The start-to-end chemometric image processing of 2D thin-layer videoscans

Komsta, Łukasz; Cieśla, Łukasz; Bogucka‐Kocka, Anna; Józefczyk, Aleksandra; Kryszeń, Jakub; Waksmundzka‐Hajnos, Monika

doi:10.1016/j.chroma.2010.12.004

Cited by 39 publications

(19 citation statements)

References 27 publications

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“…They are usually displayed as a threedimensional plot in which the x-and y-coordinates define the spot position and the z direction the absorbance or fluorescence intensity. Background subtraction, normalization, denoising and thresholding are common data transformation processes [76,80]. For background subtraction, the accumulated images of a blank plate are subtracted from the analytical plate on a pixel-by-pixel basis [81].…”

Section: Charged-coupled Devicesmentioning

confidence: 99%

Instrument platforms for thin-layer chromatography

Bernard-Savary¹,

Poole

2015

Journal of Chromatography A

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Section: Charged-coupled Devicesmentioning

confidence: 99%

Instrument platforms for thin-layer chromatography

Bernard-Savary¹,

Poole

2015

Journal of Chromatography A

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“…To align HPTLC fingerprint images, an image-warp procedure can be used. As an example, an algorithm of an image-warp procedure, which was applied by Komsta et al (2011), was described by Arganda-Carreras et al (2006). Besides these aligning techniques, other preprocessing methods often applied for this type of fingerprints are BC, CC, normalization, SNV, and so on.…”

Section: Data Pretreatmentmentioning

confidence: 99%

Multivariate Data Analysis of Plants

Dejaegher

2014

Encyclopedia of Analytical Chemistry

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When developing fingerprints of herbal samples, three steps should be considered, that is, the development, the validation, and the extraction of information from the multivariate fingerprint data. After an introduction concerning the tendency to shifting toward using fingerprints to evaluate herbal samples in various contexts and a brief description of the three steps when developing fingerprints, the major part of this chapter focuses on the multivariate data analysis of herbal fingerprints. This chapter also deals with the preprocessing of the multivariate data, and unsupervised and supervised data analysis techniques are described in short Finally, some case studies are presented, in which multivariate data analysis methods were applied to extract information on herbal samples from various types of fingerprints, such as spectroscopic, mass spectrometric, chromatographic fingerprints, and fingerprints developed using electrodriven techniques. Depending on the goal of the study, different multivariate data analysis methods were used.

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“…Special modes of chromatogram development have been well described in the literature [38,39] with examples of their application for fingerprint construction [40,41]. Supervised and unsupervised chemometric analysis of two-dimensional images has also been recently described that turned out to be beneficial for recognizing the differences between closely related plant species [42]. Apart from chemometric pretreatment, a concept of an average fingerprint construction by means of freely available program ImageJ (Wayne Rasband, Natonal Institutes of Health, USA; http://rsbweb.nih.gov/ij/) has also been proposed [43].…”

Section: Perspectives Of Bfa Developmentmentioning

confidence: 99%

Biological Fingerprinting of Herbal Samples by Means of Liquid Chromatography

Cieśla

2012

Chromatography Research International

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Biological chromatographic fingerprinting is a relatively new concept in the quality control of herbal samples. Originally it has been developed with the application of HPLC, and recently herbal samples' biological profiles have been obtained by means of thin-layer chromatography (TLC). This paper summarizes the application of liquid chromatographic techniques for the purpose of biological fingerprint analysis (BFA) of complex herbal samples. In case of biological TLC fingerprint, which is a relatively novel solution, perspectives of its further development are outlined in more detail. Apart from already published data, some novel results are also shown and briefly discussed. The paper aims at drawing scientists' attention to the unique solutions offered by biological fingerprint construction.

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The start-to-end chemometric image processing of 2D thin-layer videoscans

Cited by 39 publications

References 27 publications

Instrument platforms for thin-layer chromatography

Instrument platforms for thin-layer chromatography

Multivariate Data Analysis of Plants

Biological Fingerprinting of Herbal Samples by Means of Liquid Chromatography

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