Picchi Monica, Domizio Paola, Wilson Matt, Santos Josè, Orrin Frederick, Zanoni Bruno, Canuti Valentina
DAGRI-Department of Agriculture, Food, Environment and Forestry, University of Florence, Via Donizetti, 6, 50144 Firenze, Italy.
Enartis, 7795 Bell Road, Windsor, CA 95492, USA.
Foods. 2023 May 30;12(11):2191. doi: 10.3390/foods12112191.
Cider is a fermented drink obtained from apple juice. As a function of the used apple cultivar, cider can be classified in four different categories (dry, semi-dry, semi-sweet, sweet), distinguished by the attribute of "dryness," which reflects the sweetness and softness perceived. The dryness level is defined by scales (IRF, NYCA scales) based on the residual sugar, titratable acidity and tannin contents. Despite some adjustments, these scales show limitations in the prediction of actual perceived dryness, as they cannot consider the complicated interrelation between combined chemical compounds and sensory perception. After defining the perceived sensory dryness and its sensory description by using the quantitative descriptive analysis (QDA) method, a multivariate approach (PLS) was applied to define a predictive model for the dryness and to identify the chemical compounds with which it was correlated. Three models were developed, based on three different sets of chemical parameters, to provide a method that is easily applicable in the ordinary production process of cider. The comparison between the predicted rating and the relative scales scores showed that the models were able to predict the dryness rating in a more effective way. The multivariate approach was found to be the most suitable to study the relation between chemical and sensory data.
苹果酒是一种由苹果汁发酵而成的饮品。根据所使用的苹果品种，苹果酒可分为四类（干型、半干型、半甜型、甜型），以“干度”属性区分，该属性反映了所感知到的甜度和柔和度。干度水平由基于残糖、可滴定酸度和单宁含量的量表（IRF量表、纽约州农业试验站量表）来定义。尽管进行了一些调整，但这些量表在预测实际感知到的干度方面存在局限性，因为它们无法考虑复合化合物与感官感知之间复杂的相互关系。在使用定量描述分析（QDA）方法定义了感知到的感官干度及其感官描述之后，采用多元方法（偏最小二乘法）来定义干度的预测模型，并识别与之相关的化合物。基于三组不同的化学参数开发了三个模型，以提供一种易于应用于苹果酒普通生产过程的方法。预测评分与相对量表分数之间的比较表明，这些模型能够更有效地预测干度评分。结果发现多元方法最适合研究化学数据与感官数据之间的关系。
