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Abstract
This pilot study investigates the use of Raman spectroscopy combined with Machine Learning algorithms to differentiate fruit distillates based on trademark, geographical, and botanical origin. Two spectral Raman ranges (200-600 cm⁻¹ and 1200-1400 cm⁻¹) showed the highest discrimination potential. The approach achieved 95.5% accuracy for trademark differentiation and 90.9% for geographical discrimination within the Transylvania region.
Publisher
Scientific Reports
Published On
Dec 03, 2020
Authors
Camelia Berghian-Grosan, Dana Alina Magdas
Tags
Raman spectroscopy
Machine Learning
fruit distillates
trademark differentiation
geographical classification
Transylvania
botanical origin

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