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Differentiation of Lupinus and Mimosa by Machine Learning Employing Spectroscopic Data: A Comparative Study
Mariana Koetz1, Maria H Vendruscolo1, Andressa K Maia1
1Faculty of Pharmacy, Center for the Study of Natural Products, Federal University of Rio Grande do Sul, Porto Alegre, RS 90610-000, Brazil.
ACS Omega
|May 11, 2026
Summary
This study used spectroscopy and machine learning to differentiate plant species from the Lupinus and Mimosa genera. The combined methods achieved 100% accuracy in classifying these Fabaceae family members.
Area of Science:
- Plant chemistry
- Spectroscopy
- Machine learning
- Taxonomy
Background:
- The Fabaceae family, including genera like Lupinus and Mimosa, exhibits complex chemical profiles.
- Accurate species differentiation is crucial for plant taxonomy and understanding chemical diversity.
- Traditional methods may face challenges with high-dimensional and collinear spectral data.
Purpose of the Study:
- To investigate the chemical composition of Lupinus and Mimosa species from southern Brazil.
- To develop a robust method for accurately distinguishing between these genera using spectroscopic data.
- To explore the application of machine learning in plant species identification.
Main Methods:
- Utilized ultraviolet-visible (UV-vis) and Fourier transform infrared (FTIR) spectroscopy.
- Employed machine learning techniques, including linear discriminant analysis (LDA).
- Integrated variable selection algorithms such as successive projection algorithm (SPA) and genetic algorithm (GA) to handle spectral data challenges.
Main Results:
- Spectroscopic data combined with machine learning successfully distinguished between Lupinus and Mimosa species.
- Identified specific spectral markers crucial for accurate classification.
- Achieved 100% sensitivity, specificity, and accuracy in sample classification.
Conclusions:
- Accessible spectroscopic techniques coupled with machine learning offer a powerful tool for plant taxonomy.
- This approach provides a robust preliminary alternative for species differentiation.
- Enhanced understanding of chemical diversity within the Fabaceae family is achieved.
