傅里叶变换用于铁和锌的同时光度测定

研究了傅里叶变换技术用于铁锌二组分的同时分光光度测定，采用傅里叶变换对吸光度数据进行预处理，再结合目标转换因子分析或偏最小二乘分析，结果较普通的目标转换因子分析或偏最小二乘法有显著改善。以傅里叶变换－偏最小二乘法就用于实际铝合金样品中铁和锌的同时测定，结果令人满意。     

钛锡钼钨同时测定多元统计与滤波分辨法比较

采用多元线性回归、主成份回归、偏最小二乘、目标因子分析和自适应滤波等多元统计及滤波分辨法,借金属离子-苯基荧光酮PF-CTMAB显色体系同时测定钼钨钛锡四组分,结果良好。并进行了方法比较。     

偏最小二乘-一阶导数分光光度法测定苯甲酸复方制剂中苯甲酸及水杨酸的含量

复方苯甲酸涂剂主要成分是苯甲酸和水杨酸,其在临床上常用于治疗皮肤疾患,由于紫外吸收光谱重叠较严重,用光度法测定时,彼此相互干扰。计量学方法的兴起为多组分的同时测定提供了一种不需分离的新技术。偏最小二乘法可以最大程度地从校正试样中提取信息,具有较强的数据处理能力,因而优于主成分回归等其它计量学方法。本工作将导数光谱的高灵敏度与偏最小二乘法的优良解析性能相结合,提出了同时测定两组分的偏最小二乘导数分光光度法,方法用于复方苯甲酸制剂中两组分的测定,对加和性不太好的体系,也能得到较为满意的结果。     

人工神经网络紫外光度法同时测定甲基苯甲醛的三种同分异构体及其与偏最小二乘法的比较

同分异构体的同时测定一直是分析化学领域的热点和难点问题,本文将化学计量学中的多元校正方法,如偏最小二乘法和人工神经网络法与紫外分光光度法相结合,同时测定了紫外吸收光谱严重重叠的甲基苯甲醛的三种同分异构体混合体系中各组分的含量。确定了测定的最佳波长范围为230～304 nm;测得48个混合标样的吸光度值用于建立模型,其中,邻、间、对甲基苯甲醛的浓度范围分别为6.0～15.0、7.0～16.0和8.0～19.0 μg·mL-1。7个模拟样品作为监测集用于检验所建立模型的预测性能。本文还讨论了三种组分浓度比例对所建立模型预测性能的影响并确定了可以准确测定的浓度比例范围。所建立的方法用于模拟样品的测定,其回收率在84.00%与109.60%之间。与偏最小二乘法的测定结果比较,经成对t检验表明,两种方法对邻、间甲基苯甲醛测定结果无显著性差异;而对甲基苯甲醛的测定,人工神经网络法的测定结果优于偏最小二乘法。     

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。     

拉曼光谱同时测定乙醇与葡萄糖的方法研究

以共焦拉曼光谱技术为基础,结合96孔板,对比利用一元线性回归法、多元线性回归法、主成分回归法和偏最小二乘法建立定量分析模型,探索同时定量检测乙醇和葡萄糖的快捷方法。对同一组乙醇和葡萄糖混合标准溶液进行定量检测,并用木薯淀粉发酵液进一步验证。结果表明,偏最小二乘法定量结果的平均标准误差(SE)为0.179,平均相对标准偏差(RSD)为0.029,结合二阶导数后分别降至0.106和0.021,说明偏最小二乘法具有良好的紧密度和稳定性;t检验表明,在置信度为95%的条件下,实测值与标准值间不存在显著性差异。研究表明基于拉曼光谱技术的偏最小二乘回归定量方法,能满足实验和生产对乙醇和葡萄糖检测精度的要求,可用于乙醇和葡萄糖相关成分的同时快速检测。     

红外光声光谱技术结合稳健回归用于油菜籽定量分析

将稳健偏最小二乘回归和偏稳健M回归应用于油菜籽红外光声光谱分析中含氮量、含油量与硫苷含量的测定。结果表明,利用红外光声光谱技术可以实现油菜籽品质的快速测定。同时,稳健回归模型较经典偏最小二乘回归模型可以更好地规避异常值影响,进而优化定量分析结果;其中,稳健偏M回归稍优于稳健偏最小二乘回归。     

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。     

紫外分光光度-局部偏最小二乘回归法同时测定三种人造甜味剂

本文报道了一种简便、快速、准确地同时测定3种人造甜味剂安赛蜜、阿斯巴甜和糖精钠的方法。方法基于在p H为3.21的盐酸溶液中对安赛蜜、阿斯巴甜和糖精钠三组分混合溶液进行紫外光度测定,所得重叠光谱数据分别用偏最小二乘回归法(PLSR)、特征峰结合PLSR法和特征峰结合局部偏最小二乘回归法(LPLSR)进行处理。结果表明,选取特征波段的峰值作为自变量,采用4个局部样本做拟合的预报误差最小,总相对偏差仅为3.05%。对果汁样品进行测定,获得了很好的定量分析结果。安赛蜜、阿斯巴甜和糖精钠的定量线性范围分别为1.0~30.0 mg/L、1.0~10.0 mg/L和1.0~10.0 mg/L。     

偏最小二乘法-紫外光度法同时测定防腐剂尼泊金乙酯钠、山梨酸钾和苯甲酸钠

介绍一种快速、简便同时测定食用防腐剂尼泊金乙酯钠、山梨酸钾和苯甲酸钠的紫外光度法。在pH5．72的B—R缓冲溶液中对尼泊金乙酯钠、山梨酸钾和苯甲酸钠3组分混合溶液进行吸光度测定,所得的重叠波谱数据用主成分回归法（PCR）和偏最小二乘法（PLS）逆行处理,结果表明,偏最小二乘法的测定误差较小。尼泊金乙酯钠、山梨酸钾和苯甲酸钠的线性范围均为1～10mg／L,回收率为84．5％～108．2％。用该法对样品进行测定,获得了较好的定量分析结果。     

微分脉冲溶出伏安法结合化学计量学测定醚类除草剂

在pH=6.82的Britton-Robinson缓冲溶液中,采用循环伏安法和微分脉冲溶出伏安法对醚类除草剂甲羧除草醚(Bifenox)和三氟羧草醚(Acifluofen)的伏安行为进行了研究,发现吸附时间为50 s时此电化学体系达到平衡,而且微分脉冲溶出伏安法能给出较高的灵敏度,甲羧除草醚和三氟羧草醚分别在-685 mV和-700 mV处具有良好还原峰,但由于峰电位接近而谱峰重叠,很难分别测定.本文采用化学计量学方法来解析重叠峰并完成这两种除草剂的定量分析.甲羧除草醚和三氟羧草醚的测定线性范围分别为0.02～0.18 μg·5mL~(-1)和0.02～0.16 μg·5mL~(-1),检出限分别为0.0073 μg·5mL~(-1)和0.0068 μg·5mL~(-1).利用该方法对水样中的甲羧除草醚和三氟羧草醚进行直接测定,获得了较好的定量分析结果.     

Simultaneous spectrophotometric determination of drugs in pharmaceutical preparations using multiple linear regression and partial least-squares regression, calibration and prediction methods

Two new methods for the simultaneous determination of acetylsalicylic acid, acetaminophen and caffeine based on total absorbance measurements and their processing by multiple linear regession and partial least-squares regression are proposed. The concentration ranges used to construct the calibration matrix were 4.0-12.0, 2.0-10.0 and 0.9-6.0 μg ml⁻¹ for acetylsalicylic acid, acetaminophen and caffeine respectively. The proposed methods were validated by using a set of synthetic sample mixtures and subsequently applied to the determination of the three active principles in three different pharmaceutical preparations.     

Complementary use of partial least-squares and artificial neural networks for the non-linear spectrophotometric analysis of pharmaceutical samples

The complementary use of partial least-squares (PLS) multivariate calibration and artificial neural networks (ANNs) for the simultaneous spectrophotometric determination of three active components in a pharmaceutical formulation has been explored. The presence of non-linearities caused by chemical interactions was confirmed by a recently discussed methodology based on Mallows augmented partial residual plots. Ternary mixtures of chlorpheniramine, naphazoline and dexamethasone in a matrix of excipients have been resolved by using PLS for the two major analytes (chlorpheniramine and naphazoline) and ANNs for the minor one (dexamethasone). Notwithstanding the large number of constituents, their high degree of spectral overlap and the occurrence of non-linearities, rapid and simultaneous analysis has been achieved, with reasonably good accuracy and precision. No extraction procedures using non-aqueous solvents are required.     

Mass spectrometry and partial least-squares regression: a tool for identification of wheat variety and end-use quality

Rapid methods for the identification of wheat varieties and their end-use quality have been developed. The methods combine the analysis of wheat protein extracts by mass spectrometry with partial least-squares regression in order to predict the variety or end-use quality of unknown wheat samples. The whole process takes approximately 30 min. Extracts of alcohol-soluble storage proteins (gliadins) from wheat were analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Partial least-squares regression was subsequently applied using these mass spectra for making models that could predict the wheat variety or end-use quality. Previously, an artificial neural network was used to identify wheat varieties based on their protein mass spectra profiles. The present study showed that partial least-squares regression is at least as useful as neural networks for this identification. Furthermore, it was demonstrated that partial least-squares regression could be used to predict wheat end-use quality, which has not been possible using neural networks.     

Spectrophotometric determination of metal ions in electroplating solutions in the presence of EDTA with the aid of multivariate calibration and artificial neural networks

Metal ions such as Co(II), Ni(II), Cu(II), Fe(III) and Cr(III), which are commonly present in electroplating baths at high concentrations, were analysed simultaneously by a spectrophotometric method modified by the inclusion of the ethylenediaminetetraacetate (EDTA) solution as a chromogenic reagent. The prediction of the metal ion concentrations was facilitated by the use of an orthogonal array design to build a calibration data set consisting of absorption spectra collected in the 370-760 nm range from solution mixtures containing the five metal ions earlier. With the aid of this data set, calibration models were built based on 10 different chemometrics methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), artificial neural networks (ANN) and others. These were tested with the use of a validation data set constructed from synthetic solutions of the five metal ions. The analytical performance of these chemometrics methods were characterized by relative prediction errors and recoveries (%). On the basis of these results, the computational methods were ranked according to their performances using the multi-criteria decision making procedures preference ranking organization method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive aid (GAIA). PLS and PCR models applied to the spectral data matrix that used the first derivative pre-treatment were the preferred methods. They together with ANN-radial basis function (RBF) and PLS were applied for analysis of results from some typical industrial samples analysed by the EDTA-spectrophotometric method described. DPLS, DPCR and the ANN-RBF chemometrics methods performed particularly well especially when compared with some target values provided by industry.     

Single- and multi-channel detection for generalized quantitative analysis in cases of unresolved chromatographic peaks

Computerized quantification of components under overlapping chromatographic peaks is done by calibration of chromatograms against component mixtures. For conventional (single-channel) detectors, the limitations of earlier methods based on ordinary multiple regression, can be circumvented by data reduction with the aid of principal component analysis with the partial least-squares approach. Simulation studies show that the method can be applied even when there is severe peak overlap, unstable baseline, noisy chromatograms or non-linear detector response. Advantages in the quantification of fused peaks by means of multichannel detectors are outlined. Present limitations on the quantitative evaluation of several overlapping component peaks from a single spectro-chromatogram by means of the partial least-squares method combined with multiple regression on the pure component spectra, are discussed with respect to practical high-performance liquid chromatography.     

Application of partial least-squares regression to the resolution of highly correlated spectra. Simultaneous spectrofluorimetric determination of Al(3+), Ga(3+) and In(3+)

The simultaneous spectrofluorimetric determination of mixtures of aluminium, gallium and indium as their 8-hydroxyquinoline complexes following extraction into chloroform is studied. The high collinearity of the spectra hindered their resolution by multiple linear regression (MLR) methodology; therefore, experimental data were processed by partial least-squares regression (PLSR) methodology. A previous step in the study of three-dimensional fluorescence spectrum is possible to select the best information to quantify this system with high collinearity. Finally the optimal conditions for quantitation, the best data preprocessing procedure and the most suitable spectral mode for calibration were established. Using an external set allowed the three analytes to be determined simultaineously at concentrations below 1 mug ml(-1) with errors less than 10% for aluminium and indium, and 15% for gallium.     

Differential Kinetic Spectrophotometric Determination of Methamidophos and Fenitrothion in Water and Food Samples by Use of Chemometrics

A spectrophotometric method for simultaneous analysis of methamidophos and fenitrothion was proposed by application of chemometrics to the spectral kinetic data, which was based upon the difference in the inhibitory effect of the two pesticides on acetylcholinesterase (AChE) and the use of 5,5′‐dithiobis(2‐nitrobenzoic acid) (DTNB) as a chromogenic reagent for the thiocholine iodide (TChI) released from the acetylthiocholine iodide (ATChI) substrate. The absorbance of the chromogenic product was measured at 412 nm. The different experimental conditions affecting the development and stability of the chromogenic product were carefully studied and optimized. Linear calibration graphs were obtained in the concentration range of 0.5–7.5 ng·mL^?1 and 5–75 ng·mL^?1 for methamidophos and fenitrothion, respectively. Synthetic mixtures of the two pesticides were analysed, and the data obtained processed by chemometrics, such as partial least square (PLS), principal component regression (PCR), back propagation‐artificial neural network (BP‐ANN), radial basis function‐artificial neural network (RBF‐ANN) and principal component‐radial basis function‐artificial neural network (PC‐RBF‐ANN). The results show that the RBF‐ANN gives the lowest prediction errors of the five chemometric methods. Following the validation of the proposed method, it was applied to the determination of the pesticides in several commercial fruit and vegetable samples; and the standard addition method yielded satisfactory recoveries.     

Simultaneous spectrophotometric determination of carbamazepine and phenytoin in serum by PLS regression and comparison with HPLC

Carbamazepine (CBZ) and phenytoin (PHT) are two antiepileptic drugs which are used simultaneously. In this paper a partial least-squares (PLS) calibration method is described for the simultaneous spectrophotometric determination of CBZ and PHT in plasma. Standard binary mixtures of CBZ and PHT have been resolved by application of PLS-1 to their UV spectra. Then, the binary standard solutions, spiked to plasma, were prepared and after the extraction of the drugs, their corresponding UV spectrum were analyzed by PLS regression to calculate the concentration of drugs in unknown plasma. A leave one out cross-validation procedure was employed to find the optimum numbers of latent variables using PRESS. A HPLC method was also applied for simultaneous determination of two drugs in the plasma and in methanol. The mean recoveries obtained by PLS were 98.4 and 98.2 for CBZ and PHT and those obtained by HPLC were 100.1 and 101.7, respectively. Although, the HPLC method showed better performance than PLS, it was found that the results obtained by PLS were comparable with those obtained by HPLC method.     

偏最小二乘吸光光度法测定混合染料浓度

用偏最小二乘（ＰＬＳ）及阻尼因子矩阵（ＣＰＡ）吸光光度法测定混合染料浓度，两种方法所得结果相一致，用于测定四元混合染料中单一染料，结果较为满意。