Analysis of bee pollen constituents from different Brazilian regions:Quantification by NIR spectroscopy and PLS regression

Abstract

In the present work partial least square regression (PLS) models were built for quantification of the majorcomponents of 154 Brazilian bee pollen samples. Bee pollen has nutritive and therapeutic properties thatmake it attractive for human health. However, studies on the nutrient and bioactive compoundcomposition of this product are needed, as well as the verification of the presence of contaminants thatare harmful to health. The conventional analysis methods are costly and time-consuming, while nearinfrared spectroscopy (NIR) associated to PLS regression allows a fast and non-costly quantification of thebee pollen components without samples pre-treatment.The calibration models exhibited the determination coefficients,R2>0.94. The mean percent cali-bration error varied from 1.49 to 5.58%. For external validation,R2ranged from 0.89 to 0.98 among thesix. The results indicated that some models are good for quantification, while others are qualified forscreening calibration