De Flaviis Riccardo, Santarelli Veronica, Mutarutwa Delvana, Grilli Sergio, Sacchetti Giampiero
Department of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Via R. Balzarini 1, 64100, Teramo, Italy.
Food Consultant as BeerStudioLab, Via Nazionale per Teramo 75, 64021, Giulianova, Italy.
Curr Res Food Sci. 2022 Dec 29;6:100429. doi: 10.1016/j.crfs.2022.100429. eCollection 2023.
Raw materials are recognized to affect the sensory profile of 'Blanche' craft beers and their 'terroir'. Two common wheat ( L.) were harvested in three experimental fields with different pedo-climatic conditions and altitudes, and then used for beer production. The taste and flavour of wheat beers were analysed by sensory (panel and consumer test) and SPME GC-MS analyses. Panel dataset was processed by multivariate statistical analyses: a principal component analysis (PCA) revealed that formulation was the main source of variation of sensory profile in wheat beers and a generalized Procrustes analysis (GPA) showed how wheat origin affected the sensory profiles of wheat craft beers based on the consensus among panelists. Moreover, a partial least-squares discriminant analysis (PLS-DA) on VOCs permitted to discriminate and characterize beers selected by a panel-driven approach. By comparing panel and VOCs results, it was possible to highlight that higher altitudes of wheat cultivation determine an increase of pleasant notes such as fruity and herbal. A PCA on consumer test data confirmed that formulation was the main factor affecting liking scores and that the preferences were affected by age, involvement and frequency of use. An internal preference map combining panel and consumer data suggested that the majority of preferences are driven by a few key sensory attributes. Differences in liking among the considered beers revealed two main consumer groups.
原材料被认为会影响“布兰奇”精酿啤酒的感官特征及其“风土”。在三个具有不同土壤气候条件和海拔高度的试验田中收获了两种常见的小麦（L.），然后将其用于啤酒生产。通过感官分析（专家小组和消费者测试）以及固相微萃取气相色谱 - 质谱联用（SPME GC - MS）分析对小麦啤酒的口感和风味进行了分析。专家小组数据集通过多元统计分析进行处理：主成分分析（PCA）表明配方是小麦啤酒感官特征变化的主要来源，广义Procrustes分析（GPA）基于专家小组成员之间的共识展示了小麦产地如何影响小麦精酿啤酒的感官特征。此外，对挥发性有机化合物（VOCs）进行的偏最小二乘判别分析（PLS - DA）能够区分并表征通过专家小组驱动方法选择的啤酒。通过比较专家小组和VOCs的结果，可以突出显示小麦种植海拔较高会使诸如水果味和草本味等宜人香气增加。对消费者测试数据进行的PCA证实配方是影响喜好评分的主要因素，并且偏好受年龄、参与度和使用频率的影响。结合专家小组和消费者数据的内部偏好图表明，大多数偏好是由一些关键感官属性驱动的。所考虑啤酒之间的喜好差异揭示了两个主要的消费者群体。
