Prediction of bioactive compounds in barley by near-infrared reflectance spectroscopy (NIRS)

Abstract

Barley grains contain a variable amount of biologically active compounds such as non-starch polysaccharides and phenol compounds. These compounds are important in nutrition due to their significant health benefits and technological role in food. We developed predictive models for β-glucans (BG), arabinoxylans (AX), bound phenols (BP), free phenols (FP), and anthocyanins (AN) based on near-infrared spectroscopy (NIRS) using two different NIRS instruments with different spectral range and spectral steps. Regressions of modified partial least squares (MPLS) and several combinations of scattering correction and derivative treatments were tested. The optimal calibration models generated high coefficients of determination for BG and BP, but not for AN content. The instrument with the highest resolution only gave better results for BG prediction models, and the addition of the visible range did not prove to be ostensibly advantageous to the determination of any of the active compounds of study, not even in the case of AN analysis.