Carotenoid Profile Determination of Bee Pollen by Advanced Digital Image Analysis

Abstract

Bee pollen is a natural matrix widely studied in its nutritional and bioactive compounds, including carotenoids. That composition is usually identified by Rapid Resolution Liquid Chromatography (RRLC) coupled to UV–Vis spectrophotometry, an expensive method that requires complex sample preparation and long analysis time. In this work, a correlation between colorimetric coordinates and carotenoid composition was evaluated. Through Digital Image Analysis (DIA) by DigiEye, the color characteristics were determined, and carotenoids profile was done by RRLC. The correlations were made by multiple linear regression (MLR). From 12 carotenoids found in the samples, six had a coefficient R2 > 0.75 between reference and predict value. Heterogeneous mixtures of bee pollen samples were analyzed, and the suitability of the mathematical models could be corroborated because the relative error for most of the compounds was less than 20%. It has been demonstrated that union of Tristimulus Colorimetry and Image Analysis represent an effective tool to estimate the chemical composition in food industry.