scholarly journals Detection of Cyanuric Acid and Melamine in Infant Formula Powders by Mid-FTIR Spectroscopy and Multivariate Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Edwin García-Miguel ◽  
Ofelia Gabriela Meza-Márquez ◽  
Guillermo Osorio-Revilla ◽  
Darío Iker Téllez-Medina ◽  
Cristian Jiménez-Martínez ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Ftir Spectroscopy ◽  
Least Squares ◽  
Infant Formula ◽  
Cyanuric Acid ◽  
Principal Component Regression ◽  
Predictive Ability ◽  
Principal Component ◽  
Infant Formulas ◽  
Chemometric Methods

Chemometric methods using mid-FTIR spectroscopy were developed in order to reduce the time of study of melamine and cyanuric acid in infant formulas. Chemometric models were constructed using the algorithms Partial Least Squares (PLS1, PLS2) and Principal Component Regression (PCR) in order to correlate the IR signal with the levels of melamine or cyanuric acid in the infant formula samples. Results showed that the best correlations were obtained using PLS1 (R2: 0.9998, SEC: 0.0793, and SEP: 0.5545 for melamine and R2: 0.9997, SEC: 0.1074, and SEP: 0.5021 for cyanuric acid). Also, the SIMCA model was studied to distinguish between adulterated formulas and nonadulterated samples, giving optimum discrimination and good interclass distances between samples. Results showed that chemometric models demonstrated a good predictive ability of melamine and cyanuric acid concentrations in infant formulas, showing that this is a rapid and accurate technique to be used in the identification and quantification of these adulterants in infant formulas.

Spectrophotometric Simultaneous Determination of Levamisole and Triclabendazole in Tablets by Principal Component Regression and Partial Least Squares Chemometric Methods

2008 ◽  
Vol 59 (2) ◽  
pp. 154-158 ◽  
Author(s):  
Gozde Pektas ◽  
Erdal Dinc ◽  
Dumitru Baleanu
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Principal Component Regression ◽  
Principal Component ◽  
Standard Addition ◽  
Chemometric Methods ◽  
Preliminary Separation ◽  
Absorbance Data ◽  
Good Agreement

Principal component regression (PCR) and partial least squares (PLS) chemometric methods were applied to the simultaneous quantitative analysis of levamisole (LVM) and triclabendazole (TCB) in tablets without using a preliminary separation, even in presence of the overlapping spectra of the above compounds. For both PCR and PLS, a concentration set containing 25 different mixtures of LVM and TCB in the linear concentration range was symmetrically prepared and then the absorbance values of the concentration set were measured at the wavelength set with Dl=0.1 nm in the spectral region of 225-322.3 nm. PCR and PLS calibrations were obtained by applying the PCR and PLS algorithms to the concentration set data (y-block) and their corresponding absorbance data (x-block). The validity of PCR and PLS chemometric methods was performed by using the independent synthetic mixtures and the standard addition technique. Then, these analytical methods were applied to the commercial tablets and a good agreement was obtained between experimental results provided by the application of the PCR and PLS to the synthetic and real samples.

Application of independent component analysis, principal component regression and partial least squares methodologies for the simultaneous potentiometric titration of some amino acids

RSC Advances ◽  
2016 ◽  
Vol 6 (74) ◽  
pp. 69902-69908 ◽  
Author(s):  
A. Hakan Aktaş ◽  
Sermin Göksu Karagöz
Keyword(s):  
Amino Acids ◽  
Independent Component Analysis ◽  
Least Squares ◽  
Simultaneous Determination ◽  
Partial Least Squares ◽  
Potentiometric Titration ◽  
Principal Component Regression ◽  
Principal Component ◽  
Chemometric Methods

Potentiometric titration and chemometric methods were applied to the simultaneous determination of the four amino acids, alanine (ALA), phenylalanine (PHE), leucine (LEU) and lysine (LYS).

scholarly journals Universal procedures for spectrophotometric determination of anticoccidial drugs; application to multi-ingredient veterinary formulation and computational investigations for multivariate analysis

2021 ◽  
Vol 12 (4) ◽  
pp. 368-376
Author(s):  
Mahmoud Mohamed Abbas ◽  
Amira Mabrouk El-Kosasy ◽  
Lobna Abd El-Aziz Hussein ◽  
Nancy Magdy Hanna
Keyword(s):  
Multivariate Analysis ◽  
Least Squares ◽  
Simultaneous Determination ◽  
Partial Least Squares ◽  
Principal Component Regression ◽  
Principal Component ◽  
Dual Wavelength ◽  
Ich Guidelines ◽  
The Difference

Simple, accurate, and eco-friendly spectrophotometric procedures were proposed and implemented for simultaneous determination of anticoccidial drugs from three different classes namely, amprolium hydrochloride (AMP), sulfaquinoxaline sodium (SQX) and diaveridine hydrochloride (DVD). Dual wavelength in ratio spectra procedure was proposed where the difference in amplitudes (ΔP) in the ratio spectra at 264 nm and 301.9 nm (ΔP264&301.9 nm) corresponded to AMP with mean percentage recovery 100.00±0.923%, while (ΔP250.9&279 nm) and (ΔP218&243.5 nm) corresponded to SQX and DVD with mean percentage recoveries 99.31±1.083 and 100.64±1.219%, respectively. The dual wavelength in ratio spectra procedure was validated according to the ICH guidelines and accuracy, precision and repeatability were found to be within the acceptable limit. Multivariate chemometric approaches, namely, partial least-squares (PLS-2) and principal component regression (PCR) were also proposed with mean percentage recoveries 99.31±0.769, 98.91±1.192 and 99.04±1.245% for AMP, SQX and DVD, respectively, in PLS-2 and 99.63±1.005, 99.11±1.272 and 98.93±1.338% for AMP, SQX and DVD, respectively, in PCR. These procedures were successfully applied to the multi-ingredient veterinary formulation with mean percentage recoveries 100.75±1.238, 99.29±0.875 and 99.34±0.745% for AMP, SQX and DVD, respectively, in dual wavelength in ratio spectra procedure and 101.03±1.261, 101.48±0.984 and 101.10±1.339% for AMP, SQX and DVD, respectively, in PLS-2 and 100.22±1.204, 101.10±0.546 and 100.91±0.677% for AMP, SQX and DVD, respectively, in PCR.

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 Biodegradable and Compostable Shopping Bags under Investigation by FTIR Spectroscopy

2021 ◽  
Vol 11 (2) ◽  
pp. 621
Author(s):  
Silvana Alfei ◽  
Anna Maria Schito ◽  
Guendalina Zuccari
Keyword(s):  
Principal Component Analysis ◽  
Ftir Spectroscopy ◽  
Principal Component ◽  
Poly Lactic Acid ◽  
Chemometric Methods ◽  
Industrial Sectors ◽  
Fresh Food ◽  
Extruded Films ◽  
Productive Process ◽  
Non Destructive

In the recent years, plastic-based shopping bags have become irregular and progressively replaced by compostable ones. To be marketed, these “new plastics” must possess suitable requirements verified by specific bodies, which grant the conformity mark, and the approved physicochemical properties are periodically verified. The fast, inexpensive, non-destructive, easy to use, and reproducible Fourier-Transform infrared (FTIR) spectroscopy is a technique routinely applied to perform analysis in various industrial sectors. To get reliable information from spectral data, chemometric methods, such as Principal Component Analysis (PCA), are commonly suggested. In this context, PCA was herein performed on 4, 5, and 21 × 3251 matrices, collecting the FTIR data from regular and irregular shopping bags, including three freshly extruded films from the Italian industry MecPlast, to predict their compliance with legislation. The results allowed us to unequivocally achieve such information and to classify the bags as suitable for containing fresh food in bulk or only for transport. A self-validated linear model was developed capable to estimate, by acquiring a single FTIR spectrum if, after the productive process, the content of renewable poly-lactic-acid (PLA) in a new produced film respect the expectations. Surprisingly, our findings established that among the grocery bags available on the market, irregular plastic-based shopping bags continue to survive.

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.

Cox Survival Analysis of Microarray Gene Expression Data Using Correlation Principal Component Regression

2007 ◽  
Vol 6 (1) ◽  
Author(s):  
Qiang Zhao ◽  
Jianguo Sun
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Principal Component Regression ◽  
Predictive Ability ◽  
Principal Component ◽  
Microarray Gene Expression Data ◽  
Expression Data ◽  
Microarray Gene Expression ◽  
New Approach ◽  
Microarray Gene

Statistical analysis of microarray gene expression data has recently attracted a great deal of attention. One problem of interest is to relate genes to survival outcomes of patients with the purpose of building regression models for the prediction of future patients' survival based on their gene expression data. For this, several authors have discussed the use of the proportional hazards or Cox model after reducing the dimension of the gene expression data. This paper presents a new approach to conduct the Cox survival analysis of microarray gene expression data with the focus on models' predictive ability. The method modifies the correlation principal component regression (Sun, 1995) to handle the censoring problem of survival data. The results based on simulated data and a set of publicly available data on diffuse large B-cell lymphoma show that the proposed method works well in terms of models' robustness and predictive ability in comparison with some existing partial least squares approaches. Also, the new approach is simpler and easy to implement.

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