Relationship between molecular characteristics of soil humic fractions and glycolytic pathway and krebs cycle in maize seedlings

A humic acid (HA) isolated from a volcanic soil was separated in three fractions of decreasing molecular size (I, II and III) by preparative high performance size exclusion chromatography (HPSEC). The molecular content of the bulk soil HA and its size fractions was characterized by pyrolysis-GC-MS (thermochemolysis with tetramethylammonium hydroxide) and NMR spectroscopy. All soil humic materials were used to evaluate their effects on the enzymatic activities involved in glycolytic and respiratory processes of Zea mays (L.) seedlings. The elementary analyses and NMR spectra of the humic fractions indicated that the content of polar carbons (mainly carbohydrates) increased with decreasing molecular size of separated fractions. The products evolved by on-line thermochemolysis showed that the smallest size fraction (Fraction III) with the least rigid molecular conformation among the humic samples had the lowest content of lignin moieties and the largest amount of other non-lignin aromatic compounds. The bulk HA and the three humic fractions affected the enzyme activities related to glycolysis and tricarboxylic acid cycle (TCA) in different ways depending on molecular size, molecular characteristics and concentrations. The overall effectiveness of the four fractions in promoting the metabolic pathways was in the order: III>HA>II>I. The largest effect of Fraction III, either alone or incorporated into the bulk HA, was attributed to a flexible conformational structure that promoted a more efficient diffusion of bioactive humic components to maize cells. A better knowledge of the relationship between molecular structure of soil humic matter and plant activity may be of practical interest in increasing carbon fixation in plants and redirect atmospheric CO₂ into bio-fuel resources.     

Near Crack Line Elastoplastic Solution for an Eccentric Cracks Loaded by the Pore Water Pressure

By using near crack line analysis method and Mohr-Coulomb strength criterion,the elastic-plastic solution for near crack line of an eccentric cracks loaded by the pore water pressure under large scale yielding condition is analyzed.The elastic stress fields,the plastic stress field,the unit normal vector of the elastic-plastic boundary near the crack line,the elastic-plastic stress fields near crack line are identified.The change pattern of the length of the plastic zone and the pore water pressure is presented.Besides,the elastic-plastic analytical solution for an eccentric cracks loaded by the pore water pressure is obtained.     

Application of Wavelet Transform in the Prediction of Navel Orange Vitamin C Content by Near-Infrared Spectroscopy

This study was to search for an approach for rapid measurement of orange vitamin C （Vc） content. By using different decomposing levels of Daubechies 3 wavelet transform, the near-infrared spectra signals obtained from intact fruits of 100 navel orange samples were denoised, and the results of the predicted Vc contents for the corresponding samples determined by the reconstructed spectra after denoising were validated by means of PLS-CV （partial least squared-cross validation）. It was shown that the prediction effects verified by PLS-CV analysis varied when different wavelet transform decomposing levels were employed. At the wavelet decomposing level 4, the best prediction effect was obtained, with the correlation coefficient R between the prediction and true values being 0.9574 and the expected variance RMSECV being as low as 3.9 mg 100 g^-1. Furthermore, the 11 different approaches for the pretreatment of the near-infrared spectrum were compared. It was found that the calibration model established by PLS using spectra pretreated by wavelet transform denoising provided the best prediction for Vc content, exhibiting the highest correlation between the prediction and true values by cross validation. In conclusion, the near infrared spectral model denoised by means of wavelet transform can be used for accurate, rapid, and nondestructive quantitative analysis on navel orange Vc content.     

基于近红外光谱技术的大米掺伪定量判别

针对现在市场上常见的两种大米掺伪现象,利用近红外光谱技术结合化学计量学方法分别建立了大米中掺入低档米和掺入矿物油的定量分析模型。制配不同掺伪比例的大米样品,采集其近红外光谱,并选用标准正态变量变换、最大最小归一化、平滑和一阶导数4种方法对原始光谱进行预处理,分别结合偏最小二乘法建立PLS定量分析模型。通过对比建模结果选出的最优预处理方法是最大最小归一化,建立的掺低档米模型的校正集和预测集相关系数分别为0.9698和0.9845,均方根误差分别为8.66和6.46;掺矿物油米模型的校正集和预测集相关系数分别为0.9739和0.9888,均方根误差分别为0.106和0.0698。模型的预测精度和稳定性均很好,实现了对两种掺伪大米快速、准确的定量判别,为大米的品质监控提供了一种新的方法思路。     

近红外漫反射光谱法用于不同人参种子的鉴别

目的建立近红外漫反射光谱法鉴别不同种类的人参及西洋参种子。方法利用近红外光谱(NIRS)法对不同产地和种类的人参及西洋参种子样品进行聚类分析并建立了鉴别分析模型。结果聚类分析结果良好,所建立的鉴别分析模型能有效地判别人参及西洋参种子的类别。结论近红外光谱法能够实现人参及西洋参种子的快速无损分析,为区分不同种类的人参及西洋参种子提供了一个客观的评价方法。     

水稻蛋白质含量NIR模型适配范围的研究

【目的】比较不同类型样品建立水稻蛋白质近红外模型的效果和适配范围。【方法】通过对178份来自“II-32B/岳早籼6号”的重组自交系和496份水稻品种的近红外反射光谱的比较分析，选择其中59个株系和76份品种作为建模样品，采用偏最小二乘法建立基于品种、重组自交系和混合样品的3个蛋白质含量回归模型。【结果】经模型内部交叉验证和对模型外部重组自交系和品种样品的验证结果的比较分析，发现基于分离群体的模型因蛋白质含量范围较窄，样品来源较单一，适应范围仅局限于本群体内样品蛋白质含量预测，而品种和混合模型对群体和品种样品都表现出良好的适应能力，交叉验证决定系数大于0.90，外部验证决定系数大于0.89, 本试验可为近红外建模的样本集选择提供良好的指导意义。【结论】不同类型样品对建模效果有显著影响，品种模型和混合模型的适配范围显著大于群体模型，研究结果不能支持用背景变异较小的样品建立较高精度回归模型的设想。     

生物矿化合成木材-SiO2复合材料的XPS分析

利用生物矿化原理制备木材—SiO2复合材料,采用溶胶—凝胶法制备硅溶液,用不同质量分数的硅溶液对喜树进行浇灌和滴注试验。经过1个月的试验得到样品,利用光电子能谱仪(XPS)分析素材和SiO2复合材样品中硅、碳的质量比,证实喜树成功吸收硅元素,并且存活,植株根茎附近生长较好,枝叶较多,顶部附近枝叶较少。比较浇灌、滴注2种方法:①浇灌过程相对简单,树木对硅的吸收相对较少;使用质量分数越高的药品对树木进行浇灌,树木对硅的吸收越好。②滴注过程相对复杂,树木对硅的吸收相对较多;使用质量分数越高的药品进行滴注,树木对硅的吸收越好;但吸收不均匀,呈滴注孔口附近往树梢方向减少趋势。前期研究结果表明,对树木进行浇灌和滴注,药品硅的质量分数过高树木会死亡,过低则达不到要求,因此,最佳质量分数配制还有待于进一步研究确定。总的来说,利用生物矿化原理模拟木材—SiO复合材是可行的。     

磺酸基官能化介孔材料MSU的合成及其酸性研究

为解决涉及一些较大分子的反应之固体酸催化问题,以价格便宜的硅酸钠为主要原料合成了磺酸基官能化介孔材料MSU,并采用固体核磁共振(SSNMR)等技术研究了所合成材料(MSU-SO3H)的结构和酸性.结果表明,合成的磺酸基官能化的MSU具有规整的介孔结构,其总体酸性略弱于微孔分子筛HZSM-5.     

水稻籽粒直链淀粉含量非破坏性活体测定方法研究

对533份杂交稻和常规稻材料的糙米和精米直链淀粉含量进行化学分析,并结合近红外透射光谱数据,采用改进偏最小二乘法（MPLS）分别建立糙米、精米的直链淀粉含量（AC）预测定标模型,并对其进行内部和外部验证.结果表明,杂交稻糙米及精米模型的定标相关系数（RSQ）分别为0.873和0.922,常规稻糙米及精米模型的RSQ则分别为0.924和0.939,定标标准偏差（SEC）分别为1.100,0.956,1.537,1.547;内部交叉验证预测值和真实值之间的RSQ分别为0.866,0.901,0.892和0.921,外部验证的RSQ分别为0.9506,0.9352,0.9116,0.9180,所建模型的相关性较高,预测值与真实值之间的误差小.常规稻模型可应用于大量育种材料快速、无损的早代筛选,杂交稻模型可用于新组合直链淀粉含量的快速鉴定,促进稻米品质改良,提高育种效率.