逆最小二乘法—导数谱同时测定锌,镉,汞和铅

本文研究了在碱性介质中，ＣＰＢ存在下，ｍｅｓｏ－四（４－三甲铵基苯）卟啉与Ｚｎ（Ⅱ），Ｃｄ（Ⅱ），Ｈｇ（Ⅱ）和Ｐｂ（Ⅱ）络合物的导数光谱，提出了应用逆最小二乘法（或称ＣＰＡ－矩阵法）原理对导数光谱进行解释，同时测定四组分的方法。应用本法对合成样品和水进行分析，结果满意。     

分子轨道图形理论的应用（Ⅲ）—估算Eπ的断键法

分子轨道图形理论的应用（Ⅲ）──估算Ｅ_π的断键法赵洪刚，杨开海，王长生，张继才，曹阳（辽宁师范大学化学系，大连，１１６０２２）（苏州大学化学系，苏州）关键词π电子总能量，矩，分子拓扑在分子轨道图形理论中，对一般的应用，π电子总能量Ｅπ的近似表达式就?..     

催化动力学光度法测定痕量锇——中性红—氯酸钾—锇（Ⅷ）—砷（Ⅲ）体系

催化动力学光度法测定痕量锇—中性红－氯酸钾－锇（Ⅷ）－砷（Ⅲ）体系唐宁莉傅明来（桂林工学院应用化学系，桂林，５４１００４）利用锇对溴酸钾氧化中性红而建立的催化光度法测定锇，选择性较好，但需控制反应温度为３０℃，操作较严格，应用受到限制．我们用氯酸钾...     

毛细管电泳的原理及应用（第二讲）毛细管电泳的原理及应用

毛细管电泳的原理及应用（第二讲）毛细管电泳的原理及应用罗国安，王义明（清华大学生命科学与工程研究院，清华大学化学系北京１０００８４）１概述毛细管电泳（ＣＥ）除了比其它色谱分离分析方法具有效率更高、速度更快、样品和试剂耗量更少、应用面同样广泛等优点外，...     

关于开展材料成分、化验（检验）人员职业资格考核培训通知

由国家质量技术监督局职业技能鉴定指导中心主办、南京计量测试技术成果应用开发中心承办的材料成分、化验（检验）人员职业资格考核培训即将在南京市开班。授课以应用为主线，理论为基础，内容实用，取材广泛，涵盖材料成分，化验（检验）应知应会的全部基础专业知识。     

2006年《中国无机分析化学文摘》征订启事

由国家质量技术监督局职业技能鉴定指导中心主办、南京计量测试技术成果应用开发中心承办的材料成分、化验（检验）人员职业资格考核培训即将在南京市开班。授课以应用为主线，理论为基础，内容实用，取材广泛，涵盖材料成分，化验（检验）应知应会的全部基础专业知识。     

应用逐步多元线性回归方法研究α，β－双唑酯类农药的构效关系

应用逐步多元线性回归方法研究α，β－双唑酯类农药的构效关系刘艾林，迟翰林（中国医学科学院，中国协和医科大学药物研究所，北京１０００５０）赖城明，林少凡，张金碚（南开大学中心实验室，天津３０００７１）彭永冰，刘晔伟（南开大学元素有机化学研究所，天津３０...     

应用FTIR光谱研究不同取代苯胺对O－乙基－N－异丙基（取代硫脲基）硫代磷酰胺酯生成反应的影响

应用ＦＴＩＲ光谱研究不同取代苯胺对Ｏ－乙基－Ｎ－异丙基（取代硫脲基）硫代磷酰胺酯生成反应的影响何兰龄，赖城明，林，徐谨民，王永泰，杨华铮，吴烨（南开大学化学系，天津，３０００７１）（南开大学中心实验室）（南开大学元素有机化学研究所）关键词ＦＴＩＲ，取...     

CmⅠ奇宇称光谱能级的模式识别研究

应用新的模式识别方法PCA－BPN（PrincipalComponentAnalysis－BackPropagationNetwork）指认CmⅠ奇宇称未知能级，支持了前人应用传统的KNN（KNearestNeighbors）等模式识别方法及对传神经网络方法（CounterPropagationNetwork，CPN）对大部分谱线的指认，进一步确认了这些组态的归属；鉴别了KNN等与CPN不同的预报结果，纠正CPN的某些错误分类，并以可视非线性映照分类器加以佐证     

AES法和AAS法测定食品、药物中微量元素的进展

综述了80年代以来原子发射光谱（AES）法和原子吸收光谱（AAS）法在食品和药物中微量元素分析的应用进展，内容包括，样品的预处理和进样技术，ICP-AES法和其他AES法。FAAS法，GFAAS法，HG-AAS法和冷蒸气AAS法等方面的应用及发展状况。     

水质监测中总磷无损的近红外光谱分析研究

本文对天然水样的近红外光谱与水样总磷（TP）含量进行了相关性研究,并建立了水质总磷的近红外光谱（NIRS）分析方法。结果表明：NIRS方法建立的定量分析模型所得TP含量与国标法得到结果的相关性达到0.908,并且在显著性水平大于0.05的条件下对NIRS方法与国标法的测定结果进行t检验,二者无显著性差异,说明了NIRS方法定量分析地表水中低含量总磷的可行性。     

近红外光谱分析技术在快速分析上的应用

简要介绍了近红外光谱的原理、特点,综述了近红外光谱在农业、食品、制药、石油化工、高分子等领域快速分析上的研究及应用现状,并对近红外光谱的应用前景进行了展望．     

我国油料产品品质的近红外光谱快速检测技术研究进展

近红外光谱技术是一种快速无损检测技术,具有操作简单、检测成本低、无需化学试剂、绿色环保,以及可实现多品质参数同步检测等优点。该文综述了我国油料和食用植物油品质的近红外光谱速测技术研究进展,包括油料含油量、粗蛋白含量、脂肪酸含量等品质指标,食用油的理化指标,以及脂肪酸和食用油的真实性鉴别,并对油料产品品质的近红外光谱速测技术的发展前景进行了展望。     

Rapid Determination of Betulin in Betula platyphylla Outer Bark Using Near-Infrared Spectroscopy

A simple, rapid, and nondestructive method for the determination of betulin in the outer birch bark was developed using near infrared spectroscopy (NIRS). NIRS data of the outer birch bark collected throughout the year was preprocessed and analyzed by principal component analysis, which led to clear discrimination of the samples according to their harvest times. The reference content of betulin, a major constituent of the outer birch bark, was determined using ultra performance liquid chromatography with a diode array detector (UPLC-DAD). The optimized and validated analytical conditions of UPLC-DAD provided better separation and faster analysis time compared to a conventional HPLC method. Betulin content also showed seasonal variation and was higher in the samples collected during the summer season. Partial least squares calibration techniques were employed to estimate the relationship between the NIRS data and betulin contents. The spectral data showed high correlation coefficients (over 0.700) with betulin content. These results indicate that NIRS combined with UPLC can be used to determine the quality and to quantify the betulin content of the outer birch bark.     

Comparison of different chemometric and analytical methods for the prediction of particle size distribution in pharmaceutical powders

This work compares the estimation of the particle size distribution of a pharmaceutical powder using near-infrared spectroscopy (NIRS), powder flowability properties, and components concentration. The estimations were made by considering the former data blocks separately and together using a multi-block approach. The powders were based on a formulation of paracetamol as the pharmaceutical active ingredient. The reference method used to determine particle size distribution was sieving. Partial least squares methods were used to estimate the multivariate regression models, and the results were compared in terms of figures of merit. It was shown that the partial least squares methods gave similar prediction errors. Regarding the data blocks used, the NIRS block was proven the most advantageous to estimate the particle size distribution. The prediction error of the NIRS block was similar to the other data blocks with additional advantages such as less generalization problems and the possibility of its use to predict additional physical and chemical properties with an improvement to analysis time. The multi-block approach produced the worst results but nevertheless allowed a deeper understanding of the individual contributions of the data blocks in the prediction of the particle size distribution.     

Identification of counterfeit drugs using near-infrared spectroscopy

This work was aimed at the investigation of the use of near-infrared spectroscopy (NIRS) for the identification of counterfeit drugs. The identification is based on the comparison of the NIR spectrum of a sample with typical spectra of the authentic drug using multivariate modelling and classification algorithms (PCA/SIMCA). Initially, NIRS was evaluated for spectrum acquisition of various drugs, selected in order to observe the diversity of physico-chemical characteristics found among commercial products. The parameters which could affect the spectra of a given drug (especially if presented in solid form) were investigated and the results showed that the first derivative can minimise spectral changes associated with tablet geometry, physical differences in their faces and position in relation to the probe beam. The power of NIRS in distinguishing among similar pharmaceuticals was demonstrated and a protocol is proposed to construct a multivariate model and to include it in a library allowing testing for drug authenticity. The methodology was evaluated with real samples of counterfeit drugs and was able to recognise all those presenting changes in composition as false. The results show unequivocally the potential of NIRS for rapid, on-site and non-destructive identification of counterfeit pharmaceuticals.     

Development of Near-Infrared Reflectance Spectroscopy Models for Quantitative Determination of Water-Soluble Carbohydrate Content in Wheat Stem and Glume

Water-soluble carbohydrate (WSC) reserved in stem is an important agronomic trait for crop improvement. The intact samples and pieces of chipped samples were employed to determine WSC content by near-infrared reflectance spectroscopy (NIRS). Three NIRS models were developed to predict WSC content in wheat stem lower internode, upmost internode, and wheat glume, respectively. Moreover, a mixed model was developed for WSC quantitative analysis in the mixed sample of the three wheat organs. Statistics analysis indicated that the four models showed a high determination coefficient (R² ≥ 0.97) and ratio of standard deviation to RMSECV (RPD ≥ 5.99). The NIRS models would allow rapid and high throughout assessments and selections of WSC contents in wheat genetics and breeding programs.     

近红外光谱法快速测定附子中6个生物碱的含量

应用近红外光谱(NIRS)技术结合偏最小二乘(PLS)和最小二乘支持向量机(LS-SVM)建立了附子中多指标成分的快速无损检测方法.选取38批样品建立了同时测定附子样品中6种成分含量的高效液相色谱(HPLC)方法;通过采集附子样品的NIRS图,分别采用PLS和LS-SVM建立了各个成分HPLC测定值与NIRS图的定量校...     

Revealing the Effect of Heat Treatment on the Spectral Pattern of Unifloral Honeys Using Aquaphotomics

In this study we aimed to investigate the effect of heat treatment on the spectral pattern of honey using near infrared spectroscopy (NIRS). For the research, sunflower, bastard indigo, and acacia honeys were collected from entrusted beekeepers. The honeys were not subject to any treatment before. Samples were treated at 40 °C, 60 °C, 80 °C, and 100 °C for 60, 120, 180, and 240 min. This resulted in 17 levels, including the untreated control samples. The 5-hydroxymethylfurfural (HMF) content of the honeys was determined using the Winkler method. NIRS spectra were recorded using a handheld instrument. Data analysis was performed using ANOVA for the HMF content and multivariate analysis for the NIRS data. For the latter, PCA, PCA-LDA, and PLSR models were built (using the 1300–1600 nm spectral range) and the wavelengths presenting the greatest change induced by the perturbations of temperature and time intervals were collected systematically, based on the difference spectra and the weights of the models. The most contributing wavelengths were used to visualize the spectral pattern changes on the aquagrams in the specific water matrix coordinates. Our results showed that the heat treatment highly contributed to the formation of free or less bonded water, however, the changes in the spectral pattern highly depended on the crystallization phase and the honey type.     

Non-linear regression methods in NIRS quantitative analysis

Due to its speed and precision, near-infrared reflectance spectroscopy (NIRS) has become a widely used analytical technique in many industries. It offers, moreover, a number of other advantages which make it ideal for meeting current demands in terms of control and traceability: low cost per sample analysed; little or no need for sample preparation; ability to analyse a wide range of products and parameters; a high degree of reproducibility and repeatability. NIRS can be built into in-line processes, and - since no reagents are required - produces no waste. However, the major drawback to the use of NIRS for its most traditional application (the generation of prediction equations) is that it is a secondary method, and as such needs to be calibrated using a conventional reference method. For quantitative applications, calibration involves ascertaining the optimum mathematical relationship between spectral data and data provided by the reference method. The model may be fairly complex, since the NIRS spectrum is highly variable and contains physical/chemical information for the sample which may be redundant. As a result, multivariate calibration is required, based on a set of absorption values from several wavelengths. Since the relationship to be modelled is often non-linear, classical regression methods are unsuitable, and more complex strategies and algorithms must be sought in order to model this non-linearity. This overview addresses the most widely used non-linear algorithms in the management of NIRS data.