Gómez-Caravaca Ana María, Verardo Vito, Berardinelli Annachiara, Marconi Emanuele, Caboni Maria Fiorenza
Department of Analytical Chemistry, University of Granada, c/Fuentenueva s/n, E-18071 Granada, Spain; Research and Development of Functional Food Centre (CIDAF), PTS Granada, Avda. del Conocimiento s/n, Edificio Bioregión, E-18007 Granada, Spain.
Inter-Departmental Centre for Agri-Food Industrial Research (CIRI Agroalimentare), University of Bologna, P.zza Goidanich 60, I-47521 Cesena (FC), Italy.
J Chromatogr A. 2014 Aug 15;1355:134-42. doi: 10.1016/j.chroma.2014.06.007. Epub 2014 Jun 7.
Barley (Hordeum vulgare L.) is a cereal crop that has been cultivated since ancient times. However, its interest as nutritional food and as food ingredient is relatively new. Thus, in this study, the phenolic compounds of eighteen different varieties of barley (4 waxy and 14 non-waxy) grown under the same agronomic conditions in the same experimental field have been determined by HPLC-DAD-MS. Two new methodologies were developed using new generation superficially porous HPLC columns with different stationary phases: C18 and pentafluorophenyl (PFP). Twelve free phenolic compounds and eight bound phenolic compounds could be identified in barley samples in less than 22min. The study of different method parameters showed that C18 column was more suitable for the analysis of phenolic compounds of barley. Hierarchical cluster analysis (HCA) was conducted in order to assess the different ability of the two different core shell HPLC columns in the discrimination between "waxy" and "non-waxy" varieties, and only HCA of C18 column could separate waxy and non-waxy genotypes. Significant differences in the content of phenolic compounds between waxy and non-waxy samples were found, being waxy barley samples the ones which presented higher content of free and bound phenolic compounds. Once the best discriminant HPLC column was established, principal component analysis (PCA) was applied and it was able to discriminate between "waxy" and "non-waxy" varieties; however it discriminated the barley samples based only in free phenolic compounds. Because of that, partial least squares discriminant analysis (PLS-DA) and Artificial Neural Networks (ANN) were carried out. PLS-DA and ANN permitted the classification of waxy and non-waxy genotypes from both free and bound phenolic compounds.
大麦（Hordeum vulgare L.）是一种自古以来就被种植的谷类作物。然而，它作为营养食品和食品成分受到关注相对较新。因此，在本研究中，通过HPLC-DAD-MS测定了在同一试验田相同农艺条件下种植的18个不同品种大麦（4个糯性和14个非糯性）的酚类化合物。使用具有不同固定相的新一代表面多孔HPLC柱开发了两种新方法：C18和五氟苯基（PFP）。在不到22分钟内可在大麦样品中鉴定出12种游离酚类化合物和8种结合酚类化合物。对不同方法参数的研究表明，C18柱更适合分析大麦中的酚类化合物。进行了层次聚类分析（HCA），以评估两种不同核壳HPLC柱在区分“糯性”和“非糯性”品种方面的不同能力，只有C18柱的HCA能够分离糯性和非糯性基因型。发现糯性和非糯性样品之间酚类化合物含量存在显著差异，糯性大麦样品中游离和结合酚类化合物含量较高。一旦确定了最佳判别HPLC柱，就应用主成分分析（PCA），它能够区分“糯性”和“非糯性”品种；然而，它仅根据游离酚类化合物来区分大麦样品。因此，进行了偏最小二乘判别分析（PLS-DA）和人工神经网络（ANN）。PLS-DA和ANN允许根据游离和结合酚类化合物对糯性和非糯性基因型进行分类。
Zotero 插件