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NMR 光谱法评价土壤与阿利坎特葡萄红酒分子组成的直接关系。

NMR spectroscopy evaluation of direct relationship between soils and molecular composition of red wines from Aglianico grapes.

机构信息

Centro Interdipartimentale per la Risonanza Magnetica Nucleare (CERMANU), Universita 'di Napoli Federico II, Via Universita' 100, 80055 Portici, Italy.

出版信息

Anal Chim Acta. 2010 Jul 19;673(2):167-72. doi: 10.1016/j.aca.2010.06.003. Epub 2010 Jun 9.

Abstract

(1)H NMR spectroscopy was employed to investigate the molecular quality of Aglianico red wines from the Campania region of Italy. The wines were obtained from three different Aglianico vineyards characterized by different microclimatic and pedological properties. In order to reach an objective evaluation of "terroir" influence on wine quality, grapes were subjected to the same winemaking procedures. The careful subtraction of water and ethanol signals from NMR spectra allowed to statistically recognize the metabolites to be employed in multivariate statistical methods: Principal Component Analysis (PCA), Discriminant Analysis (DA) and Hierarchical Clustering Analysis (HCA). The three wines were differentiated from each other by six metabolites: alpha-hydroxyisobutyrate, lactic acid, succinic acid, glycerol, alpha-fructose and beta-D-glucuronic acid. All multivariate analyses confirmed that the differentiation among the wines were related to micro-climate, and carbonate, clay, and organic matter content of soils. Additionally, the wine discrimination ability of NMR spectroscopy combined with chemometric methods, was proved when commercial Aglianico wines, deriving from different soils, were shown to be statistically different from the studied wines. Our findings indicate that multivariate statistical elaboration of NMR spectra of wines is a fast and accurate method to evaluate the molecular quality of wines, underlining the objective relation with terroir.

摘要

(1)采用 1H NMR 光谱法研究了来自意大利坎帕尼亚地区的阿利尼科红葡萄酒的分子质量。这些葡萄酒来自三个具有不同微气候和土壤特性的不同阿利尼科葡萄园。为了对“风土”对葡萄酒质量的影响进行客观评价,葡萄采用了相同的酿酒工艺。通过仔细从 NMR 光谱中减去水和乙醇信号,我们可以统计识别出用于多元统计方法的代谢物:主成分分析(PCA)、判别分析(DA)和层次聚类分析(HCA)。这三种葡萄酒通过六种代谢物彼此区分:α-羟基异丁酸、乳酸、琥珀酸、甘油、α-果糖和β-D-葡萄糖醛酸。所有多元分析均证实,葡萄酒之间的差异与微气候以及土壤中的碳酸盐、粘土和有机物含量有关。此外,当来自不同土壤的商业阿利尼科葡萄酒被证明在统计学上与所研究的葡萄酒不同时,NMR 光谱结合化学计量学方法的葡萄酒鉴别能力得到了证明。我们的研究结果表明,对葡萄酒 NMR 光谱进行多元统计分析是一种快速准确的方法,可以评估葡萄酒的分子质量,突出了与风土的客观关系。

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