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首页> 外文期刊>Microchemical Journal: Devoted to the Application of Microtechniques in all Branches of Science >Unraveling Vitis vinifera L. grape maturity markers based on integration of terpenic pattern and chemometric methods
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Unraveling Vitis vinifera L. grape maturity markers based on integration of terpenic pattern and chemometric methods

机译:基于萜烯图案和化学计量方法的整合,解开葡萄vinifera L.葡萄成熟度标记

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摘要

The current research attempts to provide an alternative tool for grape maturity measurement related to the wine composition since, the classical parameters (weight grape berries, sugar content, titratable acidity), commonly used in the winemaking industry, do not provide any sensorial information. In this context, the evolution of terpenic compounds (TC) during ripening of four V. vinifera L. grape varieties - Bual, Malvasia, Sercial (white grapes) and Tinta Negra (red grapes), was investigated, in addition to the establishment of terpenic pattern, using headspace solid phase microextraction (HS-SPME) combined with GC-MS. Using the optimal analytical conditions were identified 62 TC in the investigated V. vinifera L. grapes. The integration of chromatographic and chemometric data provides a powerful strategy to identify potential maturity markers. The maximum potential of mono- and sesquiterpenic compounds was reached at maturity, whereas the highest levels of norisoprenoids were observed at veraison. Partial Least Squares Regression (PLS-R) was employed to describe the relationship between classical parameters and TC. Based on PLS-R models, three monoterpenic (linalool, alpha-terpineol, carvomenthol), one sesquiterpenic (bicyclogermacrene) and two norisoprenoids compounds (vitispirane I, beta-damascenone) could be used to define the optimum harvest date.
机译:目前的研究试图提供与葡萄酒组成相关的葡萄成熟度测量的替代工具,因为葡萄酒组合物,常用于酿酒行业的经典参数(重量葡萄浆,糖含量,可滴定的酸度),不提供任何情感信息。在这种情况下,除了建立之外,还研究了四个V.Vinifera L.葡萄品种 - Bual,Malvasia,哺乳(白葡萄)和Tinta Negra(红葡萄)的逐渐变化期间的萜烯化合物(Tc)的演变。用顶空固相微萃取(HS-SPME)结合GC-MS,萜烯图案。使用最佳分析条件在研究的V.Vinifera L.葡萄中鉴定了62吨。色谱和化学计数数据的整合提供了强大的策略来识别潜在的成熟度标记。在成熟度下达到单次和筛选化合物的最大电位,而在Veraison中观察到最高水平的诺异戊二烯。部分最小二乘回归(PLS-R)用于描述经典参数和TC之间的关系。基于PLS-R模型,三种单萜(LINALOOL,α-萜品醇,甘草醇),一种倍半萜(双环丙酮)和两种Notisoprenoids化合物(Vitispirane I,Beta-Tabascenone)可用于定义最佳收获日期。

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