Discrimination of Euterpe Oleracea Mart. (Açaí) and Euterpe Edulis Mart. (Juçara) Intact Fruit Using Near‐Infrared (NIR) Spectroscopy and Linear Discriminant Analysis

As the verification of authenticity of agricultural foods has become a potential application of spectroscopic methods, this study aimed to use near-infrared (NIR) spectroscopy associated with linear discriminant analysis (LDA) to discriminate intact fruit of the species Euterpe oleracea Mart. (acai) and Euterpe edulis Mart. (jucara). One hundred sixty-eight acai fruits from 17 genotypes and 200 fruits from 20 jucara genotypes were investigated and two groups were used for discriminating the species: calibration (294 fruits) and prediction (74 fruits). L-star, a(star), b(star)-PCA, and NIR-PCA of spectra pretreated with multiplicative scatter correction (MSC) showed the best results. The L-star, a(star), b(star)-LDA model resulted in 96.3% correct classification and 93.2% prediction accuracy of the external validation group. NIR spectra pretreated with MSC had 98% correct classification and 97.3% prediction accuracy. NIR spectroscopy associated with LDA is a reliable method for the discrimination of intact acai and jucara fruit.