Application of the correlation constrained multivariate curve resolution alternating least-squares method for analyte quantitation in the presence of unexpected interferences using first-order instrumental data

The Analyst ◽  
2010 ◽  
Vol 135 (3) ◽  
pp. 636 ◽  
Author(s):  
Héctor C. Goicoechea ◽  
Alejandro C. Olivieri ◽  
Romà Tauler
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Instrumental Data ◽  
Curve Resolution ◽  
First Order

scholarly journals Application of multivariate curve resolution-alternating least squares (MCR-ALS) for resolving pyrogallol autoxidation in weakly alkaline aqueous solutions

2012 ◽  
Vol 10 (6) ◽  
pp. 1942-1948 ◽  
Author(s):  
Aleksandar Veselinović ◽  
Ružica Nikolić ◽  
Goran Nikolić
Keyword(s):  
Aqueous Solutions ◽  
Least Squares ◽  
Reaction Model ◽  
Spectrophotometric Analysis ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Weakly Alkaline ◽  
Curve Resolution ◽  
First Order ◽  
Concentration Changes

AbstractMultivariate curve resolution — alternating least squares (MCR-ALS) has been applied to data collected from UV/Vis spectrophotometric analysis of the autoxidation process of pyrogallol in weakly alkaline aqueous solutions. The MCR-ALS analysis was able to explain the autoxidation kinetics of pyrogallol at pH 7.4 and 8.0, allowing deduction of the pure spectra and concentration changes of different species present throughout the entire process. The autoxidation process at pH 7.4 was found to follow a first-order reaction model, with formation of purpurogallin as the sole and terminal product. Changing the pH to 8.0 not only accelerated autoxidation of pyrogallol to purpurogallin but also introduced a further autoxidation of purpurogallin. At pH 8.0 the process fits a model of two consecutive first-order reactions. The first step is formation of purpurogallin, which reacts in a further autoxidation to form a yellow colored substance, most probably purpurogallin polymer.

scholarly journals Quantitative analysis and resolution of pharmaceuticals in the environment using multivariate curve resolution-alternating least squares (MCR-ALS)

2019 ◽  
Vol 69 (2) ◽  
pp. 217-231 ◽  
Author(s):  
Ahmed Mostafa ◽  
Heba Shaaban
Keyword(s):  
Least Squares ◽  
Water Samples ◽  
Alternating Least Squares ◽  
Multivariate Curve Resolution ◽  
Least Squares Regression ◽  
Environmental Matrices ◽  
Curve Resolution ◽  
Real Water Samples ◽  
Target Analytes ◽  
Spectrophotometric Data

Abstract The study presents the application of multivariate curve resolution alternating least squares (MCR-ALS) with a correlation constraint for simultaneous resolution and quantification of ketoprofen, naproxen, paracetamol and caffeine as target analytes and triclosan as an interfering component in different water samples using UV-Vis spectrophotometric data. A multivariate regression model using the partial least squares regression (PLSR) algorithm was developed and calculated. The MCR-ALS results were compared with the PLSR obtained results. Both models were validated on external sample sets and were applied to the analysis of real water samples. Both models showed comparable and satisfactory results with the relative error of prediction of real water samples in the range of 1.70–9.75 % and 1.64–9.43 % for MCR-ALS and PLSR, resp. The obtained results show the potential of MCR-ALS with correlation constraint to be applied for the determination of different pharmaceuticals in complex environmental matrices.

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