近红外光谱分析中的化学计量学算法研究新进展

近红外光谱是一种绿色、快捷的分析技术,在科学研究、工业生产以及日常检测中得到广泛应用。化学计量学算法的应用在近红外光谱技术的发展过程中发挥了重要作用。化学计量学方法通过寻找测量变量之间的相关性,构建数学模型,量化样本间的差异性,并发现事物变化的内在规律,实现较合理准确的未知预测。这也是"大数据"战略的重要环节和主旨所在。该文针对近红外光谱吸收信号较弱、谱峰重叠严重,以及光谱测量过程中易受背景、噪声、无信息变量和外界环境因素干扰等,导致借助化学计量学方法建立的光谱与研究目标的定性定量分析模型变差问题,总结了近年来在近红外光谱领域所提出的一些化学计量学新方法,包括光谱预处理、变量选择、多元校正和模型转移,从不同角度阐述了这些方法在消除近红外光谱模型的干扰因素,提高模型的可靠性、预测准确性和适用性等方面的作用。     

近红外光谱分析技术的最新进展与展望

在过去的几十年,近红外光谱是发展最为迅速的分析技术之一。振动光谱基础理论、光谱仪器硬件和化学计量学是现代近红外光谱分析技术的3大支柱,近些年,近红外光谱技术在这3个方面均取得了显著进展。该文结合上述3个方面的应用研究情况,对近红外光谱分析技术的最新进展进行了综述,并对未来发展趋势进行了展望。     

近五年我国近红外光谱分析技术研究与应用进展

评述了近五年来(2014～2018)我国近红外光谱分析技术的研究与应用进展,内容涉及方法研究、软硬件研发、应用特点和趋势等方面,并对今后我国近红外光谱技术的发展方向进行了展望。引用文献97篇。     

近红外光谱技术结合主成分分析法用于子宫内膜癌的诊断

应用近红外光谱技术结合化学计量学方法研究了子宫内膜癌组织近红外光谱特征提取和早期诊断的可行性. 测定了154 例子宫内膜组织切片的近红外光谱, 选取适宜的波段和光谱预处理方法进行主成分分析, 很好地区分了癌变、增生和正常子宫内膜组织切片, 并且分辨出处于不同分化期的组织切片, 为子宫内膜癌的早期诊断提供了可靠依据. 该法快速、简便, 有望发展成为一种新型的肿瘤无创诊断方法.     

烟草近红外光谱分析网络化及其应用进展

该文回顾了近红外光谱(NIRS)分析技术的应用历程以及"近红外光谱分析+互联网"模式在烟草领域中的应用研究与实践,探讨了在近红外光谱分析网络化环境中,近红外光谱仪器设备存在的硬件差异以及常规化学计量学方法(算法)在建模、数据处理存在的不足对近红外光谱的深度应用产生的影响,并提出了近红外光谱分析云计算应用的解决思路。最后,对大数据时代近红外光谱分析网络化模式的应用前景进行了展望。     

微小型近红外光谱仪的应用进展与展望

近些年,近红外光谱分析技术得到了迅猛发展,该技术可直接对气体、液体和固体等各种复杂混合物进行定性和定量分析,具有分析速度快、效率高,可实现无损和在线分析等优势,在科研和工农业生产中发挥着越来越重要的作用。近红外光谱分析仪的微小型化是一个重要的发展方向,近期出现了众多不同类型的商品化微小型近红外光谱仪器。手持式或便携式现场快速分析是一种更经济、更高效、更灵活的方法,具有小体积、低功耗、低成本、便于二次开发等优点,在农业、食品、医药、石油化工和安全等众多领域获得了广泛的研究与应用。物联网技术在智能农业、智能工厂、智能医疗和智慧城市等众多领域的兴起,成为推动近红外光谱传感器向着微型化方向发展的主要力量。该文主要综述了近些年新型的商品化微小型（便携式、手持式和袖珍式）近红外光谱仪器及其应用进展,并对该技术的发展趋势和应用前景进行了展望。     

近红外光谱在无机微量成分分析中的应用

由于近红外光谱的独特优势, 在实际复杂样品分析中发挥了重要作用. 但由于近红外光谱的信号相对较弱, 无机离子在近红外光谱中一般没有响应, 因此难以用于微量成分特别是无机微量组分的测定. 总结了近红外光谱技术在环境、土壤、植物及生物样品分析中的应用, 说明了近红外光谱用于无机微量成分分析的原理. 由于近红外光谱技术一般通过多元校正方法进行定性定量分析, 利用组分间的相互作用或组分含量之间的相关性可以实现微量组分或无光谱响应组分的定量分析. 还总结了富集技术在近红外光谱分析中的应用, 利用富集技术可实现稀溶液中金属离子含量的快速测定, 并可以改善分析的灵敏度和检测限.     

大豆蛋白的中红外和近红外光谱研究*

大豆蛋白在各领域的应用已得到广泛的关注,因此大豆蛋白及其改性材料在结构性能方面的研究显得越来越重要。中红外光谱(mid-infrared spectroscopy,MIR)和近红外光谱(near-infrared spectroscopy,NIR)正是对蛋白质进行定性定量分析的有力手段。中红外光谱可以有效地分析大豆蛋白在溶液和薄膜中的二级结构以及大豆衍生材料内蛋白质的结构变化情况。近红外光谱则在蛋白质定量分析方面有着独特的优势。本文介绍了运用这两种光谱技术进行研究的一些工作,这些实例表明了中红外和近红外光谱在大豆蛋白研究领域的重要应用价值。     

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．     

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。     

Qualitative and quantitative analysis of oxytetracycline by near-infrared spectroscopy

Near-infrared (NIR) spectroscopy, in combination with chemometrics, enable the analysis of raw materials without time-consuming sample preparation methods. The aim of our work was to estimate critical parameters in the analytical specification of oxytetracycline, and consequently the development of a method for quantification and qualification of these parameters by NIR spectroscopy. A Karl Fischer (K.F.) titration to determine the water content, a colorimetric assay method, and Fourier transform-infrared (FT-IR) spectroscopy to identify the oxytetracycline base, were used as reference methods, respectively. Multivariate calibration was performed on NIR spectral data using principal component analysis (PCA), partial least-squares (PLS 1) and principal component regression (PCR) chemometric methods. Multivariate calibration models for NIR spectroscopy have been developed. Using PCA and the Soft Independent Modelling of Class Analogy (SIMCA) approach, we established the cluster model for the determination of sample identity. PLS 1 and PCR regression methods were applied to develop the calibration models for the determination of water content and the assay of the oxytetracycline base. Comparing the PLS and PCR regression methods we found out that the PLS is better established by NIR, especially as the spectroscopic data (NIR spectra) are highly collinear and there are many wavelengths due to non-selective wavelengths. The calibration models for NIR spectroscopy are convenient alternatives to the colorimetric method and to the K.F. method, as well as to FT-IR spectroscopy, in the routine control of incoming material.     

The Ability of Near Infrared (NIR) Spectroscopy to Predict Functional Properties in Foods: Challenges and Opportunities

Near infrared (NIR) spectroscopy is considered one of the main routine analytical methods used by the food industry. This technique is utilised to determine proximate chemical compositions (e.g., protein, dry matter, fat and fibre) of a wide range of food ingredients and products. Novel algorithms and new instrumentation are allowing the development of new applications of NIR spectroscopy in the field of food science and technology. Specifically, several studies have reported the use of NIR spectroscopy to evaluate or measure functional properties in both food ingredients and products in addition to their chemical composition. This mini-review highlights and discussed the applications, challenges and opportunities that NIR spectroscopy offers to target the quantification and measurement of food functionality in dairy and cereals.     

Monitoring of the Sol-Gel Synthesis of Organic-inorganic Hybrids by FTIR Transmission,FTIR/ATR,NIR and Raman Spectroscopy

Summary: The sol-gel synthesis of organic-inorganic hybrids based on triethoxysilane- terminated poly(ethylene oxide) and tetraethylorthosilicate was monitored in-situ using three spectroscopic methods (FTIR/ATR, Raman, NIR). These spectroscopic methods allow in-situ monitoring of the evolution of hybrid materials starting from the modification of the polymer and the early steps of hydrolysis up to the network formation. By application of ²⁹Si solid-state NMR spectroscopy the assignment and quantification of the Raman bands to different end groups and different cross-linking states was made. The sol-gel reaction was also followed by in-line NIR spectroscopy. A multivariate data analysis was accomplished to obtain a conversion-time curve. Furthermore, we investigated spin-coated films on wafers using FTIR transmission spectroscopy.     

Principles and Applications of Miniaturized Near-Infrared (NIR) Spectrometers

This review article focuses on the principles and applications of miniaturized near-infrared (NIR) spectrometers. This technology and its applicability has advanced considerably over the last few years and revolutionized several fields of application. What is particularly remarkable is that the applications have a distinctly diverse nature, ranging from agriculture and the food sector, through to materials science, industry and environmental studies. Unlike a rather uniform design of a mature benchtop FTNIR spectrometer, miniaturized instruments employ diverse technological solutions, which have an impact on their operational characteristics. Continuous progress leads to new instruments appearing on the market. The current focus in analytical NIR spectroscopy is on the evaluation of the devices and associated methods, and to systematic characterization of their performance profiles.     

Quantitative determination of soybean meal content in compound feeds: comparison of near-infrared spectroscopy and real-time PCR

Standard methods for determining the raw material content of compound feed are little exploited, except for the identification of meat and bone meal in feeds. In this work, near-infrared (NIR) spectroscopy and real-time polymerase chain reaction (PCR) were applied in order to establish new and fast methods for quantification of soybean meal content in compound feeds. The best prediction quality was achieved by using a model based on NIR spectroscopy (R ² = 0.9857, standard error of cross-validation 1.1065). Furthermore, a sensitive qualitative detection method by using the real-time PCR was developed (R ² = 0.976, slope −3.7599). Finally, the differences between the real-time PCR result and the NIR spectroscopy result for a given sample were also treated, and we found that the NIR spectroscopy method provided quite accurate results which approach closely those of the real-time PCR method. Hui Li and Xiaowen Lv contributed equally to this work.     

Comparison of near-infrared and mid-infrared spectroscopy for the determination of distillation property of kerosene

Near-infrared (NIR) and mid-infrared (MIR) spectroscopy have been compared and evaluated for the determination of the distillation property of kerosene with the use of partial least squares (PLS) regression. Since kerosene is a complex mixture of similar hydrocarbons, both spectroscopic methods will be best evaluated with this complex sample matrix. PLS calibration models for each percent recovery temperature have been developed by using both NIR and MIR spectra without spectral pretreatment. Both methods have shown good correlation with the corresponding reference method, however NIR provided better calibration performance over MIR. To rationalize the improved calibration performance of NIR, spectra of the same kerosene sample were continuously collected and the corresponding spectral reproducibility was evaluated. The greater spectral reproducibility including signal-to-noise ratio of NIR led to the improved calibration performance, even though MIR spectroscopy provided more qualitative spectral information. The reproducibility of measurement, signal-to-noise ratio, and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for quantitative analysis.     

Expanding the analytical toolbox for identity testing of pharmaceutical ingredients: Spectroscopic screening of dextrose using portable Raman and near infrared spectrometers

In the pharmaceutical industry, dextrose is used as an active ingredient in parenteral solutions and as an inactive ingredient (excipient) in tablets and capsules. In order to address the need for more sophisticated analytical techniques, we report our efforts to develop enhanced identification methods to screen pharmaceutical ingredients at risk for adulteration or substitution using field-deployable spectroscopic screening. In this paper, we report our results for a study designed to evaluate the performance of field-deployable Raman and near infrared (NIR) methods to identify dextrose samples. We report a comparison of the sensitivity of the spectroscopic screening methods against current compendial identification tests that rely largely on a colorimetric assay. Our findings indicate that NIR and Raman spectroscopy are both able to distinguish dextrose by hydration state and from other sugar substitutes with 100% accuracy for all methods tested including spectral correlation based library methods, principal component analysis and classification methods.     

Use of NIR spectroscopy in the production of modified industrial resins

Natural resins are scarcely used, but after appropriate modification processes they acquire characteristics of viscosity, point of softening, stability, etc. that facilitate their application in fields such as paintings, varnishes, cosmetic, etc. The complexity of resins makes it very difficult to monitor the reactions involved in their modification, the extent of which is usually determined via more experimentally accessible parameters. However, the methods typically used to determine such parameters are slow and produce environmentally unfriendly waste.In this work, we assessed the potential of NIR spectroscopy, as an alternative to the traditional analytical methods, for monitoring the industrial processes involved in the production of modified resins. To this end, we developed PLS calibration models that were used to quantify physical (viscosity and cloud point) and chemical parameters (acid and hydroxyl numbers), with a view to characterize the evolution of the resins during the reaction that take place throughout the fabrication process.Samples were withdrawn at different times stages of the process for analysis with the proposed quantitation models; the data thus obtained were compared with those provided by reference methods. Based on the results, NIR spectroscopy is an effective choice for the accurate, expeditious monitoring of industrial resin modification processes.     

From Ultrafast Structure Determination to Steering Reactions: Mixed IR/Non‐IR Multidimensional Vibrational Spectroscopies

Ultrafast multidimensional infrared spectroscopy is a powerful method for resolving features of molecular structure and dynamics that are difficult or impossible to address with linear spectroscopy. Augmenting the IR pulse sequences by resonant or nonresonant UV, Vis, or NIR pulses considerably extends the range of application and creates techniques with possibilities far beyond a pure multidimensional IR experiment. These include surface‐specific 2D‐IR spectroscopy with sub‐monolayer sensitivity, ultrafast structure determination in non‐equilibrium systems, triggered exchange spectroscopy to correlate reactant and product bands, exploring the interplay of electronic and nuclear degrees of freedom, investigation of interactions between Raman‐ and IR‐active modes, imaging with chemical contrast, sub‐ensemble‐selective photochemistry, and even steering a reaction by selective IR excitation. We give an overview of useful mixed IR/non‐IR pulse sequences, discuss their differences, and illustrate their application potential.