Qualitative and Quantitative HPTLC Analysis

Chromatography

Qualitative and Quantitative HPTLC Analysis

10 Mar, 2015

Published over 11 years ago. See the latest and most current information on Chromatography.

As Camag’s UK distributor, Omicron Research Ltd are proud to offer customers visionCATS 2.0, the newest version of Camag’s next generation HPTLC software.  Whereas the previous release of visionCATS (1.4) was clearly focused on qualitative analysis based on digital images, and unlocked the full potential of the TLC Visualizer, visionCATS 2.0 integrates quantitative analysis using the TLC Scanner.

visionCATS is an easy to use and intuitive software tool for TLC/HPTLC analysis. It can compare samples and references side by side on the same plate. visionCATS 2.0 features a new database design that makes locating relevant samples easy and extremely fast.

With its clearly structured graphic user interface, visionCATS puts the user in complete control of the HPTLC process and guides the user through all steps. visionCATS offers a Method Library for seamless import of validated methods and images of standards and botanical reference materials. Licensed users can download library files and import them into their own database free of charge.

visionCATS uses a client server system offering enormous flexibility to the number of instruments and users that are working together, and enabling access to the same data for all members of a work group. At the heart of the client server architecture is a powerful database, allowing the retrieval of all data associated with each individual sample based on the sample ID, while samples are still analysed in the context of a plate.

The fully integrated image comparison tool enables the viewing of data of multiple samples or detection modes from different analysis side by side, independent of their plate origin. Together with the TLC Visualizer visionCATS supports low noise, high dynamic range images and includes a comprehensive set of image enhancement tools. Sophisticated algorithms ensure best image quality for identification of even the weakest zones. 

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