Utilização de espectroscopia de infravermelho médio e modelos quimiométricos para discriminação de variedades de cacau seco

Abstract

ABSTRACT Generally, the taxonomic classification of cocoa beans is based on the theobromine/caffeine ratio determined using high-performance liquid chromatography (HPLC). However, this technique involves laborious and time-consuming calculations. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy is a valuable, effective, and rapid tool for analyzing the chemical composition of food products. The objective of this study was to examine the potential of ATR-FTIR combined with chemometric tools such as principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares regression-discriminant analysis (PLS-DA) to discriminate between the Trinitario and Forastero dry bean cocoa varieties defined by theobromine and caffeine measurements via HPLC. The cocoa varieties were evaluated using HPLC analysis of 36 dry cocoa bean samples to determine the theobromine/caffeine ratio. Moreover, ATR-FTIR spectra were analyzed in the mid-infrared (MIR) region, and signals associated with theobromine and caffeine were identified and analyzed using the LDA and PLS-DA models. The LDA and PLS-DA models allowed the satisfactory differentiation between cocoa varieties, providing overall prediction capacity values of 98.2 ± 1.8% and 96.1 ± 2.4%, respectively. The results show the potential of ATR-FTIR spectroscopy for the reliable, fast, and easy differentiation of dried cocoa beans.