偏最小二乘法分光光度同时测定复方扑热息痛片中各组分含量

本文介绍了偏最小二乘法(PLS)用于多组分分光光度分析的基本原理和算法.研究了复方扑热患痛片中扑热息痛、阿司匹林和咖啡因的PLS测定方法,各组分的平均回收率分别为99.88±0.33％、99.99±0.14％和99.92±1.24％(置信度95％).     

偏最小二乘法用于研究酚类物质的竞争吸附

将偏最小二乘法(PLS)用于紫外-可见分光光度分析,同时测定水溶液中苯酚、对甲氧基苯酚和α-萘酚三种组分,并将此方法用于研究苯酚、对甲氧基苯酚和α-萘酚在水溶液中的竞争吸附.结果表明:合成样本的回收率在96%~107.6%之间,结果比较令人满意.采用PLS法计算三种酚类物质吸附后的平衡浓度和吸附量,其结果与采用LCA(Langmuir Competitive Adsorption)模型预测的结果较为接近.     

Attenuated Total Reflection-Fourier transform infrared analysis of the fermentation process of pineapple

A direct and reagent free procedure has been developed to monitor the fermentation process of pine apple nectar using Attenuated Total Reflectance Fourier-transform mid-infrared spectrometry (FT-IR) and multivariate analysis. A classical 4² design for standards was employed for calibration using the information in the spectral range from 907 to 1531 cm⁻¹ of the first order derivative spectra after mean centering of infrared data. The root mean square error of calibration (RMSEC) of 0.040, 0.021, 0.063 and 0.074% w/w were obtained for glucose, fructose, saccharose and ethanol, respectively, and a mean relative validation error of 2.9, 2.1, 2.6 and 3.6% was achieved for glucose, fructose, saccharose and ethanol. Results obtained by the proposed procedure for the alcohol content at different fermentation levels were statistically comparable with those obtained by a reference spectrometric method. So, FT-IR spectrometry provides a fast alternative to long and tedious classical procedures to ethanol determination and sugar enzymatic analysis.     

Solid sampling Fourier transform infrared determination of Mancozeb in pesticide formulations

A series of approaches have been assayed for FTIR determination of Mancozeb in several solid commercial fungicides using different calibration strategies. The simplest procedure was based on the use of the ratio between the absorbance of a characteristic band of Mancozeb and that of a KSCN internal standard measured in the FTIR spectra obtained from KBr pellets. It was employed the quotient between peak height absorbance values at 1525 cm⁻¹ for Mancozeb and 2070 cm⁻¹ for KSCN. In these conditions a precision as relative standard deviation (RSD) of 0.6% and a relative accuracy error of 0.8% (w/w) were found. For complex formulations, containing other compounds with characteristic absorption bands at different wavenumbers than Mancozeb, one of them was used as internal reference being employed the standard addition approach. In this case, the Mancozeb bands at 1525 cm⁻¹ or at 1289 cm⁻¹ were employed, being used the ferrocyanide band at 2075 cm⁻¹ as internal reference. RSD values between 0.7-1.4% and a relative accuracy error of 3% (w/w) were found. A third strategy was based on the use of partial least squares (PLS) calibration. A reference set was prepared mixing Mancozeb, Kaolin, Cymoxanil and KBr, being predicted the Mancozeb concentration in pesticide formulations by using the quotient between absorbance bands of Mancozeb and those of Cymoxanil. In these conditions a relative accuracy error of 0.6% (w/w) and a relative standard deviation of 1.3% were found.     

Spectral regions selection to improve prediction ability of PLS models by changeable size moving window partial least squares and searching combination moving window partial least squares

Changeable size moving window partial least squares (CSMWPLS) and searching combination moving window partial least squares (SCMWPLS) are proposed to search for an optimized spectral interval and an optimized combination of spectral regions from informative regions obtained by a previously proposed spectral interval selection method, moving window partial least squares (MWPLSR) [Anal. Chem. 74 (2002) 3555]. The utilization of informative regions aims to construct better PLS models than those based on the whole spectral points. The purpose of CSMWPLS and SCMWPLS is to optimize the informative regions and their combination to further improve the prediction ability of the PLS models. The results of their application to an open-path (OP)/FT-IR spectra data set show that the proposed methods, especially SCMWPLS can find out an optimized combination, with which one can improve, often significantly, the performance of the corresponding PLS model, in terms of low prediction error, root mean square error of prediction (RMSEP) with the reasonable latent variable (LVs) number, comparing with the results obtained using whole spectra or direct combination of informative regions for a compound. Regions consisting of the combinations obtained can easily be explained by the existence of IR absorption bands in those spectral regions.     

A Novel Preprocessing Algorithm for Three-Way HPLC Data

Orthogonal signal correction (OSC) was a data preprocessing algorithm. It ensured that the filtered information was irrelevant to concentration data while using it to filter the noise from the original data. This paper extended the OSC application range from two-way data to three-way data. Two drug data sets, Enoxacin, Norfloxacin, Ciprofloxacin and Betamethasone, cortisone acetate, prednisone acetate, showed that the application of the OSC algorithm to three-way HPLC data was feasible and needed further research.     

用数值遗传算法改进非线性PLS法进行构效关系研究

将数值遗传算法同非线性ＰＬＳ结合，改进和完善了非线性ＰＬＳ，推导了指数，对数，倒数和Ｓｉｇｍｏｉｄ函数的公式，构造了可以处理多种非线性函数关系的算法，可用于解决复杂的结构与性能相互关系。     

Nutritional parameters of commercially available milk samples by FTIR and chemometric techniques

A chemometric study on the prediction of the main nutritional aspects of milk has been carried out by using fourier transform infrared spectroscopy (FTIR) attenuated total reflectance (ATR) measurements of commercially available milk samples of different types. Whole, semi and skimmed milks, enriched or not with calcium, vitamins or modified by alteration of lipid or sugar composition were considered. After evaluating different strategies for data acquisition and ATR cleaning between samples, hierarchical cluster analysis (HCA) was carried out for classification of samples in order to choose the calibration set. The prediction capabilities of partial least squares (PLS) data treatment were evaluated in order to obtain information about total fat, total protein, total carbohydrates (CH), calories and calcium. On using the mean square error of cross-validation and prediction as control variables, a critical evaluation were made about the calibration set to be used, the spectral range to be considered and the data treatment (PLS-1 or PLS-2) to be performed. By selecting a calibration set of 33 samples the properties of 48 samples were predicted with relative precision of triplicates of 0.062, 0.040 and 0.039% w/v for total fat, protein and carbohydrates, and 0.66 kcal/100 ml for calories, and 2.1 mg of Ca/100 ml. The mean difference (d_x−y) between predicted and actual values and standard deviation of mean differences (s_x−y), were of 0.06 (0.38), 0.03 (0.18) and −0.15 (0.41), being s_x−y values between brackets, for total fat, proteins and carbohydrates, 0.06 (3.8) kcal/100 ml for calories and −4.5 (9) mg/100 ml for calcium.The sensitivity and selectivity of the methodology developed were evaluated on terms of the net analyte signal. Selectivity factors ranging from 2 to 7.6% have been calculated for the five parameters considered.     

Simultaneous measurement of glucose and glutamine in aqueous solutions by near infrared spectroscopy

A method is described for measuring the concentrations of both glucose and glutamine in binary mixtures from near infrared (NIR) absorption spectra. Spectra are collected over the range from 5000–4000/cm (2.0–2.5μm) with a 1-mm optical path length. Glucose absorbance features at 4710, 4400, and 4300/cm and glutamine features at 4700, 4580, and 4390/cm provide the analytical information required for the measurement. Multivariate calibration models are generated by using partial least squares (PLS) regression alone and PLS regression combined with a preprocessing digital Fourier filtering step. The ideal number of PLS factors and spectral range are identified separately for each analyte. In addition, the optimum Fourier filter parameters are established for both compounds. The best overall analytical performance is obtained by combining Fourier filtering and PLS regression. Glucose measurements are established over the concentration range from 1.66–59.91 mM, with a standard error of prediction (SEP) of 0.32 mM and a mean percent error of 1.84%. Glutamine can be measured over the concentration range from 1.10–30.65 mM with a SEP of 0.75 mM and a mean percent error of 6.67%. These results demonstrate the analytical utility of NIR spectroscopy for monitoring glucose and glutamine levels in mammalian and insect cell cultures.