Genetic Algorithms-Based Approach for Wavelength Selection in Spectrophotometric Determination of Vitamin B12 in Pharmaceutical Tablets by Partial Least-Squares

Sratthaphut, Lawan; Ruangwises, Nongluck

doi:10.1016/j.proeng.2012.01.1261

Cited by 17 publications

(6 citation statements)

References 11 publications

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“…Specifically, the performance of GAs is absolutely wonderful on mixed (discrete and continuous) combinatorial issues. A number of GA-based applications have been reported in pharmaceutical analysis [16][17][18][19].…”

Section: Ga-pls Methodsmentioning

confidence: 99%

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

et al. 2021

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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.

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Section: Ga-pls Methodsmentioning

confidence: 99%

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

et al. 2021

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“…Due to spectral data characteristics, in which one or several sets of predictors provide the same information, the use of an MC analysis contributes towards eliminating those predictors with redundant contributions to the model [29,30]. Another alternative for the selection of independent variables is Genetic Algorithm (GA) analysis, widely used in chemical spectrometry [21,[31][32][33][34][35][36][37]. GAs are adaptive procedures for finding solutions, or numerical optimizations, and are inspired by the theory of evolution: in a living environment, the "best" individuals have a greater chance of surviving and a higher probability of spreading their genes by reproduction [38].…”

Section: Introductionmentioning

confidence: 99%

Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions

et al. 2019

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To overcome the environmental changes occurring now and predicted for the future, it is essential that fruit breeders develop cultivars with better physiological performance. During the last few decades, high-throughput plant phenotyping and phenomics have been developed primarily in cereal breeding programs. In this study, plant reflectance, at the level of the leaf, was used to assess several physiological traits in five Vaccinium spp. cultivars growing under four controlled conditions (no-stress, water deficit, heat stress, and combined stress). Two modeling methodologies [Multiple Linear Regression (MLR) and Partial Least Squares (PLS)] with or without (W/O) prior wavelength selection (multicollinearity, genetic algorithms, or in combination) were considered. PLS generated better estimates than MLR, although prior wavelength selection improved MLR predictions. When data from the environments were combined, PLS W/O gave the best assessment for most of the traits, while in individual environments, the results varied according to the trait and methodology considered. The highest validation predictions were obtained for chlorophyll a/b (R2Val ≤ 0.87), maximum electron transport rate (R2Val ≤ 0.60), and the irradiance at which the electron transport rate is saturated (R2Val ≤ 0.59). The results of this study, the first to model modulated chlorophyll fluorescence by reflectance, confirming the potential for implementing this tool in blueberry breeding programs, at least for the estimation of a number of important physiological traits. Additionally, the differential effects of the environment on the spectral signature of each cultivar shows this tool could be directly used to assess their tolerance to specific environments.

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“…Various wavelengths are measured with minimal effort measuring per test and yield multivariate information. There are several literatures reporting the improvement of predictive ability when wavelength choosing is accomplished before multivariate calibration [1][2][3] and describing the different strategies of wavelength selection [4][5][6]. In the previous two decades, a standout among fascinating variable selection approaches was self-organizing map (SOM).…”

Section: Introductionmentioning

confidence: 99%

Comparative investigation of two different self-organizing map-based wavelength selection approaches for analysis of binary mixtures with strongly overlapping spectral lines

Sratthaphut¹,

Niratisai²,

Toyama³

2017

Trop. J. Pharm Res

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Genetic Algorithms-Based Approach for Wavelength Selection in Spectrophotometric Determination of Vitamin B12 in Pharmaceutical Tablets by Partial Least-Squares

Cited by 17 publications

References 11 publications

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

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

Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions

Comparative investigation of two different self-organizing map-based wavelength selection approaches for analysis of binary mixtures with strongly overlapping spectral lines

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