Stingless bees, important pollinating insects in the tropics, produce honey whose unique quality features differentiate their origin. The feasibility of multivariate data analysis for quality discrimination of stingless bee honey from different genera (Melipona bicolor, quadrifasciata, marginata and Scaptotrigona bipunctata) by mineral content, physicochemical and microbiological properties were investigated. The principal component analysis explained 72.12% of the total variance of the data, and the separation into two main groups in a scatter plot was observed. Group 2 was formed by Scaptotrigona genus, that showed the highest values of pH, ash, and soluble solids. Potassium was the most abundant mineral followed by calcium and sodium for both groups quantified by inductively coupled plasma optical emission spectrometry. This honey has higher acidity and moisture than Apis mellifera honey. Microbiological analyses showed that total aerobic mesophiles ranged between 2.00 and 4.77 log CFU/g. Salmonella spp. was not detected, while the mould and yeast content was above the maximum allowed under the Apis mellifera honey legislation. The evaluated honey samples presented the lactic acid bacteria, which are considered a benefit. The multivariate statistical analysis was efficient in discriminate stingless bee honey, contributing to approaches that can be used for standardization and regulation.
Keywords: Brazilian honey; Chemometrics; Hierarchical cluster analysis; Melipona; Principal component analysis; Scaptotrigona.
© Association of Food Scientists & Technologists (India) 2019.