Carabetta Sonia, Di Sanzo Rosa, Andronaco Pietro, Canino Francesco, Branyik Tomas, Salafia Fabio, Fuda Salvatore, Muscolo Adele, Russo Mariateresa
Food Chemistry, Safety and Sensoromic Laboratory (FoCuSS Lab), Department of Agriculture, Mediterranean University of Reggio Calabria, Via dell'Università, 25, 89124 Reggio Calabria, Italy.
Laboratory of Pedology and Soil Ecology, Department of Agriculture, Mediterranean University of Reggio Calabria, Via dell'Università, 25, 89124 Reggio Calabria, Italy.
Foods. 2024 Apr 10;13(8):1149. doi: 10.3390/foods13081149.
In this study, a UHPLC-PDA method for the simultaneous identification of polyphenols and bitter acids (alpha, beta, and isoalpha) in beer was developed. The resulting chemical profiles were leveraged to distinguish the characteristics of four (IPA, Lager, Blanche, ALE) bergamot-flavored beers, produced on a pilot-scale plant. In a streamlined 29 min analysis, thirty polyphenols and fourteen bitter acids were successfully identified under optimized separation conditions. Validation, encompassing parameters such as LOD (from 0.028 ppm for isorhamnetin to 0.106 for narirutin), LOQ (from 0.077 ppm for naringenin to 0.355 for narirutin), R (always more than 0.9992), repeatability (from 0.67% for tangeretin to 6.38% for myricetin), and reproducibility (from 0.99% for sinensetin to 6% for naringin), was conducted for polyphenol quantification using constructed calibration curves with seven levels. Exploring polyphenolic components as potential discriminators among different beer styles, a total of thirty-two polyphenolic compounds were identified and quantified, including characteristic bergamot peel polyphenols like neoeriocitrin (from 7.85 ppm for CBS2 to 11.95 ppm in CBS1); naringin (from 4.56 ppm for CBS4 to 10.96 in CBS1), and neohesperidin (from 5.93 in CBS3 to 15.95 for CBS2). The multivariate analysis provided additional insights into variations among specific beer styles, revealing discrepancies in the presence or relative concentrations of specific compounds linked to brewing ingredients and processes. This research enhances the fingerprinting of the chemistry governing beer quality through a straightforward and cost-effective analytical approach.
在本研究中,开发了一种超高效液相色谱 - 光电二极管阵列(UHPLC - PDA)法,用于同时鉴定啤酒中的多酚和苦味酸(α、β和异α)。利用所得化学图谱来区分在中试规模工厂生产的四种(印度淡色艾尔啤酒、拉格啤酒、白啤酒、爱尔啤酒)佛手柑风味啤酒的特征。在简化的29分钟分析中,在优化的分离条件下成功鉴定出30种多酚和14种苦味酸。进行了验证,包括检测限(异鼠李素为0.028 ppm至柚皮芸香苷为0.106 ppm)、定量限(柚皮素为0.077 ppm至柚皮芸香苷为0.355 ppm)、R(始终大于0.9992)、重复性(橘红素为0.67%至杨梅素为6.38%)以及重现性(川陈皮素为0.99%至柚皮苷为6%),使用具有七个水平的构建校准曲线对多酚进行定量。探索多酚成分作为不同啤酒风格之间的潜在鉴别指标,共鉴定并定量了32种多酚化合物,包括特征性佛手柑皮多酚,如新橙皮苷(CBS2中为7.85 ppm至CBS1中为11.95 ppm);柚皮苷(CBS4中为4.56 ppm至CBS1中为10.96 ppm),以及新橙皮苷(CBS3中为5.93至CBS2中为15.95)。多变量分析为特定啤酒风格之间的差异提供了更多见解,揭示了与酿造原料和工艺相关的特定化合物的存在或相对浓度的差异。本研究通过一种直接且经济高效的分析方法,增强了对控制啤酒质量的化学特征的指纹识别。