Version 1
: Received: 14 August 2024 / Approved: 14 August 2024 / Online: 15 August 2024 (08:51:53 CEST)
How to cite:
Kucharska-Ambrożej, K.; Karpińska, J.; Ratkiewicz, A. Performance of the Multi-Class Classification Tools for Small Samples of Lamiaceae Family Herb Species. Preprints2024, 2024081114. https://doi.org/10.20944/preprints202408.1114.v1
Kucharska-Ambrożej, K.; Karpińska, J.; Ratkiewicz, A. Performance of the Multi-Class Classification Tools for Small Samples of Lamiaceae Family Herb Species. Preprints 2024, 2024081114. https://doi.org/10.20944/preprints202408.1114.v1
Kucharska-Ambrożej, K.; Karpińska, J.; Ratkiewicz, A. Performance of the Multi-Class Classification Tools for Small Samples of Lamiaceae Family Herb Species. Preprints2024, 2024081114. https://doi.org/10.20944/preprints202408.1114.v1
APA Style
Kucharska-Ambrożej, K., Karpińska, J., & Ratkiewicz, A. (2024). Performance of the Multi-Class Classification Tools for Small Samples of Lamiaceae Family Herb Species. Preprints. https://doi.org/10.20944/preprints202408.1114.v1
Chicago/Turabian Style
Kucharska-Ambrożej, K., Joanna Karpińska and Artur Ratkiewicz. 2024 "Performance of the Multi-Class Classification Tools for Small Samples of Lamiaceae Family Herb Species" Preprints. https://doi.org/10.20944/preprints202408.1114.v1
Abstract
The primary objective of this study was to identify a rapid and noninvasive methodology for effectively differentiating various herbal species cultivated in Eastern Poland. Typically, a plant's chemical profile is obtained using chromatographic methods; however, spectroscopic methods can serve as a complementary or independent tool for determining similarities in the analyzed samples. The investigation centered on leaves of plant species from the Lamiaceae family, encompassing basil, lavender, oregano, sage, and thyme. UV-VIS and ATR-FTIR spectra of dried plant samples' powder were recorded and subsequently analyzed using chemometric tools. This paper assesses the relative performance of different discrimination methods, including both traditional methods based on machine learning and those dealing with specimens associated with a specific category. Among the methodologies tested, SIMCA showed the best performance, particularly effective for small training sets.
Keywords
Keywords: UV-Vis, ATR-FTIR, multiclass discriminative analysis, class oriented methods, SIMCA
Subject
Chemistry and Materials Science, Analytical Chemistry
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.
