偏最小二乘紫外分光光度法同时测定甲基苯甲醛三种同分异构体

将偏最小二乘法(PLS)用于紫外分光光度数据的解析,建立了同时测定甲基苯甲醛3种同分异构体的模型。在230～304 nm范围内,将测得的48个样品的吸光度值作为校正集,另18个样品的吸光度值作为预测集用于建模。所建立的邻、间、对甲基苯甲醛模型的平均回收率分别为101.2%、100.2%和98.9%;均方根误差(RMSE)分别为0.2667、0.3853和0.2118;预测浓度范围分别为4.6～16.2μg/mL、5.8～17.4μg/mL和6.5～20.6μg/mL。讨论了混合物中3种同分异构体浓度比例对测定结果的影响,并确定了最佳的浓度比例范围。对模拟样品进行加标回收率试验。并通过与顺、反丁烯二酸两种同分异构体测定结果的比较,得出了有意义的结论。     

间接电合成甲基苯甲醛产物中3种异构体的同时测定

将迭代算法、PLS与紫外吸收光谱法相结合,建立了同时测定二甲苯间接电合成甲基苯甲醛混合6组分中3种甲基苯甲醛含量的新方法。该方法将PLS镶嵌在迭代算法内部,通过多次迭代计算逐步逼近样品真值,提高了光谱的识别能力。将该方法用于4组模拟样本的测定,邻、间、对甲基苯甲醛的平均回收率分别为101%、100%和101%,预测均方差(RMSEP)分别为0.214、0.148和0.057。而应用于5批实际电合成产物中3种甲基苯甲醛同分异构体的同时测定,邻、间、对甲基苯甲醛的平均回收率分别为106%、92%和100%,相对偏差≤±19.7%,与高效液相色谱法测定结果基本吻合。     

偏最小二乘-分光光度法同时测定芦丁与槲皮素的方法研究

芦丁和槲皮素在紫外区的最大吸收波长接近,吸收光谱严重重叠,普通光度法分析难以实现两者的直接测定.该文通过测定以1∶4甲醇-水为溶剂的芦丁、槲皮素标准混合溶液在200～500 nm波长范围的吸收光谱,采用偏最小二乘法(PLS法)建立校正模型,对样品中的芦丁和槲皮素的含量进行预测,建立了偏最小二乘-分光光度法同时测定芦丁和...     

紫外光谱法对维生素E油酸酯、维生素E与油酸的同时测定

建立了混合体系中维生素E、油酸和维生素E油酸酯同时测定的方法,用光纤光谱仪获取混合体系紫外-可见透射光谱.实验按均匀设计建立校正集和预测集,在255 ～315 nm波段采用偏最小二乘法建立了同时定量测定该3组分的校正模型,并用间隔区间偏最小二乘法(iPLS)通过优选建模区间改进油酸的预测模型.采用iPLS能够显著提高模型准确度,尤其对光谱弱响应的物质,最大相对误差从PLS直接建模的54.7%降至iPLS的8.98%,建立的模型可满足动力学研究的原位分析需要.     

偏最小二乘紫外分光光度法同时测定丁烯二酸的顺反异构体

将偏最小二乘法用于紫外分光光度分析,在pH=1.4的磷酸溶液中,同时测定了丁烯二酸的顺、反异构体。确定了测定的最佳波长范围为190～268nm;测得23个混合标样的吸光度值用于建立模型,顺、反丁烯二酸的浓度范围为3.0～14.0mg/L和1.0～13.0mg/L。所建立的测定二者模型的相关系数分别为0.9951和0.9983;平均回收率分别为100.8%和100.7%;均方根误差(RMSE)分别为0.3667和0.2233;预测相对误差(REP)分别为5.05%和3.49%。对3个批次反丁烯二酸样品的测定结果与高效液相色谱法的测定结果进行比较,经成对t检验表明,两种方法的测定结果无显著性差异。     

傅里叶变换红外光声光谱法测定土壤中有效磷

以中国科学院封丘生态实验站长期定位实验区的土样为材料(68样),利用傅里叶转换红外光声光谱测定土壤有效磷:以Olsen-P为因变量,通过傅里转换红外光声光谱构建偏最小二乘法和人工神经网络模型,利用模型进行预测。结果表明,偏最小二乘法模型的相关系数(R2)为0.96,校正标准偏差为1.79mg/kg,验证标准偏差为5.25mg/kg;人工神经网络模型的校正系数为0.84,校正标准偏差为2.40mg/kg,验证标准偏差为5.43mg/kg。两种模型均可以用于土壤有效磷的预测,且偏最小二乘模型优于人工神经网络模型。该方法的特点是无需样品前处理,且测定对样品无破坏,为土壤有效磷的快速测定提供新的手段。     

偏最小二乘-分光光度法同时测定福美锌和代森锰农药残留量

利用紫外可见分光光度法研究了农药福美锌和代森锰与苯基荧光酮的相互作用,发现反应后的产物分别在波长为551和554 nm处最大有吸收,但光谱严重重叠.实验采集了450～700 nm波长范围吸光度数据,并对该数据进行一阶求导后用偏最小二乘法处理,据此建立了偏最小二乘-分光光度法同时测定福美锌和代森锰两种农药的新方法.福美锌和代森锰的线性范围分别为0.3～6.0和0.2～3.5 μg/mL;检出限分别为0.22和0.13 μg/mL.混合样品分析无需分离,方法简单、快速.用于水果、大米和自来水等实际样品测定.     

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。     

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。     

多模型共识偏最小二乘法用于近红外光谱定量分析

将多模型共识偏最小二乘法用于近红外光谱定量分析。利用随机抽取的训练子集建立一系列偏最小二乘模型,选取其中性能较好的部分模型作为成员模型,用这些成员模型来预测未知样品。将该方法用于一组生物样本的近红外光谱与样品中人血清白蛋白、γ-球蛋白以及葡萄糖含量之间的建模研究,并与单模型偏最小二乘法了进行比较。结果 PLS对独立测试集中三种组分进行50次重复预测的平均RMSEP分别为0.1066,0.0853和0.1338,RMSEP的标准偏差分别为0.0174,0.0144和0.0416;而本方法重复预测的平均RMSEP分别为0.0715,0.0750和0.0781,RMSEP的标准偏差分别为0.0033,0.2729×10-4和0.0025。     

Genetic Algorithm Applied to Selection of Wavelength in Partial Least Squares for Simultaneous Spectrophotometric Determination of Nitrophenol Isomers

Abstract

Ternary mixtures of nitrophenol isomers have been simultaneously determined in synthetic and real matrix by application of genetic algorithm and partial least squares model. All factors affecting the sensitivity were optimized and the linear dynamic range for determination of nitrophenol isomers found. The simultaneous determination of nitrophenol mixtures by using spectrophotometric methods is a difficult problem, due to spectral interferences. The partial least squares modeling was used for the multivariate calibration of the spectrophotometric data. A genetic algorithm is a suitable method for selecting wavelength for PLS calibration of mixtures with almost identical spectra without loss prediction capacity. The experimental calibration matrix was designed by measuring the absorbance over the range 300–520 nm for 21 samples of 1–20 µg mL^?1, 1–20 µg mL^?1, and 1–10 µg mL^?1 of m‐nitrophenol, o‐nitrophenol, and p‐nitrophenol, respectively. The root mean square error of prediction for m‐nitrophenol, o‐nitrophenol, and p‐nitrophenol with genetic algorithms and without genetic algorithms were 0.3732, 0.5997, 0.3181 and 0.7309, 0.9961, 1.0055, respectively. The proposed method was successfully applied for the determination of m‐nitrophenol, o‐nitrophenol, and p‐nitrophenol in synthetic and water samples.     

Simultaneous Spectrophotometric Determination of Uranium and Thorium Using Arsenazo III by H‐Point Standard Addition Method and Partial Least Squares Regression

Simultaneous determination of uranium and thorium using arsenazo III as a chromogenic reagent at pH 1.70 by H‐point standard addition method (HPSAM) and partial least squares (PLS) calibration is described. Under optimum conditions, the simultaneous determinations of uranium and thorium by HPSAM were performed. The absorbencies at one pair of wavelengths, 649 and 669 nm, were monitored with the addition of standard solutions of uranium. The results of applying the HPSAM showed that uranium and thorium can be determined simultaneously with weight concentration ratios of uranium to thorium varying from 20:1 to 1:15 in the mixed sample. By multivariate calibration methods such as PLS, it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. In this study, the calibration model is based on absorption spectra in the 600–750 nm range for 25 different mixtures of uranium and thorium. Calibration matrices contained 0.10–21.00 and 0.25–18.5 μg mL^?1 of uranium and thorium, respectively. The RMSEP for uranium and thorium were 0.7400 and 0.7276, respectively. Both proposed methods (HPSAM and PLS) were also successfully applied to the determination of uranium and thorium in several synthetic and real matrix samples.     

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.     

Spectrophotometric simultaneous determination of nitroaniline isomers by orthogonal signal correction-partial least squares

The simultaneous determination of nitroaniline isomer mixtures by using spectrophotometric methods is a difficult problem in analytical chemistry, due to spectral interferences. By multivariate calibration methods, such as partial least squares (PLS), it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. Orthogonal signal correction (OSC) is a preprocessing technique used for removes the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for partial least squares calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 200–500 nm range for 21 different mixtures of nitroaniline isomers. Calibration matrices were containing 1–21, 1–15 and 1–18 μg ml⁻¹ of m-nitroaniline, o-nitroaniline and p-nitroaniline, respectively. The RMSEP for m-nitroaniline, o-nitroaniline and p-nitroaniline with OSC and without OSC were 0.6567, 0.2692, and 0.3134, and 1.3818, 1.2181, and 0.3953, respectively. This procedure allows the simultaneous determination of nitroaniline isomers in real matrix samples and good reliability of the determination was proved.     

Genetic‐Algorithm‐Based Wavelength Selection in Multicomponent Spectrophotometric Determination by PLS: Application on Ascorbic Acid and Uric Acid Mixture

Genetic algorithm (GA) is a suitable method for selecting wavelengths for partial least squares (PLS) calibration of mixtures with almost identical spectra without loss of prediction capacity using the spectrophotometric method. In this study, the concentration model is based on absorption spectra in the range of 200‐320 nm for 25 different mixtures of ascorbic acid (AA) and uric acid (UA). The calibration curve was linear over the concentration range of 1‐15 and 2‐16 μg mL^?1 for ascorbic acid and uric acid, respectively. The root mean square deviation (RMSD) for ascorbic acid and uric acid with GA and without GA were 0.3071 and 0.3006, 0.3971 and 0.7063, respectively. The proposed method was successfully applied to the simultaneous determination of both analytes in human serum and urine samples.     

Simultaneous Spectrophotometric Determination of Benzyl Alcohol and Diclofenac in Pharmaceutical Formulations by Chemometrics Method

Diclofenac sodium (DS) is a drug with analgesic, antipyretic, and anti‐inflammatory properties. It is present in numerous pharmaceutical preparations. In injectable forms, it is usually accompanied by benzyl alcohol (BA) as an excipient, which is used as a blocking anesthetic (4%) and an antiseptic (4–10%). In this work a spectrophotometric methodology was applied in order to determine benzyl alcohol and diclofenac in injectable formulations by applying a multivariate calibration method. By a multivariate calibration method such as partial least squares (PLS), it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. In this study, the concentration model is based on absorption spectra in the 230–320 nm range for 25 different mixtures of benzyl alcohol and diclofenac. Calibration matrix contains 10–95 and 1–50 μg mL^?1 for benzyl alcohol and diclofenac, respectively. The root mean square errors of prediction (RMSEP) for benzyl alcohol and diclofenac were 3.0776 and 1.7557, respectively. The proposed method was validated by using a set of synthetic sample mixtures and subsequently applied to simultaneous determination of benzyl alcohol and diclofenac in two different pharmaceutical formulations.     

Application of Multivariate Calibration Methods for the Simultaneous Multiwavelength Spectrophotometric Determination of Fe(II), Cu(II), Zn(II), and Mn(II) in Mixtures

Abstract

A sensitive method for the simultaneous spectrophotometric determination of Fe(II), Cu(II), Zn(II), and Mn(II) in mixtures has been developed with the aid of multivariate calibration methods, such as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS). The method is based on the spectral differences of the analytes in their complexation reaction with 4‐(2‐pyridylazo)‐resorcinol (PAR) and the use of full spectra with wavelengths in the range of 300–600 nm. It was found that both the spectral positive and negative bands obtained against the PAR blank, are proportional to the concentration for each metal complex. The obtained linear calibration concentration ranges are 0.025–0.6, 0.05–0.8, 0.025–0.8, and 0.05–0.8 µg ml^?1 for Fe(II), Cu(II), Zn(II), and Mn(II), respectively, and the LODs for the four metal ions were found to be approximately 1–3×10^?2 µg ml^?1. The proposed method was applied to a verification set of synthetic mixtures of these four metal ions, with models built in three different wavelength ranges, i.e., 300–450, 450–600, and 300–600 nm, corresponding to the positive, negative bands and their combinations, respectively. It was shown that the PLS model for the 300–600 nm range gave the best results (RPE_T=6.9% and average recovery ～100%; cf. PCR: RPE_T=9.5% and average Recovery ～110%). This method was also successfully applied for the determination of the four metal ions in pharmaceutical preparations, chicken feedstuff, and water samples.     

Application of a Partial Least Squares Regression for the Determination of Nanomolar Concentrations of Scandium in the Presence of Nickel by Adsorptive Stripping Voltammetry

This paper presents the methodology of a very sensitive determination of scandium in excess of nickel by adsorptive stripping voltammetry on a mercury film electrode and PLS regression. A calibration set consisting of binary mixtures containing 5, 15, 25, 35 or 45×10^?9 M Sc(III) and simultaneously 0.5–50×10^?7 M of Ni(II) was used to develop the chemometric PLS calibrations. An external set containing synthetic mixtures of 10, 20, 30, 40×10^?9 M Sc(III) and the same Ni(II) concentration as mentioned above was used to validate the model and evaluate predictive ability. The application of data pretreatment techniques involving baseline correction, smoothing, range‐scaling, mean‐centering and their influence on the PLS model complexity, were also investigated. In the effect, the model for Sc(III), including 6 latent variables, was constructed. The model fulfills validation criteria and is characterized by a good prediction ability (majority of the prediction errors are lower than 10%). This work shows significant progress in the development of a very sensitive analytical technique for the determination of scandium in the presence of different concentrations of nickel by application of multivariate calibration tools.     

Simultaneous Kinetic‐Spectrophotometric Determination of Hydrazine and its Derivatives by Partial Least Squares and Principle Component Regression Methods

Simultaneous kinetic‐spectrophotometric determination of a ternary mixture of hydrazine (HZ) and its derivatives by principal component regression (PCR) and partial least squares (PLS) calibration is described. The methods were based on the difference observed in the reduction rate of iron(III) with HZ, thiosemicarbazide (TSCZ) and phenylhydrazine (PHZ) in the presence of 2,2′‐bipyridine (Bpy). The colored complex of [Fe(Bpy)₃]²⁺ was formed in sodium dodecyl sulfate (SDS) as micellar media, and then monitored at 520 nm. The results showed that simultaneous determination of HZ, TSCZ and PHZ could be performed in their concentration ranges of 1.0–70.0, 0.2–6.0 and 0.1–10.0 μg mL^?1, respectively. The root mean squares errors of prediction (RMSEP) of HZ, TSCZ and PHZ were 0.719, 0.164 and 0.105 (for PLS) 0.788, 0.166 and 0.993 (for PCR), respectively. Both methods (PCR and PLS) were validated using a set of synthetic sample mixtures and then applied for simultaneous determination of HZ, TSCZ and PHZ in water samples.