Classification of Brazilian Coffee Using Near-Infrared Spectroscopy and Multivariate Calibration

Abstract

Abstract This work describes the use of near infrared spectroscopy (NIRS) and chemometric techniques calibration for the classification of coffee samples from different lots and producers acquired in supermarkets and roasting industries in some Brazilian cities. Seventy-three samples of finely ground roasted coffee were acquired in the market and 91 samples of roasted ground Arabica beans were analyzed in the full NIR spectral range (800–2500 nm) using a diffuse reflectance accessory coupled to an MB160 Bomem spectrophotometer. Two classification models were constructed: Soft Independent Modeling Class Analogy (SIMCA) and PLS Discriminant Analysis (PLS-DA). All findings reveal that NIR spectroscopy, coupled with either SIMCA or PLS-DA multivariate models, can be a useful tool to differentiate roasted coffee grains and to replace sensory tests. Keywords: CoffeeNIR spectroscopyPLS-DASIMCA Acknowledgments *In memorian. The authors thank CNPq, CAPES/PROCAD, and UFRN/PPGQ. Notes Numbers between parentheses indicate the number of samples used for predicting. Numbers between parentheses indicate the number of samples used for predicting.