原料乳中蛋白质与脂肪的近红外光谱快速定量研究

本文对快速无损检测原料乳中蛋白质与脂肪含量的近红外光谱(NIRS)技术进行了研究。对采集的250组蛋白质及脂肪含量不同的原料乳近红外光谱进行马氏距离(Mahalanobis Distance)剔除异常光谱,结合主成分分析(Principal Component Analysis,PCA),筛选出最佳建模光谱区间,采用反向传播神经网络(Back Propagation Neutral Network,BPNN)建立原料乳中蛋白含量与脂肪含量的定量模型,获得了较好的预测结果,预测模型R2分别为0.9883、0.9878,预测均方根差(RMSEP)分别为1.83%、1.85%。研究结果表明,通过合理选择光谱范围及建模方法,可得到预测精度与稳定性均较高的近红外光谱定量模型,适用于原料乳中蛋白质与脂肪含量的测定。     

近红外光谱用于中药质控前景广阔

近年来，近红外光谱技术的应用研究已从农产品的实用技术扩展到许多领域，如石油化工、高分子化工和基本有机化工、食品工业、纺织工业和制药工业及临床医学等领域。在药物分析领域中，近红外光谱不仅适用于分析药物的多种不同状态，还可用于不同类型的药品，如蛋白质、中草药、抗生素等的分析。近红外光谱更适用于对原料药纯度、包装材料等的分析与检测，以及生产工艺的监控。     

近红外光谱在蛋白质和含酰胺基团聚合物研究中的应用*

近红外光谱(near-infrared spectroscopy,NIR)是一种常用的无损表征手段,但谱带强度弱、交叠情况严重等缺点局限了它的应用范围。本文介绍了几种常见的改善近红外光谱技术不足的方法,如二阶导数法、二维相关光谱法和化学计量法等,并举例阐述了近红外光谱在蛋白质和含酰胺基团聚合物的结构和含量等方面的应用。这些方法对近红外光谱的定性定量分析起了很好的辅助作用,有效地拓宽了近红外光谱技术的应用领域。     

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．     

近红外光谱法的若干应用实例

通过ＰＧＥ和ｍＰＤＡ体系反应前后的近红外和中红外光谱图的对比，说明对于含Ｎ─Ｈ和Ｏ─Ｈ官能团的物质近红外光谱显示出中红外光谱无法比拟的优越性。本研究介绍了近红外光谱对Ｎ─Ｈ、Ｏ─Ｈ、ＣＨ＿２─ＣＨ─等官能团分析的应用实例，以及如何应用近红外光谱法研究金属氧化物的表面羟基与其催化活性的关系。     

基于近红外光谱技术的内燃机油鉴别研究

针对常规近红外光谱技术测试内燃机油时光谱信号响应低,对大分子基团分辨率不高,以及光谱信息与其结构组成之间存在非线性关系等难点,提出了一种基于电压为外扰方式的内燃机油二维近红外光谱测试技术,介绍了近红外光谱具有分形的特征.运用小波变换将近红外光谱分解至不同分辨尺度,然后计算各尺度分量的分形维数(盒维数),用近红外光谱的小波基分形参量替代近红外光谱的采样值.计算结果表明,在不同小波基和不同分解尺度下,内燃机油近红外光谱具有不同的盒维数,得到了近红外光谱在分形意义下的特征信息.以美孚、埃索和壳牌3种内燃机油品种鉴别分类问题为实例,比较研究了近红外光谱采样值与小波基分形参量,K近邻法的交互验证计算结果表明,小波基分形参量的分类效果优于近红外光谱采样值.采用近红外光谱技术测试内燃机油的结构组成信息是可行的.     

近红外光谱法快速测定乙烯原料油族组成

采用色谱仪测定乙烯原料油族训练集样品的组成性质的基础数据与近红外光谱仪测定训练集样品的近红外光谱,建立了乙烯原料油族基础数据和近红外光谱库,用化学计量学分析软件,采用偏最小二乘（PLS）方法将训练集样品的光谱和相应已测定样品的族组成基础数据相关联,建立了乙烯原料中正构烷烃、异构烷烃、环烷烃、芳烃、烯烃的定量和定性分析模型。该模型具有测定结果准确、可靠,测定简便、讯速的优点,适合在线生产中对样品的快速检测。     

书刊征订

《现代近红外光谱分析技术》(第二版)新书出版近红外光谱是20世纪80年代中期才为人们所关注的一种新技术。该书系统地介绍了近红外光谱技术的概貌、近红外吸收光谱的基本原理、近红外光谱仪器、常用化学计量学方法及软件、定性与定量分析、在线过程分析技术,并重点介绍了该技术的最新进展和在石油化工领域的应用。该书可供从事分析化学、仪器分析、过程优化、化工和石油化工生产以及农业、食品、纺织、制药和环保等专业的广大科技工作者和大专院校有关师生阅读参考。《现代近红外光谱分析技术》由陆婉珍院士主编,中国石油化工出版社出版。欲…     

关于召开“全国第一届近红外光谱学术会议”的征文通知

中国分析测试协会和中国石油学会石油炼制分会拟于2006年11月8~10日在北京举办全国第一届近红外光谱学术会议。届时邀请近红外光谱分析专家学者和仪器专家作专题报告,并进行近红外光谱分析技术交流。热忱欢迎光谱学界专家教授及广大从事分析测试技术工作的科技人员踊跃撰稿,会议将编辑论文集,并推荐优秀论文在《分析测试学报》及《现代科学仪器》等杂志上发表。会议热烈邀请国内外仪器厂商前来展出近红外光谱仪以及其它各种分析仪器。征文内容如下:(1)近红外光谱基础理论研究;(2)近红外光谱分析技术国内外发展综述;(3)近红外光谱仪器新设计…     

中药近红外光谱的褶合变换与信息可视化技术

运用褶合变换挖掘近红外光谱的特征信息并通过计算可视化技术获取相应指纹谱的表征，建立一种采用信息变换和计算机技术结合分析中药近红外光谱的新方法。应用该技术鉴别丹参、板蓝根和蛇床子药材，所得分类结果与传统植物分类学结果一致。说明科学计算可视化技术与褶合变换相结合可以拓展近红外光谱在中药定性分析中的应用。     

Infrared methods for high throughput screening of metabolites: food and medical applications

Chemical and physiological properties are related to individual or bioactive compounds such as essential oils, terpenoids, flavonoids, volatile compounds and other chemicals which are present in natural products in low concentrations (e.g. ppm or ppb). For many years, classical separation, chromatographic and spectrometric techniques such as high performance liquid chromatography (HPLC), gas chromatography (GC), liquid chromatography (LC) and mass spectrometry (MS) have been used for the elucidation of isolated compounds from different matrices. Hence, the use of standard separation, chromatographic and spectrometric methods was found useful in chemical and both plant and animal physiology studies, for fingerprinting and comparing natural and synthetic samples, as well as to identify single active compounds. It has been generally accepted that a single analytical technique will not provide sufficient visualization of the metabolome, hence holistic techniques are needed for comprehensive analysis. In the last 40 years near infrared (NIR) spectroscopy became one of the most attractive and used methods of analyzing agricultural related products and plant materials which provide simultaneous, rapid and non-destructive quantitation of major. This technique has been reported to determine other minor compounds in plant materials such as volatile compounds and elements. The aim of this short review is to describe some recent applications of NIR spectroscopy combined with multivariate data analysis for high throughput screening of metabolites with an emphasis on food and medical applications.     

NIR-spectrometric analysis of food. Methodical development and achievable performance values

The application of near infrared spectrometry (NIRS) to estimate the distribution of macro nutrients in food provides a rapid method for predicting food quality. Three methods have been developed for quantitative determination of the constituents of foods containing high levels of moisture (meat products, “consumable meals” and potatoes) using reflectance spectrometry in the near infrared region within 1100–2500 nm. Experience concerning these NIRS method developments is reported in order to predict e.g. the fat, crude protein and carbohydrate content. Generally, the performance values achieved so far indicate that the methods may be used as a replacement for conventional expensive and time-consuming wet chemical analysis.     

Determination of Quality Properties of Soy Sauce by Support Vector Regression Coupled with SW-NIR Spectroscopy

The modern near-infrared(NIR) spectroscopy analysis is a simple, efficient and nondestructive technique, which has been used in chemical analysis in diverse fields. Shortwave NIR spectroscopy is also a rapid, flexible, and cost-effective method to control product quality in food industry. The method of support vector regression coupled with shortwave NIR spectroscopy was explored for the nondestructive quantitative analysis of the important quality parameters of soy sauce, including amino nitrogen content, ...     

Determination of total polar parts with new methods for the quality survey of frying fats and oils

During the frying process the fat undergoes several chemical and physical changes caused by heat, water and atmospheric oxygen. With prolonged heating time the accumulation of deterioration products leads to organoleptic failures and a decrease of the nutritive value. For the quality control of frying fats or oils the determination of total polar parts by preparative column chromatography is an approved standard method. Many attempts were undertaken to replace this time and chemical consuming method. To substitute for the determination of polar components by column chromatography the measurement of dielectric properties with a food oil sensor, nuclear magnetic resonance spectroscopy (NMR) and near infrared spectroscopy (NIR) proved to be suitable.     

Melamine detection by mid- and near-infrared (MIR/NIR) spectroscopy: a quick and sensitive method for dairy products analysis including liquid milk, infant formula, and milk powder

Melamine (2,4,6-triamino-1,3,5-triazine) is a nitrogen-rich chemical implicated in the pet and human food recalls and in the global food safety scares involving milk products. Due to the serious health concerns associated with melamine consumption and the extensive scope of affected products, rapid and sensitive methods to detect melamine's presence are essential. We propose the use of spectroscopy data-produced by near-infrared (near-IR/NIR) and mid-infrared (mid-IR/MIR) spectroscopies, in particular—for melamine detection in complex dairy matrixes. None of the up-to-date reported IR-based methods for melamine detection has unambiguously shown its wide applicability to different dairy products as well as limit of detection (LOD) below 1 ppm on independent sample set. It was found that infrared spectroscopy is an effective tool to detect melamine in dairy products, such as infant formula, milk powder, or liquid milk. ALOD below 1 ppm (0.76 ± 0.11 ppm) can be reached if a correct spectrum preprocessing (pretreatment) technique and a correct multivariate (MDA) algorithm—partial least squares regression (PLS), polynomial PLS (Poly-PLS), artificial neural network (ANN), support vector regression (SVR), or least squares support vector machine (LS-SVM)—are used for spectrum analysis. The relationship between MIR/NIR spectrum of milk products and melamine content is nonlinear. Thus, nonlinear regression methods are needed to correctly predict the triazine-derivative content of milk products. It can be concluded that mid- and near-infrared spectroscopy can be regarded as a quick, sensitive, robust, and low-cost method for liquid milk, infant formula, and milk powder analysis.     

基于近红外光谱技术的亚麻纤维化学成分含量快速测定

在推进亚麻纤维的纺纱及其产业化生产过程中,快速、准确的定量分析纤维的化学成分是重要趋势。该研究利用近红外光谱技术分析亚麻纤维化学成分,以化学分析法测定值为对照,采用偏最小二乘法(PLS)建立亚麻纤维化学成分的近红外模型,从而实现了其化学成分的高效、快速定量分析。结果表明,建立的亚麻纤维纤维素、半纤维素、木质素和果胶近红外模型的校正相关系数(R_C)与验证相关系数(R_(CV))均在0.9以上,校正均方根误差(RMSEC)小于预测均方根误差(RMSEP)且均小于1。外部验证和双尾t检验表明模型预测结果较为准确,预测值与化学分析法得到的实测值无显著性差异,故该模型可用于相关化学成分含量的快速预测。     

Discrimination of industrial products by on-line near infrared spectroscopy with an improved dendrogram

Near infrared(NIR) spectroscopy technique has shown great power and gained wide acceptance for analyzing complicated samples.The present work is to distinguish different brands of tobacco products by using on-line NIR spectroscopy and pattern recognition techniques.Moreover,since each brand contains a large number of samples,an improved dendrogram was proposed to show the classification of different brands.The results suggest that NIR spectroscopy combined with principal component analysis (PCA) and hierarchical cluster analysis(HCA) performs well in discrimination of the different brands,and the improved dendrogram could provide more information about the difference of the brands.     

Can food quality be enhanced by chromatography?

Summary Quality of food is the utmost goal of all food producers. It is determined by chemical, physical, microbiological, and even psychological aspects. The chemical and microbiological quality aspects are especially responsible for health and welfare of the consumer. Quality of food, therefore, at all times has to be ensured and be enhanced as far as possible. From the chemical point of view, foods contain a great number of major and minor components. That determine the nutritional value of a food product. Furthermore, taste and flavour are the result of many food minor components. Foods also may contain unwanted compounds like residues and contaminants. Which represent undesirable aspects of food quality. With chromatography as a powrful analytical tool in food chemistry, the quality of food products cannot only be characterized but also be enhanced. Examples of enhancing quality of food by applying chromatography to cheese, margarine, meat, and other products is reported. Presented at the 21^st ISC held in Stuttgart, Germany, 15^th–20^th September, 1996     

Self-modeling curve resolution (SMCR) analysis of near-infrared (NIR) imaging data of pharmaceutical tablets

The idea of quality by design (QbD) has been proposed in pharmaceutical field. QbD is a systematic approach to control the product performance based on the scientific understanding of the product quality and its manufacturing process. In the present study, near-infrared (NIR) imaging is utilized as a tool to achieve this concept. A practical use of a chemometrics technique called self-modeling curve resolution (SMCR) is demonstrated with NIR imaging analysis of pharmaceutical tablets containing two ingredients, a soluble active ingredient, pentoxifylline (PTX), and an insoluble excipient, palmitic acid. Concentration profiles obtained by SMCR reveal that the homogenous distribution of chemical ingredients strongly depends on the grinding time and that its process plays a central role in quantitative control, say sustained-release of PTX. In addition, pure component spectra by SMCR indicate a sequential change of specific NIR peak intensities following the increase of the grinding time. The spectra change shows a molecular structure change related to its crystallinity during grinding process. Accordingly, this study clearly demonstrates that NIR imaging combined with SMCR can be a powerful tool to reveal chemical or physical mechanism induced by the manufacturing process of pharmaceutical products and that it may be a solid solution for QbD of pharmaceutical products.     

Cooking activities during the Middle Ages: organic residues in ceramic vessels from the Sant'Antimo Church (Piombino-Central Italy)

A combined gas chromatography-electron ionization (GC-EI), atmospheric pressure chemical ionization (APCI) mass spectrometry (MS) and MS/MS approach has been used for characterizing organic residues of ceramic vessels of different forms and dimensions recovered from a vault of the apse of the 13th century church of Sant'Antimo in Piombino (Central Italy). The artifacts studied in this investigation are pots, jugs, colanders and pans probably used for cooking meals or as food containers. GC-MS has shown the presence of different fatty acids and other nonpolar markers, while APCI ionization proved to be particularly useful in the detection of diterpenoids and diacylglycerols. The data show that some organic markers may be of animal origin, while others are typical constituents or biodegradation products of vegetables. This allows one to propose the main use of these articles as vessels for cooking meat and maybe vegetable broths and soups. As there is no strict correlation between organic markers and shape, form and dimension of the ceramic vessel, it appears that the different objects probably served the same function. Chemical characterization of the organic residues of ceramic vessels, together with all the other archaeological data, contributes to a better understanding of their uses and the customs of people in the Middle Ages in Central Italy.