近红外光谱分析技术应用于植物叶片研究综述

近红外光谱技术（Near Infrared Spectroscopy,NIRS）作为 20 世纪 80 年代后期迅速发展起来 的一项检测技术,已被广泛应用于许多植物的各个组织和各种成分的分析。文章综述了该技术在植物叶 片研究上的应用进展,包括基于叶片特征的植物种类鉴别、植物叶片病虫害诊断、育种材料选择、叶片 内含物质含量测定等 4 个方面,并对近红外光谱检测技术的应用于植物叶片研究前景进行了展望。     

Assessment of tolerance of willows to saline soils through electrical impedance measurements

One-year-old potted clone plants of four willow species (Salix matsudana × alba, S. babylonica, S. psammophila and S. cheilophila) were cultivated and irrigated with saline solutions of different concentrations, while their electrical impedance spectroscopy (EIS) parameters and other physical parameters were monitored. The results indicate i) that under salt stress, height and basal diameter of all species are inhibited, and ii) that relative conductivity of cellular exudates increases while intracellular resistance (ri) and extracelluar resistance (re) drop. Both ri and re were positively correlated with height growth and basal diameter while they were significantly and negatively correlated with electric conductivity. The concentration of Na + in the shoots of willows was negatively correlated with both ri and re , whereas the concentration of K+ in the shoots was positively correlated with both ri and re . Hence, electrical impedance spectroscopy is a reliable tool for evaluating the capacity of willow species for tolerance to saline soils, with r i as the most accurate parameter.     

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。     

婴幼儿配方奶粉中8种常微量元素分析方法的研究

采用湿法消解(电热板消解法)、干式消解法(灰发化)和微波消解法对婴幼儿乳粉样品进行前处理,建立电感耦合等离子体发射光谱仪(ICP-OES)同时测定待测样品中8种常微量元素的方法。结果表明,采用微波消解-电感耦合等离子发射光谱仪测定婴幼儿乳粉样品中8种常微量元素的方法各元素的平均含量较高,相对标准偏差(RSD)最小,且小于2.05%。该方法对质控样品中各元素的相对标准偏差(RSD)均小于2%,回收率在84.6%～103.5%。     

Impact of sampling and storage technique,and duration of storage,on the composition of fresh grass when analysed using near‐infrared reflectance spectroscopy

The objective of this study was to examine the effect of sampling technique (pluck or cut), storage duration (immediate analysis, 24‐h or 48‐h), storage temperature (ambient or chilled) and storage conditions (air present, air excluded or breathable) on the composition of fresh grass sampled from a sward managed to simulate grazing. Treatments were repeated across four sampling dates, with grass samples stored in grip seal bags prior to analysis using near‐infrared reflectance spectroscopy. Grass sampled by ‘pluck’ had a higher crude protein and ME content, and a lower acid detergent fibre (ADF) content, compared to that sampled by ‘cut’. Grass stored for 48 h had a lower water soluble carbohydrate (WSC) and ME content and a higher ADF content than for immediate analysis. Samples stored for 24 h did not differ from immediate analysis. Grass stored at ambient temperature had a lower WSC and ME content compared to immediate analysis. Grass stored under ‘breathable’ conditions had a lower ME content and higher ADF content than immediate analysis or samples stored with air present or air excluded. It is recommended that grass for analysis should be sampled by cutting, stored chilled (4°C) in a sealed bag to minimize exposure to oxygen and analysed within 24 h of harvest.     

Q235钢表面环氧复合涂层在变电站环境中的腐蚀行为分析

以Q235钢表面涂覆的环氧富锌底漆,水性聚氨酯中间漆,银灰环氧磁漆构成的环氧复合涂层为对象,研究变电站环境中涂层自然暴露18个月后的腐蚀行为,并将其与用5% NaCl溶液浸泡250天处理的涂层的腐蚀行为做对比。采用电化学阻抗谱（EIS）研究环氧复合涂层试样的电化学腐蚀行为,评价环氧复合涂层的耐候性与耐盐性,并通过FT-IR表征涂层浸泡和自然暴露过程的结构变化。结果表明,环氧复合涂层试样在5% NaCl溶液中浸泡250 d后,涂层阻抗从3.967×10⁹ Ω·cm²降至9.780×10² Ω·cm²,其失效机制为腐蚀介质通过涂层微孔逐渐渗入涂层中形成微观电通路,导致涂层孔隙率逐渐增大,基底材料腐蚀加速;自然暴露试验18个月的试样,其涂层阻抗为2.708×10⁶ Ω·cm²,防护性良好。     

原子吸收法测定荒漠肉苁蓉中微量元素的含量

采用火焰原子吸收分光光度法和石墨炉法对荒漠肉苁蓉样品中的金属元素Fe、Cu、Zn、Mg、Ca、Pb、Sn含量进行了测定.结果表明,此方法简单,精密度和灵敏度高,回收率为98.90%～101.27%,结果可靠.荒漠肉苁蓉中Mg、Ca、Fe、Zn含量较高.     

Comparison of Near Infrared Spectroscopy Models for Determining Protein and Amylose Contents Between Calibration Samples of Recombinant Inbred Lines and Conventional Varieties of Rice

The near infrared spectra of 178 recombinant inbred lines （RILs） from the cross of Ⅱ-32B/Yuezaoxian 6 （YZX6） and 511 varieties in rice were acquired. A total of 80 RILs and 96 cultivars were selected as modeling samples by comparing the spectra similarity primarily. Three partial least square （PLS） regression models were developed, based on the RILs （RIL-model）, the varieties （Var-model） and their mixture （Mix-model）, for protein content （PC） and amylose content （AC）, respectively. Cross validation and outer prediction showed that the models were largely influenced by the range and distribution of modeling samples. The regression model of PC based on the cultivars and the model of AC based on RILs had higher coefficient of determination （r^2 ≥ 0.9） and lower root mean square error of cross validation （RMSECVs）. The disadvantages of RIL samples for PC model and variety samples for AC model were probably caused by the narrow range of variance. Aberrant predictions were obtained for outer sample with PC or AC outside the range or within the distribution gap of modeling samples. The Mix-models gave more reliable prediction as the distribution of RIL and variety modeling samples were complementary to each other.     

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。     

基于红外光谱概率神经网络的诃子产地鉴别

利用傅里叶变换红外光谱,测定了不同产地诃子(Terminalia chebula Retz.)样品的红外光谱图.采用常规预处理方法和小波变换对红外光谱原始数据进行了预处理,并采用主成分分析进一步压缩光谱数据,前3个主成分的累积贡献率为98.054％.以前3个主成分作为网络输入,诃子产地类别作为网络输出,建立了概率神经网络,同时对建立该网络模型的扩展常数进行了分析.模型分析表明,建立的网络模型能够对40个诃子样品进行产地鉴别,红外光谱法结合神经网络可作为中药材产地分类鉴别的一种新的现代化方法.