Crystallity Change of Compressed Poplar Wood Treated by PF Resin

INTRODUCTIONWith the implementing of the Natural ForestryProtection policies in China, the plantation forestry willplay a much larger part in meeting the demand for wood.But the plantation wood, especially Poplar and Fir, havecommon properties of soft structure, low density andpoor processing. Generally speaking, these propertiescan be evidently improved by compressing. MasafumiInoue et al. (1991a, 1991b, 1990) had studied thesurface compression of coniferous wood. Their studiesshowed …     

带锯机杠杆压砣式张紧系统的研究

根据以前对带锯机杠杆压砣式张紧系统振动的分析,设计了一新型装置,并用试验进行了对比分析,证实采用改进后的杠杆压砣系统可大大降低锯条的振动。为改善带锯机的动态特性提供了一条有效的途径。     

液压传动技术在烟草打顶机上的应用

针对烟草中后期田间管理阶段的打顶及喷施抑芽剂时,作业人员劳动强度大、生产效率低,严重影响烟草产量和质量的现状,研制出高地隙三轮自走式全液压烟草打顶机。该机采用T型车架及高架式机体,液压驱动行走、转向、制动系统,以及液压操纵烟草打顶、喷施药剂系统。该打顶机液压系统传递功率大、结构紧凑、布置灵活,且易于实现无级调速及过载保护,便于控制、操作简便,可高效地完成烟草打顶及喷施药剂作业。     

灌木平茬机沙地通过性仿真研究

为研究灌木平茬机在科尔沁沙地的通过性能,基于ADAMS/ATV建立了其虚拟样机模型及符合沙地特性的平地、坡路、垂直障碍、凹坑、正弦路面等虚拟地形,进行了灌木平茬机在典型路面上行驶的仿真分析。结果表明,灌木平茬机能够平稳通过所建立的虚拟地形,在沙地上具有较好的通过性能,转向平稳。根据仿真结果确定灌木平茬机主动轮的最佳直径为280 mm、转向半径为0.75 m。     

稻草原料表面特性FTIR和XPS分析

运用红外光谱(IR)和X射线光电子能谱分析(XPS)法，考察了热磨处理对稻草表面特性的影响。结果表明：稻草秸秆内表面的活性基团数量和氧碳元素百分比都明显高于外表面；经热磨处理，稻草纤维表面的羟基、甲基、亚甲基等官能团含量显著增加，氧碳元素百分比相对秸秆表面有大幅度提高，证明热磨处理能增强稻草表面活性，为脲醛树脂稻草中纤板制造的技术可行性提供了依据。     

瓦楞纸板自动横切机控制系统设计

针对国内瓦楞纸板生产效率低、剪损大的缺点,研制开发了瓦楞纸板自动横切系统,详细分析了其工作原理、系统构成和功能实现.现场使用表明：该系统具有自动化程度高,切割精度高,产品成本低等优点.     

Investigating the effects of simulated transport vibration on tomato tissue damage based on vis/NIR spectroscopy

Visible and near infrared (vis/NIR) spectroscopy combined with chemometrics were investigated to evaluate the effects of simulated transport vibration levels on damage of tomato fruit. A total of 280 tomato samples were randomly divided into 5 groups; each group was subjected to vibration at different acceleration levels. A total of 230 samples (46 from each group) were selected as a calibration set; whereas 50 samples (10 from each group) were selected as a prediction set. Raw spectra, differentiation (the first derivative) spectra, extended multiplicative scatter correction (EMSC) processed spectra and standard normal variant combined with detrending (SNV–DT) processed spectra were used for calibration models. SNV–DT processed spectra had the best performance using for partial least squares (PLS) analysis. The PLS analysis was implemented to calibrate models with different wavelength bands including visible, short-wave near infrared (SWNIR) and long-wave near infrared (LWNIR) regions. The best PLS model was obtained in the vis/NIR (600–1600 nm) region. Using a grid search technique and radial basis function (RBF) kernel, four least squares support vector machine (LS–SVM) models with different latent variables (7, 8, 9, and 10 LVs) were compared. The optimal model was obtained with 9 LVs and the correlation coefficient (r), root mean square error of prediction (RMSEP) and bias for the best prediction by LS–SVM were 0.984, 0.137 and 0.003, respectively. The results showed that vis/NIR spectroscopy could be applied as a reliable and rapid method for predicting the effect of vibration levels on tissue damage of tomato fruit.     

The use of infrared spectroscopy and machine learning tools for detection of Meloidogyne infestations

Plant parasitic nematodes are generally soilborne pathogens that attack plants and cause economic losses in many crops. The infested plants show nonspecific symptoms or, often, are symptomless; therefore, diagnosis is performed by taking soil and root tissue samples. Here, we show that a combination of different infrared spectra analysis and machine learning algorithms can be used to detect plant parasitic nematode infestations before symptoms become visible, using leaves instead of roots and soil as samples. We found that tomato and guava plants infested with Meloidogyne enterorlobii produced different spectral patterns compared to uninfested plants. Using partial spectra from 1,450 to 900/cm as the "fingerprint region", principal component analyses indicated that after 5 (tomatoes) or 8 weeks (guava), plants with no visible symptoms of infestations were positively diagnosed. To improve the early detection response, we used machine learning modelling. A support vector machine (SVM) was used to obtain more robust, accurate models. The SVM model contained 34 support vectors, 17 for each level. The overall performance of the model was >97% and the total accuracy was significantly higher, demonstrating the absence of chance prediction. The best prediction of infestation was obtained at the second and fourth weeks for tomatoes and guavas, respectively, reducing the diagnostic time by half. The combined application of these techniques reduces the processing time from field to laboratory and shows enormous advantages by avoiding root and soil sampling.     

基于边缘检测和区域定位的玉米根茎导航线提取方法

基于玉米根茎图像信息，提出一种基于边缘检测和区域定位的玉米根茎导航线提取方法。首先，利用最大类间方差法自动分割2G-R-B灰度图像，得到二值化图像，结合形态学处理、位置/面积去噪方法提高二值化图像质量，对去噪图像按列累加得到列像素累加曲线；针对传统方法得到的特征点中伪特征点较多的问题，引入高斯滤波器平滑累加曲线，并运用极值法减少玉米根茎伪特征点的干扰，在提取玉米茎秆边缘直线时，提出基于最远茎秆成像宽度的双侧边缘判别思路，通过扫描每条边缘直线的四边形封闭邻域有效剔除伪边缘直线；最后，根据边缘直线二次定位玉米的根茎区域范围，并剔除伪特征点，采用最小二乘线性拟合方法准确提取导航线。试验表明，本文算法处理一幅1280像素×720像素图像耗时约236ms，特征点拟合准确率为92%。与传统方法相比，本文算法精度高、实时性好，在缺苗、杂草较多和株距不标准的情况下仍具有较强的鲁棒性。     

X射线荧光光谱法快速检测原料公干鱼中的镉

旨在建立一种基于X射线荧光光谱法快速检测原料公干鱼(原料鱼)中镉的方法。应用X射线荧光光谱法快速检测原料鱼初始样及干燥样中的镉含量,对快速检测与标准检测结果的相关性进行了分析;考察了对原料鱼进行快速干燥处理的可行性;采用原料鱼的标准测定值对X射线荧光光谱仪进行校正后,考察了快速检测方法的精密度、检测限、准确度等性能参数。结果表明:X射线荧光光谱法能准确测定原料鱼干燥样中的镉,检测限达0.088 mg/kg,线性范围为0.088~1.286 mg/kg,相对标准偏差低于10%。该快速检测方法测定单个样品只需40 min左右,可满足现场对原料鱼中镉的快速测定要求,为防控原料鱼食品中镉超标风险提供了一种高效的筛查手段。