Quality evaluation of intact açaí and juçara fruit by means of near infrared spectroscopy

Abstract

ABSTRACT The objective of this study was to report the robustness of partial least squares regression (PLSR) models developed using FT-NIR reflectance spectra obtained from intact acai and jucara fruit. Mature fruit were collected over two years (6 populations of acai and jucara, totalling 505 samples). Diffuse reflectance spectra were acquired (64 scans and spectral resolution of 8 cm −1 ) using ∼25 fruits per batch on a 90 mm diameter glass dish in a single layer. Spectra were subject to several pre-processing procedures and two variable selection methods to develop the PLSR models. For total anthocyanin content (TAC) in acai, a PLSR model developed using the wavelength range of 1606–1793 nm, standard normal variate (SNV) and second derivative of Savitzky–Golay (SNV + d 2 A ) achieved a bias corrected root mean square error (SEP) of 3.6 g kg −1 and a R 2 p of 0.7 in predicting an external independent set, which was better than PLSR models for jucara (SEP of 3.7 g kg −1 , R 2 p of 0.5), and for both species combined (SEP of 5.7 g kg −1 , R 2 p of 0.5). For soluble solids content (SSC) in acai the models developed using SNV + d 2 A spectra over the window of 1640–1738 nm achieved a bias-corrected SEP of 2.9% and R 2 p of 0.8, similar to jucara (SEP of 1.1%, R 2 p of 0.9) and for both species combined (SEP of 2.3%, R 2 p of 0.8). The developed models can be used to sort acai and jucara based on SSC and TAC into two grades (low and high contents).