Use of continuous wavelet transform approach for simultaneous quantitative determination of multicomponent mixture by UV–Vis spectrophotometry

Sohrabi, Mahmoud Reza; Mirzabeygi, Vahid; Davallo, Mehran

doi:10.1016/j.saa.2018.05.020

Cited by 21 publications

(7 citation statements)

References 21 publications

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“…Another system that is performed for the measurement of molecular weights also uses wavelet transform. In the work done by [5], three wavelet transforms are implemented: Daubechies level 8 with decomposition 15 (DB8-15), biorthogonal level 4.4 with decomposition 7 (BIOR4.4-7), and biorthogonal 3.3 with decomposition 4 (BIOR3. [3][4].…”

Section: State Of Art In Electrophoresis and Image Retrievalmentioning

confidence: 99%

“…It is also shown that four works focus on the application of intelligent paradigms in image diagnosis or analysis. However, only two of them [4][5][6] are dedicated to the improvement of images and the measurement of molecular weights by means of intelligent techniques such as the use of the wavelet transform, but they do not perform a recovery based on visual information, as in the proposal of this research. More specifically, from the three strongest related works we can say specifically that:…”

Section: State Of Art In Electrophoresis and Image Retrievalmentioning

confidence: 99%

“…2. In the case of Reza and Shorabi of 2018 [5], a molecular weight detection with 95% accuracy is performed using also wavelet transform but with different families or levels. 3.…”

Section: State Of Art In Electrophoresis and Image Retrievalmentioning

confidence: 99%

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Smart Classification Paradigms for Protein Samples from 1-D Electrophoresis Gel

et al. 2020

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Electrophoresis allows us to identify the types of proteins present in food, DNA, tissues and more. With the help of the molecular marker their weight is known, these markers are applied within the one-dimensional gel, and their protein value is known by means of marks. In this research, the molecular marker is obtained and the wavelet transform (WT) is obtained, generating approximation coefficients, which were taken to determine a molecular weight using three classification paradigms. The first paradigm is an approach in content-based image retrieval (CBIR) which makes a detection of the molecular weight in electrophoresis samples. The second approach is a neural network, thus two models are employed: self-organization maps (SOM) and back propagation in a supervised and unsupervised way, respectively. The third approach is based in a J48 decision tree. A comparison is made between the three paradigms for molecular weight computation. Neural networks obtained an improvement in the precision compared versus the CBIR-WT. Five parametric statistics were generated from the wavelet approximation coefficients. The CBIR-WT, SOM, back propagation and J48 were decisive for the classification and calculation of the molecular weight of each protein stain in the one-dimensional electrophoresis gel.

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Section: State Of Art In Electrophoresis and Image Retrievalmentioning

confidence: 99%

Section: State Of Art In Electrophoresis and Image Retrievalmentioning

confidence: 99%

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Smart Classification Paradigms for Protein Samples from 1-D Electrophoresis Gel

et al. 2020

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“…In particular, the UV-Vis technique allows quantification through the detection of optical density (OD). The results are generally cost-effective, accurate, reproducible and obtained quickly, making the method popular [24][25][26][27]. This specific technique thus is an attractive alternative to correlate indirectly the cell density of microalgae with the absorption at specific wavelengths in a reliable way [11,28].…”

Section: Introductionmentioning

confidence: 99%

Optical Insight: Spectrophotometry as a Tool to Quantify Cell Density of Green Microalgae in Suspension, with Emphasis on Growing Conditions and Toxicological Evaluations

Pessoa,

Almeida,

Santos

et al. 2024

Preprint

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Microalgae are highly attractive to various industrial sectors and can serve as indicators of aquatic environmental health. An essential step for cultivating microalgae is assessing the cell density, which is traditionally performed through viable cell counting by optical microscopy (OM). However, this method has some limitations, such as the time involved in the process of counting, and the need for specialized training of laboratory personnel. Spectrophotometry is an affordable alternative, especially when applied to culture growth and toxicological tests. We chose the wavelength of 680 nm to detect the optical density (OD) of the green freshwater microalga Desmodesmus subspicatus and green the marine microalga Tetraselmis sp. The correlation between the number of cells and OD was suitable for both microalgae and accuracy was comparable to traditional OM counting. In toxicological tests, the OD technique allowed the monitoring of microalgal growth in the presence of the chemicals potassium dichromate, potassium chloride and sodium dodecyl sulfate (SDS), with results very close to those reported in the scientific literature. This study sheds light on this well-known technique, which is an important contribution since few articles have explored its potentialities and fragilities, showing the successful application to monitoring green microalgal cultures and toxicological assays.

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“…In [5], wavelet transform and zero crossing point technique were used in various studies to obtain its signals. With this, they obtained 95 % confidence since.…”

Section: Introductionmentioning

confidence: 99%

Molecular Marker for Protein Electrophoresis by Wavelet Transform

Flores-López¹,

Flores-Pulido²,

Jaramillo-Quintero³

2019

RCS

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Visual Information retrieval is an area where the analysis and recognition is helpful to generate and obtain data from image samples. In this research the image samples are obtained from analysis of electrophoresis that captures protein profiles in tissues. The electrophoresis provides a sample where the proteins are computed to know their molecular weight. The image digital processing takes electrophoresis images and a wavelet transform is applied to the sample that can be fractioned to emphasize the molecular weights that at first sight are not identified. Therefore, with the wavelet transform, it is possible to compute molecular weights of proteins and know their corresponding weight. Electrophoresis is a technique that is used in various analysis such as DNA, medicine, environment and food. All these profiles have different molecular weights, which are known by a marker that is placed in a lane. In this proposal, the wavelet transform is applied to the images of electrophoresis samples, creating the signal of the protein with the approximation coefficients, that achieves to measure a molecular weight. The approximation coefficients are computed at 3 levels of decomposition with the wavelet transform Daubechies. It is then possible to detect a molecular weight of nearly 300 samples of electrophoresis with an accuracy of 97 % in terms of numerical and visual similarity by means of visual information retrieval evaluated with recall and precision metrics.

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Use of continuous wavelet transform approach for simultaneous quantitative determination of multicomponent mixture by UV–Vis spectrophotometry

Cited by 21 publications

References 21 publications

Smart Classification Paradigms for Protein Samples from 1-D Electrophoresis Gel

Smart Classification Paradigms for Protein Samples from 1-D Electrophoresis Gel

Optical Insight: Spectrophotometry as a Tool to Quantify Cell Density of Green Microalgae in Suspension, with Emphasis on Growing Conditions and Toxicological Evaluations

Molecular Marker for Protein Electrophoresis by Wavelet Transform

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