Grieco Francesco, Fiore Anna, Gerardi Carmela, Tufariello Maria, Romano Giuseppe, Baiano Antonietta
Institute of Sciences of Food Production - National Research Council (CNR-ISPA), Via Prov.le, Lecce-Monteroni, 73100, Lecce, Italy.
Dipartimento di Scienze Agrarie, Alimenti, Risorse Naturali e Ingegneria (DAFNE), University of Foggia, Via Napoli 25, 71122, Foggia, Italy.
Heliyon. 2024 Sep 8;10(18):e37598. doi: 10.1016/j.heliyon.2024.e37598. eCollection 2024 Sep 30.
The choice of the starchy ingredients as well as that of the yeasts strongly can represent a useful tool to differentiate the final beers. Our research investigated twelve white beers obtained applying a 2-factor mixed 3-level/4-level experimental design. The first factor was the cereal mixture, with 3 combinations of barley malt (65 %) and unmalted wheat (35 % of common, durum, or emmer). The second factor was the yeast used to carry out the fermentation trials, i.e.: a starter strain (WB06); an oenological strain (9502); two mixed starters made of an oenological strain (6956) and, alternatively, one of the two strains. Most beer attributes were significantly ( < 0.05) influenced by the two considered factors with the following exceptions: the wheat species did not affect maltotriose, maltose, pH, total and volatile acidity, floral flavour, and sweetness; the yeast did not exert significant effects on foam colour, turbidity, overall olfactory intensity, yeast flavour, and body. The flavour of fruits and aromatic herbs were not influenced by the factors studied. Alcohol content was maximised using the unmalted durum wheat (∼7 %) and WB06 (∼6.8 %). The beer antioxidant content was increased by the use of emmer (566 mg/L) and by the application of the mixed inoculum (478-487 mg/L). The beers made with unmalted common wheat and fermented by the strains alone obtained the best overall sensory score (3.7). As shown by the Principal Component Analysis, the beers were better classified by the type of unmalted wheat than by the fermenting yeast. A multiple regression analysis was performed by fitting the analytical parameters that highlighted significant differences among the beers to a second-order polynomial model. Data concerning colour, glycerol concentration, FC-TPC, and antioxidant activity were satisfactorily predicted (R > 0.8) by the fitted models.
淀粉质原料以及酵母的选择很可能是区分最终啤酒的有用工具。我们的研究采用二因素混合3水平/4水平实验设计,研究了12种白啤酒。第一个因素是谷物混合物,有3种大麦麦芽(65%)与未发芽小麦(普通小麦、硬粒小麦或二粒小麦的35%)的组合。第二个因素是用于进行发酵试验的酵母,即:一种起始菌株(WB06);一种酿酒菌株(9502);两种由酿酒菌株(6956)与另外两种菌株之一混合而成的起始菌株。除以下情况外,大多数啤酒属性受到这两个因素的显著影响(P<0.05):小麦品种不影响麦芽三糖、麦芽糖、pH值、总酸度和挥发酸度、花香和甜度;酵母对泡沫颜色、浊度、整体嗅觉强度、酵母风味和酒体没有显著影响。水果和香草的风味不受所研究因素的影响。使用未发芽硬粒小麦(约7%)和WB06(约6.8%)时酒精含量最高。使用二粒小麦(566毫克/升)和混合接种物(478 - 487毫克/升)可提高啤酒的抗氧化剂含量。用未发芽普通小麦酿造并单独由这些菌株发酵的啤酒获得了最佳总体感官评分(3.7)。主成分分析表明,按未发芽小麦类型比按发酵酵母能更好地对啤酒进行分类。通过将突出啤酒间显著差异的分析参数拟合到二阶多项式模型进行多元回归分析。拟合模型对颜色、甘油浓度、FC - TPC和抗氧化活性的数据预测良好(R>0.8)。