Near-IR Spectroscopic Determination of NaCl in Aqueous Solution

1992 ◽  
Vol 46 (12) ◽  
pp. 1809-1815 ◽  
Author(s):  
Jie Lin ◽  
Chris W. Brown
Keyword(s):  
Aqueous Solution ◽  
Temperature Effects ◽  
Continuous Monitoring ◽  
Principal Component Regression ◽  
Principal Component ◽  
Standard Errors ◽  
Near Ir ◽  
Linear And Nonlinear ◽  
Ir Spectroscopic

The concentrations of NaCl in aqueous solutions have been determined with the use of near-IR spectra between 1100 and 1900 nm. Models expressing the concentration of NaCl are developed with linear and nonlinear regression with the use of the absorbances at selected wavelengths and with principal component regression (PCR) using entire spectra. Temperature perturbations on water bands interfere with the measurement of NaCl but can be removed by linear or nonlinear regressions using the absorbances at the wavelengths where the temperature effects are zero, or they can be accounted for by PCR. Standard errors of 5 mM and a detection limit of IS mM are obtained for NaCl. This technique can be applied for quantitative analysis of NaCl in the laboratory or can be readily adapted for continuous monitoring in process control.

Determination of Cholesterol Using a Novel Magnetohydrodynamic Acoustic-Resonance Near-IR (MARNIR) Spectrometer

1993 ◽  
Vol 47 (7) ◽  
pp. 887-890 ◽  
Author(s):  
Robert G. Buice ◽  
Robert A. Lodder
Keyword(s):  
Prediction Error ◽  
Principal Component Regression ◽  
Principal Component ◽  
Acoustic Resonance ◽  
Selection Methods ◽  
Wavelength Selection ◽  
Spectral Techniques ◽  
Near Ir ◽  
Physical Environments

Near-IR spectrometric determination of minor constituents of biological systems is complicated by the fact that near-IR spectra of these materials vary in different chemical and physical environments. In such cases, wavelength selection methods and full-spectral techniques such as partial least-squares and principal component regression (which weight each wavelength in calibration) produce excess error because they must attempt to model both variations in major constituents and variations in the analyte. A magnetohydrodynamic acoustic-resonance near-IR (MARNIR) spectrometer can determine major constituents of biological materials noninvasively and nondestructively, leaving the near-IR spectrum of the analyte to be used quantitatively with less prediction error.

scholarly journals Application of Derivative, Derivative Ratio, and Multivariate Spectral Analysis and Thin-Layer Chomatography-Densitometry for Determination of a Ternary Mixture Containing Drotaverine Hydrochloride, Caffeine, and Paracetamol

2007 ◽  
Vol 90 (2) ◽  
pp. 391-404 ◽  
Author(s):  
Fadia H Metwally ◽  
Yasser S El-Saharty ◽  
Mohamed Refaat ◽  
Sonia Z El-Khateeb
Keyword(s):  
Thin Layer ◽  
Least Squares ◽  
Ternary Mixture ◽  
Principal Component Regression ◽  
Pharmaceutical Preparations ◽  
Principal Component ◽  
Standard Addition ◽  
Drotaverine Hydrochloride ◽  
Assay Precision

Abstract New selective, precise, and accurate methods are described for the determination of a ternary mixture containing drotaverine hydrochloride (I), caffeine (II), and paracetamol (III). The first method uses the first (D1) and third (D3) derivative spectrophotometry at 331 and 315 nm for the determination of (I) and (III), respectively, without interference from (II). The second method depends on the simultaneous use of the first derivative of the ratio spectra (DD1) with measurement at 312.4 nm for determination of (I) using the spectrum of 40 μg/mL (III) as a divisor or measurement at 286.4 and 304 nm after using the spectrum of 4 μg/mL (I) as a divisor for the determination of (II) and (III), respectively. In the third method, the predictive abilities of the classical least-squares, principal component regression, and partial least-squares were examined for the simultaneous determination of the ternary mixture. The last method depends on thin-layer chromatography-densitometry after separation of the mixture on silica gel plates using ethyl acetatechloroformmethanol (16 + 3 + 1, v/v/v) as the mobile phase. The spots were scanned at 281, 272, and 248 nm for the determination of (I), (II), and (III), respectively. Regression analysis showed good correlation in the selected ranges with excellent percentage recoveries. The chemical variables affecting the analytical performance of the methodology were studied and optimized. The methods showed no significant interferences from excipients. Intraday and interday assay precision and accuracy values were within regulatory limits. The suggested procedures were checked using laboratory-prepared mixtures and were successfully applied for the analysis of their pharmaceutical preparations. The validity of the proposed methods was further assessed by applying a standard addition technique. The results obtained by applying the proposed methods were statistically analyzed and compared with those obtained by the manufacturer's method.

scholarly journals Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form

2021 ◽  
Vol 19 (1) ◽  
pp. 205-213
Author(s):  
Hany W. Darwish ◽  
Abdulrahman A. Al Majed ◽  
Ibrahim A. Al-Suwaidan ◽  
Ibrahim A. Darwish ◽  
Ahmed H. Bakheit ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simultaneous Determination ◽  
Predictive Power ◽  
Principal Component Regression ◽  
Selection Procedure ◽  
Principal Component ◽  
Chemometric Methods ◽  
Full Spectrum ◽  
Azilsartan Medoxomil

Abstract Five various chemometric methods were established for the simultaneous determination of azilsartan medoxomil (AZM) and chlorthalidone in the presence of azilsartan which is the core impurity of AZM. The full spectrum-based chemometric techniques, namely partial least squares (PLS), principal component regression, and artificial neural networks (ANN), were among the applied methods. Besides, the ANN and PLS were the other two methods that were extended by genetic algorithm procedure (GA-PLS and GA-ANN) as a wavelength selection procedure. The models were developed by applying a multilevel multifactor experimental design. The predictive power of the suggested models was evaluated through a validation set containing nine mixtures with different ratios of the three analytes. For the analysis of Edarbyclor® tablets, all the proposed procedures were applied and the best results were achieved in the case of ANN, GA-ANN, and GA-PLS methods. The findings of the three methods were revealed as the quantitative tool for the analysis of the three components without any intrusion from the co-formulated excipient and without prior separation procedures. Moreover, the GA impact on strengthening the predictive power of ANN- and PLS-based models was also highlighted.

Nondestructive NIR and NIT Determination of Protein, Fat, and Water in Plastic-Wrapped, Homogenized Meat

1992 ◽  
Vol 46 (11) ◽  
pp. 1685-1694 ◽  
Author(s):  
Tomas Isaksson ◽  
Charles E. Miller ◽  
Tormod Næs
Keyword(s):  
Diffuse Reflectance ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Principal Component Regression ◽  
Principal Component ◽  
Prediction Errors ◽  
Optimal Test ◽  
Meat Samples ◽  
Water Contents

In this work, the abilities of near-infrared diffuse reflectance (NIR) and transmittance (NIT) spectroscopy to noninvasively determine the protein, fat, and water contents of plastic-wrapped homogenized meat are evaluated. One hundred homogenized beef samples, ranging from 1 to 23% fat, wrapped in polyamide/polyethylene laminates, were used. Results of multivariate calibration and prediction for protein, fat, and water contents are presented. The optimal test set prediction errors (root mean square error of prediction, RMSEP), obtained with the use of the principal component regression method with NIR data, were 0.45, 0.29 and 0.50 weight % for protein, fat, and water, respectively, for plastic-wrapped meat (compared to 0.40, 0.28 and 0.45 wt % for unwrapped meat). The optimal prediction errors for the NIT method were 0.31, 0.52 and 0.42 wt % for protein, fat, and water, respectively, for plastic-wrapped meat samples (compared to 0.27, 0.38, and 0.37 wt % for unwrapped meat). We can conclude that the addition of the laminate only slightly reduced the abilities of the NIR and NIT method to predict protein, fat, and water contents in homogenized meat.

scholarly journals The Determination of Parkinson’s Drugs in Human Urine by Applying Chemometric Methods

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Guzide Pekcan Ertokus
Keyword(s):  
Urine Sample ◽  
Human Urine ◽  
Principal Component Regression ◽  
Principal Component ◽  
Healthy Person ◽  
Drug Analysis ◽  
Uv Spectrophotometry ◽  
Least Squares Regression ◽  
Chemometric Methods

The spectrophotometric-chemometric analysis of levodopa and carbidopa that are used for Parkinson’s disease was analyzed without any prior reservation. Parkinson’s drugs in the urine sample of a healthy person (never used drugs in his life) were analyzed at the same time spectrophotometrically. The chemometric methods used were partial least squares regression (PLS) and principal component regression (PCR). PLS and PCR were successfully applied as chemometric determination of levodopa and carbidopa in human urine samples. A concentration set including binary mixtures of levodopa and carbidopa in 15 different combinations was randomly prepared in acetate buffer (pH 3.5).). UV spectrophotometry is a relatively inexpensive, reliable, and less time-consuming method. Minitab program was used for absorbance and concentration values. The normalization values for each active substance were good (r2>0.9997). Additionally, experimental data were validated statistically. The results of the analyses of the results revealed high recoveries and low standard deviations. Hence, the results encouraged us to apply the method to drug analysis. The proposed methods are highly sensitive and precise, and therefore they were implemented for the determination of the active substances in the urine sample of a healthy person in triumph.

AN EASY APPROACH FOR ESTIMATING ABSORPTION LOSS IN ORGANIC THIN SOLID FILMS

1999 ◽  
Vol 08 (04) ◽  
pp. 519-525
Author(s):  
SHEN YUQUAN ◽  
LI ZHAO ◽  
ZHAO YUXIA ◽  
ZHAI JIANFENG ◽  
ZHOU JIAYUN ◽  
...  
Keyword(s):  
Spectroscopic Method ◽  
Optical Loss ◽  
Polymeric Films ◽  
Absorption Loss ◽  
Optical Losses ◽  
Thin Solid Films ◽  
Solid Films ◽  
Near Ir ◽  
Ir Spectroscopic

An UV-VIS-Near-IR spectroscopic method for determination of optical loss in organic/polymeric films has been suggested. The optical losses of two polyimide polymers with push-pull azobenzene chromophore attached were examined by this method and the data were calibrated by conventional optical method.

Development and Validation of Chemometric-Assisted Spectrophotometric Methods for Simultaneous Determination of Phenylephrine Hydrochloride and Ketorolac Tromethamine in Binary Combinations

2016 ◽  
Vol 99 (5) ◽  
pp. 1247-1251 ◽  
Author(s):  
Hamed M Elfatatry ◽  
Mokhtar M Mabrouk ◽  
Sherin F Hammad ◽  
Fotouh R Mansour ◽  
Amira H Kamal ◽  
...  
Keyword(s):  
Least Squares ◽  
Simultaneous Determination ◽  
Principal Component Regression ◽  
Principal Component ◽  
Data Matrix ◽  
Ketorolac Tromethamine ◽  
Concentration Data ◽  
Phenylephrine Hydrochloride ◽  
Spectrophotometric Methods

Abstract The present work describes new spectrophotometric methods for the simultaneous determination of phenylephrine hydrochloride and ketorolac tromethamine in their synthetic mixtures. The applied chemometric techniques are multivariate methods including classical least squares, principal component regression, and partial least squares. In these techniques, the concentration data matrix was prepared by using the synthetic mixtures containing these drugs dissolved in distilled water. The absorbance data matrix corresponding to the concentration data was obtained by measuring the absorbances at 16 wavelengths in the range 244–274 nm at 2 nm intervals in the zero-order spectra. The spectrophotometric procedures do not require any separation steps. The accuracy, precision, and linearity ranges of the methods have been determined, and analyzing synthetic mixtures containing the studied drugs has validated them. The developed methods were successfully applied to the synthetic mixtures and the results were compared to those obtained by a reported HPLC method.

scholarly journals Liquid Chromatographic and Spectrophotometric Determination of Diflucortolone Valerate and Isoconazole Nitrate in Creams

2011 ◽  
Vol 94 (1) ◽  
pp. 128-135 ◽  
Author(s):  
Elif Karacan ◽  
Mehmet Gokhan Çaġlayan ◽  
İsmail Murat Palabiyik ◽  
Feyyaz Onur
Keyword(s):  
Principal Component Regression ◽  
Principal Component ◽  
Derivative Spectrophotometry ◽  
Data Matrix ◽  
Concentration Data ◽  
Spectrophotometric Methods ◽  
First Derivative ◽  
First Derivative Spectrophotometry ◽  
Liquid Chromatographic

Abstract A new RP-LC method and two new spectrophotometric methods, principal component regression (PCR) and first derivative spectrophotometry, are proposed for simultaneous determination of diflucortolone valerate (DIF) and isoconazole nitrate (ISO) in cream formulations. An isocratic system consisting of an ACE® C18 column and a mobile phase composed of methanol–water (95+5, v/v) was used for the optimal chromatographic separation. In PCR, the concentration data matrix was prepared by using synthetic mixtures containing these drugs in methanol–water (3+1, v/v). The absorbance data matrix corresponding to the concentration data matrix was obtained by measuring the absorbances at 29 wavelengths in the range of 242–298 nm for DIF and ISO in the zero-order spectra of their combinations. In first derivative spectrophotometry, dA/dλ values were measured at 247.8 nm for DIF and at 240.2 nm for ISO in first derivative spectra of the solution of DIF and ISO in methanol–water (3+1, v/v). The linear ranges were 4.00–48.0 μg/mL for DIF and 50.0–400 μg/mL for ISO in the LC method, and 2.40–40.0 μg/mL for DIF and 60.0–260 μg/mL for ISO in the PCR and first derivative spectrophotometric methods. These methods were validated by analyzing synthetic mixtures. These three methods were successfully applied to two pharmaceutical cream preparations.

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