Gardiman Massimo, De Rosso Mirko, De Marchi Fabiola, Flamini Riccardo
Council for Agricultural Research and Economics - Research Center for Viticulture & Enology (CREA-VE), Conegliano (TV), 31015, Italy.
Metabolomics. 2023 Mar 28;19(4):25. doi: 10.1007/s11306-023-01997-w.
Prosecco wine production has been strongly extended in the last decade and several new clones have been introduced. "Glera" (minimum 85%) and "Glera lunga" are grape varieties of great economic impact used to produce Prosecco wines. Study of grape berry secondary metabolites is effective in the classification of vine varieties and clones. High-resolution mass spectrometry provides complete panorama of these metabolites in single analysis and coupling to statistical multivariate analysis is successfully applied in vine chemotaxonomy.
update and deepen the knowledge on the "Glera" and "Glera lunga" berry grapes chemotaxonomy and investigate some of the most produced and marketed clones by using the modern analytical and statistical tools.
five clones of "Glera" and two of "Glera lunga" grown in the same vineyard with same agronomical practices were studied for three vintages. Grape berry metabolomics was characterized by UHPLC/QTOF and multivariate statistical analysis was performed on the signals of main metabolites of oenological interest.
"Glera" and "Glera lunga" showed different monoterpene profiles ("Glera" is richer in glycosidic linalool and nerol) and differences in polyphenols (catechin, epicatechin and procyanidins, trans-feruloyltartaric acid, E-ε-viniferin, isorhamnetin-glucoside, quercetin galactoside). Vintage affected the accumulation of these metabolites in berry. No statistical differentiation among the clones of each variety, was found.
Coupling HRMS metabolomics/statistical multivariate analysis enabled clear differentiation between the two varieties. The examined clones of same variety showed similar metabolomic profiles and enological characteristics, but vineyard planting using different clones can result in more consistent final wines reducing the vintage variability linked to genotype × environment interaction.
在过去十年中，普罗塞克葡萄酒的产量大幅增长，并且引入了几个新的克隆品种。“格雷拉”（最低85%）和“长格雷拉”是用于生产普罗塞克葡萄酒的具有重大经济影响的葡萄品种。对葡萄浆果次生代谢产物的研究有助于葡萄品种和克隆品种的分类。高分辨率质谱法在单次分析中就能提供这些代谢产物的完整全景图，并且与统计多变量分析相结合已成功应用于葡萄化学分类学。
更新并深化对“格雷拉”和“长格雷拉”浆果葡萄化学分类学的认识，并使用现代分析和统计工具研究一些产量最高且市场上销售的克隆品种。
对在同一葡萄园采用相同农艺措施种植的5个“格雷拉”克隆品种和2个“长格雷拉”克隆品种进行了三个年份的研究。通过超高效液相色谱/四极杆飞行时间质谱对葡萄浆果代谢组学进行表征，并对酿酒学感兴趣的主要代谢产物的信号进行多变量统计分析。
“格雷拉”和“长格雷拉”表现出不同的单萜类化合物谱（“格雷拉”中糖苷形式的芳樟醇和橙花醇含量更高）以及多酚类物质的差异（儿茶素、表儿茶素和原花青素、反式阿魏酰酒石酸、E - ε - 葡萄素、异鼠李素 - 葡萄糖苷、槲皮素半乳糖苷）。年份影响了这些代谢产物在浆果中的积累。未发现每个品种的克隆之间存在统计学差异。
高分辨率质谱代谢组学与统计多变量分析相结合能够清晰地区分这两个品种。同一品种的受试克隆品种表现出相似的代谢组学特征和酿酒学特性，但使用不同克隆品种进行葡萄园种植可以使最终葡萄酒更加稳定，减少与基因型×环境相互作用相关的年份变异性。
