Identification of some coffee leaf taxa using fluorescence spectroscopy and chemometrics

Abstract

Analytical techniques for identification of coffee taxa are essential for plant breeding and quality control of products. Rapid technique for discrimination of coffee taxa based on the fluorescence signals from their leaf extracts was introduced. Five different coffee taxa: Coffea liberica; Coffea congensis; Coffea arabica var. Geisha, a spontaneous hybrid of C. Arabica and Coffea canephora (Hibrido de timor), a hybrid of Hibrido de timor, and C. arabica var. Cattura; were investigated based on their fluorescence signals. The individual taxa present different fluorescence spectra. The spectra obtained from the excitation wavelengths at 300, 330, 390, 420, and 450 nm; and emission wavelengths in the range of 500–790 nm were selected for principal component analysis (PCA) and partial least squares-discriminant analysis (PLSDA). It was found that fluorescence signals with excitation wavelength at 300 nm had been successfully implemented for rapid clustering and identification of some coffee taxa. The PCA score plot presenting natural clustering of data obtained from the fluorescence spectra tended to agree with the data of chemical contents based on antioxidant activity, total phenolic content, and total flavonoid content. The Q2 and R2 calculated via leave-one-out cross-validation (LOOCV) of model obtained from processing of the PLS-DA were 0.6 and 0.8, respectively. It means that the model has potential for the categorization of coffee taxa based on their leaf extracts without any chemical treatments.