1H NMR metabolomics applied to Bordeaux red wines.

The q-NMR metabolomics has already demonstrated its potential for classifying wines of different geographical origins, grape varieties, or vintages. This study focuses on the characterisation of Bordeaux red wines, seeking to discriminate them from others produced in the major French wine regions. A sampling of 224 commercial French wines was analysed by 1H NMR and forty compounds were quantified. Non-supervised and supervised statistical analyses revealed a singular imprint of Bordeaux wines in comparison with other French wines, with classification rates ranging from 71% to 100%. Within the Bordeaux vineyards, red wines from the different Bordeaux subdivisions were analysed from different vintages. Our results indicate that q-NMR metabolomics enables the differentiation of Médoc and Libournais vineyard highlighting the most discriminant constituents. In addition, the effects of wine evolution during bottle aging and vintage on Bordeaux red wines were pointed out and discussed.

Impact of different elicitors on grapevine leaf metabolism monitored by 1H NMR spectroscopy.

INTRODUCTION: Grapevine protection is an important issue in viticulture. To reduce pesticide use, sustainable disease control strategies are proposed, including a promising alternative method based on the elicitor-triggered stimulation of the grapevine natural defense responses. However, detailed investigations are necessary to characterize the impact of such defense induction on the primary metabolism. OBJECTIVES: Our aim was to use a metabolomics approach to assess the impact on grapevine of different elicitors dependent on the salicylic acid (SA) and/or jasmonic acid (JA) pathway. For this purpose, leaves of grapevine foliar cuttings were treated with methyl jasmonate, acibenzolar-S-methyl or phosphonates. METHODS: According to the elicitor, common and discriminating metabolites were elucidated using 1H NMR measurements and principal component analysis. RESULTS: A wide range of compounds including carbohydrates, amino acids, organic acids, phenolics and amines were identified. The score plots obtained by combining PC1 versus PC2 and PC1 versus PC3 allowed a clear separation of samples, so metabolite fingerprinting showed an extensive reprogramming of primary metabolic pathways after elicitation. CONCLUSION: The methods applied were found to be accurate for the rapid determination and differential characterization of plant samples based on their metabolic composition. These investigations can be very useful because the application of plant defense stimulators is gaining greater importance as an alternative strategy to pesticides in the vineyard.