激光拉曼光谱解谱和处理的方法研究

研究一种拉曼光谱解谱和处理的方法。以化学计量学为基础,信号处理技术为工具,配合计算机算法的数据处理方法。具体为基线校正:对拉曼光谱原始信号进行基于自适应迭代重加权惩罚最小二乘法的基线校正;平滑:对进行完基线校正的拉曼光谱信号进行基于惩罚最小二乘法的平滑;峰检测:对进行完基线校正和平滑的信号进行基于连续小波变换的峰检测。这种基于惩罚最小二乘法的光谱平滑具有快速,可以连续控制平滑度并且可以进行交叉验证得到最客观的平滑值。改善了基于非对称最小二乘法的传统基线校正方法的两个缺陷。同时,基于连续小波变换的峰检测算法可以自动地并且同时考虑峰形和峰高对峰进行检测,最大限度地降低了峰检测假阳性的概率。     

拉曼光谱结合背景扣除化学计量学方法用于汽油中MTBE含量的快速测定研究

应用便携式拉曼光谱仪测量了汽油样本的拉曼光谱,以自适应迭代惩罚最小二乘方法（airPLS）对光谱进行了背景扣除和平滑处理,并选取特征峰区间利用偏最小二乘方法（PLS）建立了预测甲基叔丁基醚（MTBE）的校正模型。以训练集相关系数和拟合误差及测试集相关系数和预测误差作为判定依据,确定了最佳建模条件。最终训练集相关系数为0.9960,拟合误差为0.3161,测试集相关系数为0.9966,预测误差为0.4901。结果表明采用便携式拉曼光谱结合化学计量学方法处理,可以满足对汽油中MTBE含量快速检测的要求。     

基于多尺度小波变换的红外光谱谱峰识别算法

传统的谱峰检测方法一般分为3个步骤:谱线平滑、基线校正和谱峰识别.现有的基于小波变换的峰值检测方法能较好地将基线校正和谱峰识别两个步骤融为一步.在此基础之上,本研究将谱线平滑也很好地融入到小波变换的峰值检测算法中,使整个峰值检测算法成为一个整体.在峰值提取时,原始谱图直接处理,不再是处理加工过的谱图,减小了谱峰检测结果...     

激光诱导击穿光谱结合CARS变量选择方法定量检测倍硫磷含量

利用双脉冲激光诱导击穿光谱(LIBS)技术对溶液中的倍硫磷含量进行定量检测。采用二通道高精度光谱仪采集不同浓度倍硫磷样品在206.28~481.77nm波段的LIBS光谱,并对光谱进行多元散射校正(MSC)、标准正态变量变换(SNV)及3点平滑预处理,根据偏最小二乘(PLS)建模确定最优的预处理方法。在此基础上,利用竞争性自适应重加权算法(CARS)筛选与倍硫磷相关的重要变量,然后应用PLS回归建立溶液中倍硫磷含量的定量分析模型,并与单变量定量分析模型及未变量选择的PLS定量分析模型进行比较。结果表明,相比单变量定量分析模型及原始光谱PLS定量分析模型,CARS-PLS定量分析模型的性能更优,其模型的校正集和预测集的决定系数及平均相对误差分别为0.9694、15.537%和0.9959、5.016%。此外,与原始光谱PLS模型相比,CARS-PLS模型仅使用其中1.9%的波长变量,但预测集平均误差却由9.829%下降为5.016%。由此可见,LIBS技术检测溶液中的倍硫磷含量具有一定的可行性,且CARS方法能简化定量分析模型,提高模型的预测精度。     

DNA碱基激光拉曼光谱检测方法的研究

以激光拉曼光谱仪采集腺嘌呤(A)、鸟嘌呤(G)、胞嘧啶(C)、胸腺嘧啶(T)的拉曼光谱图,分析了各碱基谱峰归属,并依据归属结果检测混合碱基组成。结果显示：4种碱基的特征峰集中在175~1800cm-1。相同积分时间和激光功率条件下,该波段内嘌呤碱基的激光拉曼光谱峰高于嘧啶碱基的谱峰。腺嘌呤、鸟嘌呤、胞嘧啶、胸腺嘧啶分别在723、648、791、1368cm-1处的谱峰最强,利用这些特征峰能在2min内鉴别出混合碱基中的各碱基。     

光谱基线校正算法研究与应用进展

基线漂移是拉曼、中红外、近红外以及激光诱导击穿光谱等光谱仪器测量过程中经常出现的问题,会对光谱的定量和定性分析产生不利影响.基线校正是利用数学算法对光谱数据进行预处理的过程,以便于后续的尤其是结合化学计量学方法的光谱定性和定量分析.依据算法原理,常见的基线校正算法包括导数法、迭代多项式拟合法、分段拟合的算法、移动窗口平...     

小波变换结合多维偏最小二乘方法用于近红外光谱定量分析

将小波变换和多维偏最小二乘法相结合用于近红外光谱定量校正模型的建立.首先将原始光谱进行小波变换分解,得到系列小波细节系数,通过选取一组受外界因素少、信息强的小波系数组成三维光谱阵,然后再采用多维偏最小二乘法建立校正模型.实验结果表明,该方法所建近红外校正模型的预测能力更强,并更具稳健性.     

基于高光谱技术的培养基上细菌菌落分类方法研究

利用高光谱技术对培养基上细菌(大肠杆菌、李斯特菌和金黄色葡萄球菌)菌落进行快速识别和分类。采集琼脂培养基上细菌菌落的高光谱反射图像(390~1040 nm),在对波段差图像进行大津阈值分割的基础上自动提取细菌菌落光谱,并建立细菌分类检测的全波长和简化偏最小二乘判别( PLS-DA)模型。全波长模型对预测集样本的分类准确率和置信预测分类准确率分别为100%和95.9%。此外,利用竞争性自适应重加权算法( CARS)、遗传算法( GA)和最小角回归算法( LARS-Lasso)进行波长优选并建立对应简化模型。其中,CARS简化模型在精度、稳定性及分类准确率方面均优于GA和LARS-Lasso简化模型,其对预测集样本的分类准确率和置信预测分类准确率分别达到了100%和98.0%。研究表明,高光谱是一种细菌菌落高精度、快速、无损识别检测的有效方法。简化模型中优选的波长可以为开发低成本检测仪器提供理论依据。     

Differentiation of Cultivars of Flos Chrysanthemum with the Use of High-Performance Liquid Chromatography Fingerprints and Chemometrics

Flos Chrysanthemum is a generic name for a particular group of edible plants, which also have medicinal properties. There are, in fact, twenty to thirty different cultivars, which are commonly used in beverages and for medicinal purposes. In this work, four Flos Chrysanthemum cultivars, Hangju, Taiju, Gongju, and Boju, were collected and chromatographic fingerprints were used to distinguish and assess these cultivars for quality control purposes. Chromatography fingerprints contain chemical information but also often have baseline drifts and peak shifts, which complicate data processing, and adaptive iteratively reweighted, penalized least squares, and correlation optimized warping were applied to correct the fingerprint peaks. The adjusted data were submitted to unsupervised and supervised pattern recognition methods. Principal component analysis was used to qualitatively differentiate the Flos Chrysanthemum cultivars. Partial least squares, continuum power regression, and K-nearest neighbors were used to predict the unknown samples. Finally, the elliptic joint confidence region method was used to evaluate the prediction ability of these models. The partial least squares and continuum power regression methods were shown to best represent the experimental results.     

荧光光度法同时测定邻苯二酚、间苯二酚与对苯二酚

将一种直接信号校正(DOSC)-小波包变换(WPT)-偏最小二乘法(PLS)(DOSC-WPT-PLS)新方法用于解析荧光光谱严重重叠的邻苯二酚?间苯二酚和对苯二酚混合物,并对其进行测定。该法将DOSC、WPT及PLS3种方法结合从而提高了获取特征信息的能力和回归质量。DOSC方法用于除去与浓度无关的结构噪音。利用WPT的时域和频域局部化的特点改进了除噪质量和数据压缩及信息提取能力。PLS方法用于多变量校准和噪音消除。处理该3种组分的荧光光谱数据,并实现了3种化合物的同时测定。设计了PDOSCWPTPLS程序执行相关计算,并对以上3种化学计量学方法进行了比较,其总体相对预测标准偏差分别为4.3%、7.7%、11.5%,结果表明DOSC-WPT-PLS法优于WPT-PLS法和PLS法。将该法用于测定自来水中邻苯二酚?间苯二酚和对苯二酚的含量,其回收率分别为99%¹10%?95%¹08%和98%¹04%,结果满意。     

Compositional Analysis of Cement Raw Meal by Near-Infrared (NIR) Spectroscopy

Abstract

A rapid and accurate method is presented to determine CaCO₃, SiO₂, Fe₂O₃, and Al₂O₃ in cement raw meal using near-infrared (NIR) spectroscopy. Multiplicative scatter correction (MSC) was employed to eliminate the scattering signal and partial least squares (PLS) regression was used to build the analysis model. The results demonstrated good performance by this approach for the determination of CaCO₃, SiO₂, Fe₂O₃, and Al₂O₃. NIR spectroscopy exhibits the feasibility to characterize the quality of cement raw meal. Compared with prompt gamma neutron activation analysis (PGNAA) and X-ray fluorescence (XRF), this method is more efficient and safer.     

Determination of sugars in depilatory formulations: a green analytical method employing infrared detection and partial least squares regression

A green analytical method was developed for the analysis of sugar-based depilatories. Three independent partial least squares (PLS) regression models were built for the direct determination of glucose, fructose and maltose without any sample pretreatment based on their attenuated total reflectance - Fourier transform infrared (ATR-FTIR) spectra. The models showed adequate prediction capabilities with root-mean-square-errors of prediction ranging from 7.04 to 12.55 mg sugar g⁻¹ sample. As a reference procedure, gradient liquid chromatography with on-line infrared detection, employing background correction based on cubic smoothing splines, was used. The analysis revealed changes in the sugar concentration due to the formulation process as compared to information on the ingredients provided by the manufacturers. Although fructose, glucose and sucrose were declared to be used for the production of depilatories, in the final products only fructose, glucose and maltose were determined. This fact was attributed to pH and temperature conditions employed during the production process as well as to the use of glucose syrup instead of crystalline glucose. The present ATR-FTIR-PLS method enables an accurate, cheap and fast determination without solvent consumption or toxic waste generation and offers therefore a green screening alternative to methods employing chromatographic techniques.     

Direct, reagent-free determination of free fatty acid content in olive oil and olives by Fourier transform Raman spectrometry

Fourier transform (FT) Raman spectrometry in combination with partial least squares (PLS) regression was used for direct, reagent-free determination of free fatty acid (FFA) content in olive oils and olives. Oils were directly investigated in a simple flow cell. Milled olives were measured in a dedicated sample cup, which was rotated eccentrically to the horizontal laser beam during spectrum acquisition in order to compensate sample heterogeneity. Both external and internal (leave-one-out) validation were used to assess the predictive ability of the PLS calibration models for FFA content (in terms of oleic acid) in oil and olives in the range 0.20-6.14 and 0.15-3.79%, respectively. The root mean square error of prediction (RMSEP) was 0.29% for oil and 0.28% for olives. The predicted FFA contents were used to classify oils and olives in different categories according to the European Union regulations. Ninety percent of the oil samples and 80% of the olives were correctly classified. These results demonstrate that the proposed procedures can be used for screening of good quality olives before processing, as well as, for the on-line control of the produced oil.     

Rapid Determination of Phenolics,Flavonoids, and Antioxidant Properties of Physalis ixocarpa Brot. ex Hornem. and Physalis angulata L. by Infrared Spectroscopy and Partial Least Squares

Physalis ixocarpa Brot. ex Hornem. and Physalis angulata L. are two edible species of the family Solanaceae, which have an important variety of antioxidant compounds present in their roots, stems, leaves, calyces, and fruits. This work reports the development of multivariate models based on the use of partial least square (PLS) analysis and Fourier transform infrared (FTIR) spectroscopy for the quantitative determination of total phenolics, total flavonoids, free radical scavenging activity, total antioxidant capacity, and reducing power in the extracts of roots, stems, and leaves of both P. ixocarpa and P. angulata. Standard chromatographic and colorimetric techniques were used to determine the quantitative actual values (references) in the extracts, which served as input data to develop the multivariate PLS models. Optimized FTIR-PLS models were realized by cross-validation procedures, obtaining the determination coefficients for prediction between 0.792 and 0.905 for P. ixocarpa, and between 0.756 and 0.893 for P. angulata. In this form, FTIR spectroscopy with multivariate analysis could represent a versatile tool to evaluate quantitatively concentrations of bioactive compounds and antioxidant properties in the extracts of both species, requiring a very short time at low cost.     

X‐tended target projection (XTP)—comparison with orthogonal partial least squares (OPLS) and PLS post‐processing by similarity transformation (PLS + ST)

Target projection (TP) also called target rotation (TR) was introduced to facilitate interpretation of latent‐variable regression models. Orthogonal partial least squares (OPLS) regression and PLS post‐processing by similarity transform (PLS + ST) represent two alternative algorithms for the same purpose. In addition, OPLS and PLS + ST provide components to explain systematic variation in X orthogonal to the response. We show, that for the same number of components, OPLS and PLS + ST provide score and loading vectors for the predictive latent variable that are the same as for TP except for a scaling factor. Furthermore, we show how the TP approach can be extended to become a hybrid of latent‐variable (LV) regression and exploratory LV analysis and thus embrace systematic variation in X unrelated to the response. Principal component analysis (PCA) of the residual variation after removal of the target component is here used to extract the orthogonal components, but X‐tended TP (XTP) permits other criteria for decomposition of the residual variation. If PCA is used for decomposing the orthogonal variation in XTP, the variance of the major orthogonal components obtained for OPLS and XTP is observed to be almost the same, showing the close relationship between the methods. The XTP approach is tested and compared with OPLS for a three‐component mixture analyzed by infrared spectroscopy and a multicomponent mixture measured by near infrared spectroscopy in a reactor. Copyright © 2008 John Wiley & Sons, Ltd.