Version 1
: Received: 13 September 2018 / Approved: 13 September 2018 / Online: 13 September 2018 (12:06:44 CEST)
How to cite:
Guié Théodore, T. B.; Sié, O.; Nango Jérôme, A.; Alain, C. Acquisition of Images and Parameter Calculations for the Automatic Identification of Molecules in a Thin-film Extract Combined with Laser. Preprints2018, 2018090238. https://doi.org/10.20944/preprints201809.0238.v1
Guié Théodore, T. B.; Sié, O.; Nango Jérôme, A.; Alain, C. Acquisition of Images and Parameter Calculations for the Automatic Identification of Molecules in a Thin-film Extract Combined with Laser. Preprints 2018, 2018090238. https://doi.org/10.20944/preprints201809.0238.v1
Guié Théodore, T. B.; Sié, O.; Nango Jérôme, A.; Alain, C. Acquisition of Images and Parameter Calculations for the Automatic Identification of Molecules in a Thin-film Extract Combined with Laser. Preprints2018, 2018090238. https://doi.org/10.20944/preprints201809.0238.v1
APA Style
Guié Théodore, T. B., Sié, O., Nango Jérôme, A., & Alain, C. (2018). Acquisition of Images and Parameter Calculations for the Automatic Identification of Molecules in a Thin-film Extract Combined with Laser. Preprints. https://doi.org/10.20944/preprints201809.0238.v1
Chicago/Turabian Style
Guié Théodore, T. B., Alico Nango Jérôme and Clement Alain. 2018 "Acquisition of Images and Parameter Calculations for the Automatic Identification of Molecules in a Thin-film Extract Combined with Laser" Preprints. https://doi.org/10.20944/preprints201809.0238.v1
Abstract
This paper presents the automation of the thin-layer chromatography technique whose separation and identification of molecules present in a mixture are currently done manually and laboriously [1]. We have therefore found an interest in automating this technique. In this part, the method implemented comprises 2 steps. First we proceeded to the segmentation of the spots obtained on the chromatographic plate. We then developed a program to identify families of molecules such as coumarins, terpenes, tannins, flavonoids, polyphenols, etc. by calculating segmentation parameters such as standard deviation, entropy, average pixel intensity from an algorithm on the matlab software. Finally our results have been compared to the results obtained by the traditional identification technique in laboratories. Some similarity between the two results obtained shows the reliability and the robustness of our technique.
Keywords
Automation; chromatography; thin film; identification; segmentation; standard deviation; entropy; average intensity; algorithm; matlab.
Subject
Engineering, Automotive Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.