Marsol-Vall Alexis, Balcells Mercè, Eras Jordi, Canela-Garayoa Ramon
Departament de Química-DBA Center, Universitat de Lleida-Agrotecnio Center, Avda. Alcalde Rovira Roure, 191, E-25198 Lleida, Spain.
Departament de Química-DBA Center, Universitat de Lleida-Agrotecnio Center, Avda. Alcalde Rovira Roure, 191, E-25198 Lleida, Spain.
Food Chem. 2018 Jan 15;239:119-125. doi: 10.1016/j.foodchem.2017.06.070. Epub 2017 Jun 10.
Peach juices of distinct varieties, namely yellow- and red-fleshed, and commercial and freshly blended were analyzed. The method used was based on Stir Bar Sorptive Extraction (SBSE) involving a polydimethylsiloxane-coated stir bar with thermal desorption (TD), followed by gas chromatography coupled to mass spectrometry (GC-MS) analysis. The resulting analytical data included 41 compounds belonging to several chemical classes, such as aldehydes, alcohols, lactones, terpenoids, fatty aldehydes, fatty acids and hydrocarbons. Furthermore, chemometric data treatment using unsupervised analysis (PCA) proved useful to classify peach juices on the basis of variety. Stepwise Linear Discriminant Analysis (SLDA) showed that a reduced number of variables (14 compounds), including lactones (6-pentyl-α-pyrone, γ-decalactone, γ-dodecalactone, and δ-dodecalactone), fatty acids (hexadecanoic acid), fatty aldehydes (tetracosanal and octacosanal), hydrocarbons (C23, C26, C27, C29, and C33), and alcohols (phytol and α-tocopherol), were necessary to classify the juice samples according to variety and processing conditions.
对不同品种的桃汁进行了分析，即黄肉和红肉品种，以及市售桃汁和新鲜混合桃汁。所采用的方法基于搅拌棒吸附萃取（SBSE），使用涂有聚二甲基硅氧烷的搅拌棒并结合热脱附（TD），随后进行气相色谱-质谱联用（GC-MS）分析。所得分析数据包括41种属于多种化学类别的化合物，如醛类、醇类、内酯类、萜类、脂肪醛类、脂肪酸类和烃类。此外，使用无监督分析（PCA）的化学计量学数据处理方法被证明有助于根据品种对桃汁进行分类。逐步线性判别分析（SLDA）表明，包括内酯类（6-戊基-α-吡喃酮、γ-癸内酯、γ-十二内酯和δ-十二内酯）、脂肪酸类（十六烷酸）、脂肪醛类（二十四烷醇和二十八烷醇）、烃类（C23、C26、C27、C29和C33）以及醇类（叶绿醇和α-生育酚）在内的数量减少的变量（14种化合物）对于根据品种和加工条件对果汁样品进行分类是必要的。
