基于可见/近红外透射光谱的番茄红素含量无损检测方法研究

针对番茄内外部结构特征,搭建了可见/近红外透射检测系统,利用完整番茄透射光谱信息,对番茄红素含量进行无损伤快速检测研究。采集的原始光谱曲线经去趋势(DT)、标准正态变量变换(SNV)、多元散射校正(MSC)、归一化(NOR)、一阶导数(FD)预处理后分别用偏最小二乘(PLS)进行建模分析。其中SNV预处理后的模型效果最好,校正集和验证集相关系数分别为0.9771和0.9504,校正集和验证集均方根误差为0.9711和1.0496 mg/kg。为进一步提高模型的精度和稳定性,采用无信息变量消除法(UVE)、连续投影算法(SPA)、竞争性自适应重加权算法(CARS)3种方法单独或联合处理(UVE-SPA,UVE-CARS),对全光谱进行变量优选。经UVE-CARS处理后番茄红素预测模型效果最好,其校正集和验证集相关系数分别提高至0.9830和0.9741,均方根误差分别降低至0.6919和0.7680 mg/kg。最后,选用25个番茄样品对所建立模型进行了外部验证,UVE-CARS-PLS模型的预测集相关系数为0.9812,预测集均方根误差为0.7071 mg/kg,平均相对误差为4.3%。而作为比较的PLS模型的预测集相关系数为0.951,均方根误差为1.0610 mg/kg,平均相对误差6.0%,相比于全光谱PLS模型,UVE-CARS可以很大程度地简化模型,提高模型精度,降低检测的误差限。结果表明,基于自行搭建的番茄可见/近红外透射检测系统结合光谱处理方法,可以实现对生鲜番茄中番茄红素含量的快速、无损检测,为番茄红素定量检测提供了新方法。     

可见-近红外光谱结合CARS优化模型预测棕榈油碘值

采用可见-近红外透射光谱结合CARS变量优选方法优化模型,对棕榈油碘值进行近红外定量分析。通过将使用不同预处理方法产生的建模效果进行比较,找到了理想的预处理方法,通过CARS变量选择方法优选出与棕榈油碘值相关的有效波点共60个,利用60个有效波点建立棕榈油碘值优化模型。根据优化模型的建模集相关系数(R_c=0.9814)和预测集相关系数(R_p=0.9806),得到的建模均方根误差(RM SEC=0.0398)和预测均方根误差(RM SEP=0.0406)优于采用全波段建立的模型得到的系数误差。利用可见近红外透射光谱结合CARS变量优选方法,简化了棕榈油碘值模型,并能够保证碘值预测的准确度。     

近红外光谱法快速鉴定油菜杂交种的纯度

建立近红外光谱技术测定油菜杂交种纯度的方法。考察了样品杯类型、光谱预处理方法和波长范围对近红外模型预测性能的影响。结果发现,由不同样品杯采集近红外光谱所建立的校正模型,其预测性能存在较大的差异,旋转杯明显优于安瓿瓶;采用消除常数偏移量对光谱进行预处理能有效地提取光谱信息,选择5 000~8 000 cm–1波数范围作为建模谱区,其包含的有效信息率最高。在最佳条件下建立油菜杂交种纯度的校正模型,其决定系数(R2)为0.980 0,交互验证均方根误差(RMSECV)为0.008 59。利用该模型对预测集进行测定,预期均方根误差(RMSEP)为0.007 59,表明该模型具有很好的预测性能,近红外光谱法用于杂交种纯度的鉴定是可行的。     

近红外光谱结合遗传算法快速检测红曲菌固态发酵生物量

该文研究了近红外光谱技术在红曲菌固态发酵生物量快速检测方面的应用。共采集了4个批次80个样本的光谱,采用氨基葡萄糖法测定生物量。为降低模型的复杂度和提高模型的预测性能,研究了遗传算法(Genetic Algorithm,GA)的光谱谱区选择方法,并建立所优选光谱变量的预测红曲菌固态发酵生物量的PLS模型。为说明遗传算法优选光谱变量的可行性,另外分别建立了全谱和相关系数法两种波长选择方法下的PLS定量模型,比较分析了3种方法所获模型的预测能力,并对GA方法优选的光谱波段信息与菌体成分中含氢基团的对应吸收进行分析。结果表明,遗传算法能在降低模型复杂度的同时提高模型的预测性能,其建模结果为Rc=0.998 3,RMSECV=3.580 2,Rp=0.993 1,RMSEP=3.643 7,参与建模的数据点由全谱的1 457个减少到585个,且模型预测精度相比FS-PLS模型提高了11.55%。研究表明近红外光谱技术结合遗传算法所建的PLS预测模型能够实现红曲菌固态发酵生物量的快速检测,从而为进一步实现在线发酵过程优化控制提供依据。     

苹果产地差异对可溶性固形物近红外光谱检测模型影响的研究

为更好地利用近红外光谱预测苹果可溶性固形物含量,减少产地差异对近红外光谱检测模型的影响,以4种不同产地的富士苹果为研究对象,采用基于x-y共生距离的样本划分方法分别对不同产地的苹果选取代表性样本作为校正集,利用偏最小二乘算法,建立和比较单一产地和混合产地下的苹果可溶性固形物近红外光谱检测模型,并结合竞争性自适应重加权算法(CARS)和连续投影算法(SPA)对苹果可溶性固形物的建模变量进行筛选。相比单一产地和其它混合产地模型,混合所有4种苹果产地的校正集样本建立的模型取得了最好的预测结果,另外,结合CARS-SPA筛选的16个特征波长,模型得到了进一步简化,其预测相关系数和预测均方根误差分别为0.978和0.441°Brix。结果表明,利用多个产地的苹果样本建立的混合模型,结合有效特征波长,可提高对苹果可溶性固形物含量的预测精度,减小产地差异对可溶性固形物近红外光谱检测的影响。     

基于小波变换-遗传算法-偏最小二乘的草莓糖度检测研究

采用近红外漫反射光谱分析技术,对草莓糖度进行了无损检测研究。利用便携式近红外光谱仪采集草莓样品在600～1 100 nm波段内的漫反射光谱数据。首先利用小波变换(WT)多分辨率方法对光谱数据进行去噪预处理,然后利用遗传算法(GA)优选特征波长,最后运用偏最小二乘法(PLS)建立草莓糖度的WT-GA-PLS校正模型。该模型校正集的相关系数R_C为0.9395,校正集的均方根误差RMSEC为0.1615,预测集的相关系数R_P为0.9652,预测集的均方根误差EMSEP为0.5042。与全光谱模型(FS-PLS)和小波变换模型(WT-PLS)相比,该模型预测能力更强,稳健性更优。     

基于粒子群算法的波长选择方法用于苹果酸度的近红外光谱分析

采用便携式近红外光谱分析仪,对苹果样品进行扫描获得光谱数据,运用偏最小二乘法结合基于粒子群算法的波长选择方法对苹果试验数据进行多元统计分析,建立数学模型,利用该模型对苹果酸度进行了预测。对于基于粒子群算法和全谱偏最小二乘方法,校正集样品的酸度预测值和实测值之间的相关系数分别为0.9880和0.9553,校正均方根误差分别为0.0197和0.0388;预测集样品的酸度预测值和实测值之间的相关系数分别为0.9833和0.9596,预测均方根误差分别为0.0193和0.0304。与全谱偏最小二乘法相比,基于粒子群算法的偏最小二乘法,不仅较大地减少波长变量而降低计算量,而且也较大地提高了模型性能而增强了模型预测的准确性。该方法可建立较好的定量分析模型,能广泛应用于现场或野外苹果酸度的快速分析。     

应用遗传算法和PLS的近红外光谱预测玉米中淀粉含量的研究

以普通玉米籽粒为试验材料,在应用遗传算法结合偏最小二乘回归法对近红外光谱数据进行特征波长选择的基础上,应用偏最小二乘回归法建立了特征波长测定玉米籽粒中淀粉含量的校正模型．试验结果表明,基于11个特征波长所建立的校正模型,其校正误差（RMSEC）、交叉检验误差（RMSECV）和预测误差（RMSEP）分别为0.30％、0.35％和0.27％,校正数据集和独立的检验数据集的预测值与实际测定值之间的相关系数分别达到0.9279和0.9390,与全光谱数据所建立的预测模型相比,在预测精度上均有所改善,表明应用遗传算法和PLS进行光谱特征选择,能获得更简单和更好的模型,为玉米籽粒中淀粉含量的近红外测定和红外光谱数据的处理提供了新的方法与途径．     

自适应蚁群优化算法的近红外光谱特征波长选择方法

为提高近红外光谱预测模型的精度和适用性,同时简化模型,提出了自适应蚁群优化偏最小二乘法优选特征波长的方法,建立不同产地苹果可溶性固形物含量混合分析模型。收集山东、陕西和新疆的富士苹果,采集3800~14000 cm"1范围的近红外光谱,并对其重要品质指标可溶性固形物含量进行测定。利用蚁群算法启发式全局搜索的特点,结合蒙特卡罗轮盘赌随机选择机制,优选苹果可溶性固形物含量的近红外光谱特征波长,然后用偏最小二乘法建立分析模型。与全光谱偏最小二乘模型和遗传偏最小二乘模型相比,蚁群优化算法选择的波长数最少,模型预测能力最强,预测的相关系数R和预测均方根误差RMSEP分别为0.9708和0.5144。研究结果表明,自适应蚁群优化算法可以有效选择近红外光谱特征波长,提高模型的稳健性和适用性。     

最小角回归算法(LAR)结合采样误差分布分析(SEPA)建立稳健的近红外光谱分析模型

结合采样误差分布分析(SEPA)框架和最小角回归(LAR)算法,提出了一种SEPA-LAR变量逐步筛选方法用于波长选择,并建立了稳健的近红外光谱分析模型。利用蒙特卡洛采样(MCS)获得多个数据集划分建立多个模型,对光谱各变量(波长)在所有模型的LAR系数进行统计分析,按其回归系数绝对值总和由大到小排序,选择排序靠前的波长建立偏最小二乘(PLS)模型,以未参与SEPA-LAR和建模的独立验证集对该模型进行评价。将玉米湿度、柴油密度以及奶酪脂肪的近红外光谱数据用于SEPA-LAR的性能检验,独立验证集的预测均方根误差(RMSEP)分别为0.001 44%(湿度指标)、0.001 58 g/mL(密度指标)以及1.13 g/100 g(脂肪含量指标)。结果表明,相较于竞争自适应重加权采样法(CARS),该方法具有更优异的稳定性;相较于移动窗口偏最小二乘(MWPLS)以及蒙特卡洛无信息变量消除(MCUVE)方法,该方法选择的变量更少,预测误差更低,预测性、可解释性和稳定性更优异。     

多个离群值鉴别方法在定量校正中的应用

本文使用统计量Fk进行多元线性回归分析体系离群值的鉴别,将该方法用于紫外光度法直接校正定量波长的选择及液相压电传感器阵列定量体系校正样本的选择,选择前后定量分析结果表明,方法可行。     

Mathematical algorithms applied to the multi-linear regression functions for the multicomponent determination of pharmaceutical dosage form containing three-component mixtures

In the presence of closely overlapping spectra, the quantitative multiresolution of ternary mixtures of three active compounds paracetamol (PAR), caffeine (CAF) and acetylsalycilic acid (ASP) in tablets, without using pretreatment such as separation step and graphical procedure of spectra was accomplished by the multivariate spectral calibration models, tri-linear regression calibration (TLRC), multi-linear regression calibration (MLRC) and Cramer's rule solution (CRS) of three linear equation functions in the matrix form. In the first two models, TLRC and MLRC are based on the use of the linear regression functions at selected wavelength sets in the spectral region of 210-300 nm. In the case of CRS model, A1(1) (1%, 1 cm) were used to obtain three linear equation functions and this linear equation system was resolved by the Cramer's rule for the prediction of PAR, CAF and ASP in samples. In the TLRC and CRS models, the selection of the appropriate wavelength set was performed by the Kaiser's technique. The algorithms of these mathematical calibration models were briefly described. The validation of TLRC, MLRC and CRS models was carried out by analyzing various synthetic ternary mixtures and by using the standard addition technique. These three calibration approaches were applied to the analysis of the real pharmaceutical tablets containing PAR, CAF and ASP. The obtained results were statistically compared with each other by using experimental and statistical tests. In the comparison of TLRC and MLRC models to the classical approach, CRS technique, the successful assay results were observed for the quantitative multiresolution of ternary mixture of the subject active compounds.     

Application of ridge trace analysis in direct spectrophotometric calibration

The use of ridge trace analysis for multivariate calibration problems is described. Application is made to the simultaneous quantitative determination of components for several pharmaceutical systems with unknown sample UV spectra by the direct calibration technique. The results indicate that with the help of ridge trace analysis and ridge regression, the parameter k can be selected to obtain estimation of the colinearity of a system based on the stability of relative concentration as a function of k. Much information about the system to be analyzed can be obtained, such as whether there is colinearity among the variables, which measurement wavelength range is suitable for performing quantitative analysis, which components cannot be measured and which components can only be measured as a sum, and whether the quantitative model is correct.     

Resolution of mixtures of three nonsteroidal anti-inflammatory drugs by fluorescence using partial least squares multivariate calibration with previous wavelength selection by Kohonen artificial neural networks

A spectrofluorometric method for the quantitative determination of flufenamic, mefenamic and meclofenamic acids in mixtures has been developed by recording emission fluorescence spectra between 370 and 550 nm with an excitation wavelength of 352 nm. The excitation–emission spectra of these compounds are deeply overlapped which does not allow their direct determination without previous separation. The proposed method applies partial least squares (PLS) multivariate calibration to the resolution of this mixture using a set of wavelengths previously selected by Kohonen artificial neural networks (K-ANN). The linear calibration graphs used to construct the calibration matrix were selected in the ranges from 0.25 to 1.00 μg ml⁻¹ for flufenamic and meclofenamic acids, and from 1.00 to 4.00 μg ml⁻¹ for mefenamic acid. A cross-validation procedure was used to select the number of factors. The selected calibration model has been applied to the determination of these compounds in synthetic mixtures and pharmaceutical formulations.     

Net analyte signal-based simultaneous determination of antazoline and naphazoline using wavelength region selection by experimental design-neural networks

Net analyte signal (NAS)-based multivariate calibration methods were employed for simultaneous determination of anthazoline and naphazoline. The NAS vectors calculated from the absorbance data of the drugs mixture were used as input for classical least squares (CLS), principal component and partial least squares regression PCR and PLS methods. A wavelength selection strategy was used to find the best wavelength region for each drug separately. As a new procedure, we proposed an experimental design-neural network strategy for wavelength region optimization. By use of a full factorial design method, some different wavelength regions were selected by taking into account different spectral parameters including the starting wavelength, the ending wavelength and the wavelength interval. The performance of all the multivariate calibration methods, in all selected wavelength regions for both drugs, was evaluated by calculating a fitness function based on the root mean square error of calibration and validation. A three-layered feed-forward artificial neural network (ANN) model with back-propagation learning algorithm was employed to model the nonlinear relationship between the spectral parameters and fitness of each regression method. From the resulted ANN models, the spectral regions in which lowest fitness could be obtained were chosen. Comparison of the results revealed that the net NAS-PLS resulted in lower prediction error than the other models. The proposed NAS-based calibration method was successfully applied to the simultaneous analyses of anthazoline and naphazoline in a commercial eye drop sample.     

Backscattered electron images,X-ray maps and Monte Carlo simulations applied to the study of plagioclase composition in volcanic rocks

Zoning patterns in plagioclases are related to abrupt changes in the anorthite content along the crystal growing direction. Accurate characterization of these patterns by electron microprobe is useful to identify magma chamber processes such as recharge, mingling and whole-chamber overturn events.In this work, a new procedure to obtain high resolution quantitative maps of anorthite concentration in single plagioclase crystals is developed. The methodology consists of performing a calibration of backscattered electron images using quantitative X-ray maps. The ultimate resolution of characteristic X-rays and backscattered electron signals is studied by Monte Carlo simulation. The method is applied to characterize the chemical composition of a volcanic plagioclase from the Cerro Vilama, Argentina. The results obtained are more precise than the values given by the methods commonly used in the study of plagioclase composition, i.e. the classical profiling by electron microprobe point analysis or the modern backscattered electron image calibration by means of quantitative energy or wavelength dispersive X-ray analysis at a few selected points.     

Development of Calibration-Free Laser-Induced-Breakdown-Spectroscopy based techniques for deposited layers diagnostics on ITER-like tiles

High temperature plasma in hydrogen isotopes is peculiar of thermonuclear fusion devices. The study of plasma–wall interaction is of paramount importance for avoiding both damage of plasma facing components (PFCs) and pollution of the plasma. To assure continuous and fault-free operation a strict control must be exerted on the amount of impurities deposited on, and of the fuel retained in the PFCs. This requirement makes Laser-Induced-Breakdown-Spectroscopy (LIBS) an ideal candidate for on-line quantitative monitoring of the walls of the current as well as of the next generation fusion devices like the International Thermonuclear Experimental Reactor (ITER).An experimental setup has been designed and realized in order to optimize the characteristics of a LIBS system working at low pressure and remotely, and it has been utilized in combination with calibration free procedures for quantitative analysis. In this work, a partial calibration free method has been developed for single shot analysis of hydrogen isotopes retention at the PFCs-like surfaces, based on the acquisition of high resolution spectra in a narrow wavelength range. Results of calibration free and partial calibration free have been obtained on suitably deuterated samples; preliminary spectroscopic considerations on tritium detection are also presented.     

火灾探测器滤光片校准方法

以紫外可见近红外分光光度计为计量标准器建立火灾探测器滤光片校准方法。火焰探测器紫外滤光片校准选择波长范围150~300 nm进行光谱扫描,测量滤光片在紫外区域的透射比;红外滤光片校准选择波长范围800~1 100 nm进行光谱扫描,测量滤光片在红外区域的透射比。线型光束感烟火灾探测器滤光片校准波长扫描范围设置为700~1 100 nm,取850~950 nm透射比平均值计算减光值。火焰探测器紫外滤光片校准结果为220,240,260,280 nm波长下的透射比,红外滤光片校准结果为850,900,950,1 000 nm波长下的透射比,不作合格性判定。线型光束感烟火灾探测器滤光片减光值标称值为0.4,0.9 d B时,误差不超过±0.1 d B;减光值标称值为10.0 d B时,误差不超过±1.0 d B。     

Fractional wavelet analysis for the simultaneous quantitative analysis of lacidipine and its photodegradation product by continuous wavelet transform and multilinear regression calibration

Fractional wavelet transform (FWT) was applied to the original absorption spectra of lacidipine (LAC) and its photodegradation product (LACD), and the resulting FWT spectra were processed by continuous wavelet transform (CWT) and multilinear regression calibration (MLRC) for the simultaneous quantitative analysis of both products in their binary mixtures. These methods do not require any chemical separation step and chemical complex reaction to obtain a detectable signal for the degradation product. By using the Mexican hat function, 2 calibration functions for LAC and LACD were obtained by measuring the CWT transformed signals at 416.1 nm for LAC and 414.6 nm for LACD, after FWT processing of the original absorption spectra. The calibration graphs were linear in the concentration range of 5.08-40.64 microg/mL for LAC and 0.51-8.16 microg/mL for LACD. The limit of detection and the limit of quantitation were found to be 0.289 and 0.956 microg/mL for LAC and 0.036 and 0.118 microg/mL for LACD, respectively. For comparison, the MLRC algorithm was applied to the linear regression functions for the individual drug and its photoproduct. In this approach, a set of linear regression functions was obtained from the relationship between concentrations and FWT signals in the wavelength range 411.0-412.4 nm. Both methods were applied to the quantitative evaluation of LAC and LACD in laboratory and pharmaceutical samples, and produced very satisfactory results.     

Dansyl and dabsyl analytical constructs as tools for the accurate estimation of compounds in solid-phase synthesis

The presence of dansyl or dabsyl chromogenic moieties in a solid-phase analytical construct, an assembly of linkers/spacers/sensitizers for improving analytical characterization, allows the accurate estimation of products from solid-phase synthesis by UV detection during liquid chromatography-mass spectrometry analysis in the cleavage solution. The spectroscopic properties of dansylated molecules have been evaluated to verify the "compound-independent UV absorption" necessary for using the chromophore in the accurate estimation. First, measurements on commercial dansylated compounds were made, then a series of construct-like molecules were prepared by solution-phase synthetic procedures and their UV properties were determined. Compound calibration curves were determined, and UV absorption was shown to be both proportional to the compound concentration and compound-independent. An example of a dansyl construct derivative was then prepared on a polymeric matrix, and an accurate estimation using the calibration curves was carried out in the cleavage solution. Good agreement was found between the calculated amount of released compound using the UV calibration curves and the calculated amount using both (1)H NMR and LC/chemiluminescent nitrogen detection quantitative techniques. Preliminary studies using the dabsyl moiety as an improved chromophore with higher wavelength and extinction coefficient are also reported.