Advanced classification of Brazilian stingless bee honey by genus using comprehensive analytical techniques and chemometrics

This study aimed to investigate Brazilian stingless bee honey (SBH) to compare their chemical compositions. Fifty-five samples from the genera Melipona, Scaptotrigona, Frieseomelitta, Tetragona, and Tetragonisca, collected from five regions were evaluated by melissopalynological and physicochemical analysis, phenolic compounds, sugar profiling, and FTIR-ATR. Multiblock Analysis (MA) was employed to discriminate and assess the influence of entomological (bee genus) and geographical origins on the honey's characteristics. Subsequently, Linear Discriminant Analysis (LDA) and Partial Least Squares Discriminant Analysis (PLS-DA) were employed to classify the samples based on quantitative data and FTIR-ATR spectra, respectively. The primary factor influencing the chemical profile of Brazilian SBH was entomological origin. MA partially separated samples, while LDA and PLS-DA effectively predicted Melipona, Scaptotrigona, and Tetragonisca samples. Key parameters for separation using MA included sugar profile, phenolic compounds, and FTIR-ATR regions (1800–750 cm⁻¹). In the LDA model, electrical conductivity, pH, color (a*), raffinose content, reducing sugars, and trehalulose + maltose were key for classification. For PLS-DA, spectral regions 1610–1557 cm⁻¹ , 1126–960 cm⁻¹ , and 1170–915 cm⁻¹ were critical for distinguishing samples. This study enhances the understanding of how entomological and geographic factors influence Brazilian SBH characteristics and supports its traceability for quality and authenticity.

Keywords

Multivariate analysis Honey discrimination Multiblock analysis Sugar profile FTIR-ATR

URI

http://hdl.handle.net/10400.11/9260

Citation

RESSUTTE, Jéssica B. [et al.] (2025) - Advanced classification of Brazilian stingless bee honey by genus using comprehensive analytical techniques and chemometrics. Journal of Food Composition and Analysis. 139, p. 107138. DOI: 10.1016/j.jfca.2024.107138