlarwiththeresultsofPreviousresearch,butthedopeeofdjssociahonofadjacenttestpointswasbigrelahvely,andthevanahonten-dencywasinduencedbyran…     

楸树叶面积与叶形指数的回归分析

本实验采用数码相机拍照,利用CAD．图像处理方法得到楸树叶片的面积,并同时测量叶长、叶宽计算出长宽比、长乘宽,通过逐步回归的方法对与叶面积有关的指标进行筛选。用最后得到的最能反映叶面积的指标长乘宽,建立不同叶形的叶片长乘宽与叶面积的一元线形回归预测模型方程,分别是倒心形Y=0．652x＋16．041,决定系数R2=0．7221,水滴形Y=0．5058x＋112．47,决定系数R2=0．4994,三裂Y=0．3211x＋155．98,决定系数R2=0．6006,分析认为可将叶长乘宽作为重要的叶形指数,进行楸树生长等相关研究。     

Eucalyptus camaldulensis density and fiber length estimated by near-infrared spectroscopy

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.     

Prediction of basic wood properties for Norway spruce. Interpretation of Near Infrared Spectroscopy data using partial least squares regression

This work was undertaken to investigate the feasibility of using near infrared spectroscopy (NIR) and partial least squares regression (PLS) as a tool to characterize the basic wood properties of Norway Spruce (Picea abies (L.) Karst.). The wood samples originated from a trial located in the province of Västerbotten in Sweden. In this trial, the effects of birch shelterwoods (Betula pendula Roth) of different densities on growth and yield in Norway spruce understorey were examined. All Norway spruce trees in each shelterwood treatment were divided into three growth rate classes based on diameter at breast height (1.3?m) over bark. Five discs were cut from each tree (i.e. from the root stem, and at 20%, 40%, 60%, and 80% of the total height). The discs from 40% tree height were used (i.e., where the largest variations in annual ring widths and wood density were found). A total of 27 discs were selected. The discs were used for measuring annual ring widths, wood density, average fiber length and the fiber length distributions. Milled wood samples prepared from the discs were used for recording NIR spectra. PLS regression was used to generate prediction models for the wood properties (Y-matrix) and NIR spectra (X-matrix) as well as between the wood properties (Y-matrix) and the fiber length distributions (X-matrix). One set of models was generated using untreated spectra and fiber length distributions. For a second set of models the structure in the X-matrix, which was orthogonal to the matrix described by the wood properties, was eliminated using a soft target rotation technique called orthogonal signal correction (OSC). The PLS model obtained using “raw” untreated NIR spectra and fiber length distributions had a poor modeling power as evidenced by the cumulative Q² values. For the PLS models based on untreated NIR spectra the cumulative Q² values ranged from a minimum of 16% (wood density) to a maximum of 46% (no. of annual rings). Orthogonal signal correction of the X-matrix (NIR spectra or fiber length distributions) gave PLS models with a modeling power corresponding to cumulative Q² values well in excess of 70%. The improvement in predictive ability accomplished by the OSC procedure was verified by placing four of the 27 observations in an external test set and comparing RMSEP values for the test set observations without OSC and with OSC.     

Demarcation of juvenile and mature woods of planted Chinese fir and its wood quality prediction

lntroductionChinesefir(Cunntwh8mi8IanceoIat8(Lamb.)Hook)isaveryimportantspeciesofwoodresourcesinSouthernChina.TheheredityandameliorationonChinesefirareaIwayspaidgreatattention.However,inthepast,thefocaIpointOftheworkonheredityandamelioF8tionwashowtoCuItivatetheChinesefirwithcharaCtersoff8stgrowth,goodfigure,wideadaPt-abilityandStrongdiseaseresistance.LittleworkwasdoneonameIior8tionofwoodquaIity.AlongwiththecompositionchangeoftheforeStresourcesinChina,Chinesewoodindustryismoredependen…     

人工林毛白杨木材解剖构造与染色效果相关性的研究

为探讨木材构造和木材染色效果之间的相关性变化规律，本研究测字５株３４块人工林毛白杨 的解剖构造及其木材染色效果，对二者的相关性进行了多元回归分析。结果表明，毛白杨木材染色效果与解剖因子之间有一定的相关关系，各染色效果指标与木材解剖因子间的复相关系数在０．４８３６－０．７９９８之间，采用比较多元回归分析标准回归系数的方法，确定了影响毛白杨木材染色效果的主要解剖因子为导管比量、木纤维比量和木射线量等因子。     

Study on Glulam Process

INTRODUCTIONGlulam (namely glued laminated lumber) is a kind ofproducts that are assembled by sawn lumbers or smallsquares laminated in grain directions and glued in thedirection of thickness, width and length with adhesives.Not only does glulam possess the same property asnatural wood does, but also can avoid some defects,such as warping, distortion, split, etc. As one kind ofthree main engineered wood products as laminatedveneer lumber (LVL) and I-beam, glulam is widely usedin construc…