Construction of global and robust near-infrared calibration models based on hybrid calibration sets using Partial Least Squares (PLS) regression

Near-infrared spectroscopy (NIR) models built on a particular instrument are often invalid on other instruments due to spectral inconsistencies between the instruments. In the present work, global and robust NIR calibration models were constructed by partial least square (PLS) regression based on hybrid calibration sets, which are composed of both primary and secondary spectra. Three datasets were used as case studies. The first consisted of 72 radix scutellaria samples measured on two NIR spectrometers with known baicalin content. The second was composed of 80 corn samples measured on two instruments with known moisture, oil, and protein concentrations. The third dataset included 279 primary samples of tobacco with known nicotine content and 78 secondary samples of tobacco with known nicotine concentrations. The effect of the number of secondary spectra in the hybrid calibration sets and the methods for selecting secondary spectra on the PLS model performance were investigated by comparing the results obtained from different calibration sets. This study shows that the global and robust calibration models accurately predicted both primary and secondary samples as long as the ratios of the number of primary spectra to the number of secondary spectra were less than 22. The models performance was not influenced by the selection method of the secondary spectra. The hybrid calibration sets included the primary spectral information and also the secondary spectra; information, rendering the constructed global and robust models applicable to both primary and secondary instruments.     

偏最小二乘变量筛选法在毒品来源分析中的应用

提出了一种新的偏最小二乘变量筛选方法,该方法利用PLS回归建模过程中的一些信息,删除一部分冗余的或对建模影响不大的变量来简化、优化预报模型。用此方法结合变量扩维方法处理云南昆明、思茅、西双版纳3个来源地缴获的244个海洛因样本的ICP-MS数据时,与传统的算法比较,模型的判别准确率得到大大提高,达到95%以上。且所得到的模型含变量少,很容易分析或解释各变量对模型的影响。因此该方法可用于对毒品来源有效的识别或鉴定。     

Simultaneous determination of Cu(II), Ni(II) and Zn(II) by peroxyoxalate chemiluminescence using Partial Least Squares calibration

It was found that the ions Cu(II), Ni(II) and Zn(II) can attenuate the peroxyoxalate chemiluminescence emission, which was used to develop an analytical procedure for the simultaneous determination of these ions in a stopped-flow system using Partial Least Square (PLS) calibration. Acetonitrile was used to dissolve TCPO and to prepare a mixture of fluorescein, H(2)O(2) and imidazole. These solutions were carried using two peristaltic pumps, while a third pump was employed to propel the aqueous solutions of the metallic ions. All solutions were mixed in the quartz cell of a Campsec CL detector connected to a personal computer to register the CL development using the Clarity software. Under the optimum operative conditions each ion produced a specific CL development with maximum intensities at 0.280 min for Zn(II), 0.307 min for Ni(II) and 0.327 min for Cu(II). The latter exhibited the highest inhibition effect. The experimental calibration set was composed of 16 sample solutions using a central design for three component mixtures with scaled values. The proposed method offers the advantages of simplicity, good precision and accuracy for the simultaneous determination of Ni(2+), Cu(2+) and Zn(2+) in water samples.     

Variable selection by modified IPW (iterative predictor weighting)-PLS (partial least squares) in continuous wavelet regression models

Variable selection is often used to produce more robust and parsimonious regression models. But when they are applied directly to the raw near-infrared spectra, it is not easy to select appropriate variables because background and noise will often overshadow or overlap the absorption bands of analyte. In this work, a new hybrid algorithm based on the selection of the most informative variables in the continuous wavelet transform (CWT) domain is described. The strategy is a combination of CWT and a procedure of modified iterative predictor weighting-partial least square (mIPW-PLS). After elimination of the background and noise in NIR spectra by CWT, the mIPW-PLS approach is used to select the most informative CWT coefficients. With the selected CWT coefficients, a PLS model is built finally for prediction. It is indicated that the extraction of most important variables in the CWT domain can effectively avoid the interference of background and noise, and result in a high quality of regression model with a very small number of variables and fewer PLS components.     

偏最小二乘分光光度法同时测定扑热息痛等五组分含量

本文将偏最小二乘分光光度法应用于感冒液中扑热息痛、扑尔敏、咖啡因、对氨基酚和愈创木酚甘油醚五组分含量的分析研究，介绍了基本原理和具体的分析步骤。实验结果表明，偏最小二乘分光光度法对样品各组分的平均回收率在96．4％－105．0％之间，样品不经分离即可同时测定，取得了满意的分析结果。     

仪器噪声在近红外光谱偏最小二乘模型内的传播效应

在实际多元校正应用中有很多因素会影响偏最小二乘(PLS)模型的预测效果,作为光谱数据本源的仪器噪声是其中的重要影响因素。以往的研究工作多使用各种滤波器或平滑方法来降低仪器噪声的影响,然而对于仪器噪声如何影响偏最小二乘的建模过程和模型预测能力鲜有报道。该文阐述并论证了仪器噪声怎样通过第一个隐变量的计算被引入模型中,经过对偏最小二乘计算过程的理论推导,论述了噪声的引入对偏最小二乘权重向量、载荷向量计算具有累积效应,并随着后续隐变量的计算不断在模型中传递,从而对偏最小二乘模型产生影响。同时对偏最小二乘模型的预测误差进行理论分解,将其划分为无噪理想模型本身的误差和由噪声传播导致的误差。结果表明,仪器噪声不仅会降低偏最小二乘模型的预测性能,还会影响偏最小二乘模型的最优复杂度选择。     

X-射线荧光光谱分析中偏最小二乘回归技术与基本参数法的研究

将偏最小二乘回归技术(PLS)与X-射线荧光分析中的基本参数法(FP)相结合,编制PLSFP软件,运用熔样技术,可以定量测定地质岩石样品中的十三个主,次量元素,并使准确度提高,模型预测能力增强。模型选择和最佳维数的确定方法是成功的关键。PLSFP软件采用结构化编程,由标准FORTRAN 77语言写成,可在UNIX,XENIX和DOS操作系统下运行。     

Determination of Quercetin and Luteolin in Paprika Samples by Voltammetry and Partial Least Squares Calibration

Quercetin and luteolin are flavonoids with beneficious properties, which are present in paprika. In this work, both have been determined in paprika by using electrochemistry combined with chemometrics. The electrochemical oxidation mechanisms of both analytes have been studied through sampled direct current (DC) voltammetry, differential pulse voltammetry (DPV) and Square Wave Voltammetry (SWV), making use of a glassy carbon electrode. The final technique selected for the quantification was DPV due to its high repeatability with respect SWV. The chemical variables and the instrumental parameters were optimized and the final conditions employed were ethanol: water (20 : 80), 0.75 mol dm⁻³ of HCl, and a pulse amplitude of 50 mV. Due to the facts that oxidation potential of both analytes were quite similar, their DPV peaks were overlapped, and also because the analytes interaction during the electrochemical process causes a non‐additivity of the signals, they could not be quantified separately by direct measurement of peak intensity. For this reason, a chemometric algorithm was applied (partial least squares (PLS) regression in its modality PLS‐2). In the case of validation samples, appropriate sets of calibration and validation were built and good results were obtained. This methodology was applied to real paprika samples and the results were similar to those obtained with a HPLC method previously reported.     

Rapid Determination of Cotton Content in Textiles by Near-Infrared Spectroscopy and Interval Partial Least Squares

Textile products must be marked by fabric type and composition on the label and cotton is by far the most important fiber in the industry and often needs fast quantitative analysis. The corresponding standard methods are very time-consuming and labor-intensive. The work focuses on exploring the feasibility of combining near-infrared (NIR) spectroscopy and interval-based partial least squares (iPLS) for determining cotton content in textiles. Three types of partial least square (PLS)-based algorithms were used for experimental measurements. A total of 91 cloth samples with cotton content ranging from 0 to 100% (w/w) were collected and all compositions are commercially available on the market in China. In all cases, the original spectrum axis was split into 20 subintervals. As a result, three final models, i.e., the iPLS model on a single subinterval, the backward interval partial least squares (biPLS) model on the region remaining six subintervals, and the moving window partial least squares (mwPLS) model with a window of 75 variables, achieved better results than the full-spectrum PLS model. Also, no obvious differences in performance were observed for the three models. Thus, either iPLS or mwPLS was preferred considering their simplicity, which suggested that iPLS and mwPLS combined with NIR technique may have potential for the rapid determination of the cotton content of textile products with comparable accuracy to standard procedures. In addition, this approach may have commercial and regulatory advantages that avoid labor-intensive and time-consuming chemical analysis.     

Chemometric Assisted UV-Spectrophotometric Methods Using Multivariate Curve Resolution Alternating Least Squares and Partial Least Squares Regression for Determination of Beta-Antagonists in Formulated Products: Evaluation of the Ecological Impact

In this study, UV-spectrophotometry coupled with chemometrics has been utilized to enhance the sustainability of quality control analysis of beta antagonists. First, we developed and optimized two eco-friendly chemometric-assisted methods without preliminary separation utilizing (1) multivariate curve resolution alternating least squares (MCR-ALS) and (2) well-established partial least squares regression (PLSR) multivariate calibration for the resolution and quantification of the most commonly prescribed beta antagonists in active pharmaceutical ingredients or commercial pharmaceutical products. The performance of the two proposed chemometric methods was computed and compared. Second, a comprehensive qualitative and quantitative evaluation of the eco-friendliness of the developed methods was performed utilizing the following greenness assessment tools: Green Analytical Procedure Index (GAPI), Analytical Eco-scale assessment (AES) tool, Raynie and Driver’s assessment tool and Analytical GREEnness Metric (AGREE). The models showed satisfactory recovery with a range from 99.83% to 101.12% for MCR-ALS and from 99.66% to 101.54% for PLSR. The optimized models were employed for green analysis of the investigated beta-blockers in single or co-formulated formulations without prior separation. The predictivity of the proposed MCR-ALS and the well-established PLSR method were very comparable. Nevertheless, the MCR-ALS method has the ability to recover the pure spectra of the studied analytes and the interferences as well. The proposed chemometric methods are fast, precise and do not need any sample pretreatment. In addition, they can be used as a benign substitute for the traditional methods used for the analysis of the investigated drugs in pharmaceutical products without harmful impacts on human health and the environment. They also provide advantages in terms of low solvent usage, reduced energy consumption and short analysis time, making them a safe and sustainable approach for quality control analysis.     

非线性偏最小二乘法在速效伤风胶囊紫外分光光度分析中的应用

本文介绍了非线性偏最小二乘法的基本原理及算法。以速效伤风胶囊的紫外分光光度分析为例,扑热息痛、咖啡因、扑尔敏、人工牛黄四组分的测定结果满意,且明显好于线性偏最小二乘法。本法为多组分混合体系的分光光度分析提供了更为理想的新途径。     

Genetic Algorithm Based Potential Selection in Simultaneous Voltammetric Determination of Isoniazid and Hydrazine by Using Partial Least Squares (PLS) and Artificial Neural Networks (ANNs)

The voltammetric behavior of isoniazid and hydrazine at an overoxidized polypyrrole modified glassy carbon electrode has been investigated. The obtained cyclic voltammograms showed that their oxidation peaks were overlapped and it is difficult to determine them individually from a mixture without separation. To overcome this limitation, a procedure was proposed for resolution of overlapped voltammetric signals from mixtures of isoniazid and hydrazine. In this procedure, genetic algorithm was used for the selection of potentials for partial least squares. A feed forward artificial neural network with back propagation error algorithm was used to process the nonlinear relationship between currents and concentrations of hydrazine and isoniazid. The proposed method was suitable for determination of isoniazid in pharmaceutical tablets and detection of hydrazine impurities in the same samples.     

U-PLS/RBL三维荧光法测定藤络宁胶囊中东莨菪内酯含量

研究了东莨菪内酯的荧光性质和最佳实验条件,发现体系的最佳p H值为9.0,最大激发波长为375nm,最大发射波长为460 nm。在激发波长310~420 nm,发射波长400~550 nm范围内采集实际样本的三维荧光数据矩阵。采用二阶校正中的U-PLS/RBL(Unfolded partial least squares coupled to residual bilinearization)解析三维荧光数据阵,成功地测定了藤络宁胶囊中的东莨菪内酯含量。用U-PLS/RBL解析藤络宁胶囊中的东莨菪内酯含量,结果与HPLC方法一致,说明荧光解析法结果准确可靠。用U-PLS/RBL解析藤络宁胶囊样品的加标回收率为100.4%。相比于色谱方法,荧光方法具有操作费用低及绿色环保等优点。     

同时测定铁钴铜的小波软阈值核心偏最小二乘法

提出了一种小波软阈值核心偏最小二乘法，同时测定铁、钴、铜；该法结合小波软阈值法和主组分分析改进除噪声质量，与其它软阈值法比较选用了HYBRID法；通过最佳化，小波函数和低频截止收缩水平（L）分别选用Symmlet6和2；设计了一个名为软阈值小波核心偏最小二乘法（STWKPLS）的程序进行全部计算，实验结果表明该法是成功的，并且优于核心偏最小二乘法。     

偏最小二乘回归用于近红外光谱分析的稳健策略

偏最小二乘法（PLS）在近红外光谱（NIR）定量分析中占有重要地位,但预测结果往往容易受到样本分组和奇异样本等因素的影响,稳健性不强。多模型PLS (EPLS）方法在模型稳健性上得到提高,然而它无法识别样本中存在的奇异样本。为了同时提高模型的预测准确性和稳健性,本文提出了一种根据取样概率重新取样的多模型PLS方法,称为稳健共识PLS（RE-PLS）方法。该方法通过迭代赋权偏最小二乘法(IRPLS)计算样本回归残差得到每个校正集样本的取样概率,然后根据样本的取样概率来选择训练子集建立多个PLS模型,最后将所有PLS模型的预测结果平均作为最终预测结果。该方法用于两种不同植物样品的近红外光谱建模,并与传统的PLS及EPLS方法进行比较。结果表明该方法可以有效的避免校正集中奇异样本对模型的影响,同时可以提高预测精确度和稳健性。对于含有较多奇异样本的,复杂近红外光谱烟草实际样本,利用简单PLS或者EPLS方法建模预测效果不是很理想,而RE-PLS凭借其独特优势则有望在这种复杂光谱定量分析中得到广泛的应用。     

Resolution of Differential Pulse Voltammetric Peaks Using Genetic Algorithm Based Variable Selection‐Partial Least Squares and Principal Component‐Artificial Neural Networks

Differential Pulse Voltammetry has been used for the simultaneous determination of cysteine, tyrosine and trptophan on the unmodified glassy carbon electrode. In the analysis of these analytes in the same samples, the main difficulty is the high degree of overlapping of voltammograms. The relationships between the currents and the concentrations are complex and highly nonlinear. The predictive ability of principal component regression (PCR), partial least squares regression (PLS), genetic algorithm‐partial least squares regression (GA‐PLS) and principal component‐artificial neural networks (PC‐ANNs) were examined for simultaneous determination of three amino acids. For a regression model, everything that could not help in constructing the model may be considered as noise without further specification. PC‐ANN and GA‐PLS use significant data and show superiority over other applied multivariate methods. The proposed method was also applied satisfactorily to determination of analytes in some synthetic samples.     

偏最小二乘法—流动注射pH梯度技术用于同时测定铜和钴

以PAR作显色剂,用流动注射pH梯度技术测定多个不同pH下的吸光度,以偏最小二乘法建立校正模型并预测,对Cu~(2+)、Co~(2+)二元素进行了同时测定,其计算结果优于主成分回归及多元线性回归法。