ArticleMolecules (Basel, Switzerland)2023
Terroir Influence on Polyphenol Metabolism from Grape Canes: A Spatial Metabolomic Study at Parcel Scale.
Article in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 11 citations in OpenAlex.
- Recent uses and applications of nuclear magnetic resonance, isotope ratio mass spectrometry and high-resolution mass spectrometry for authenticity and geographical origin of wines.Food science and biotechnology · 2025Review
- Subregional pedoclimatic conditions with contrasted UV-radiation shape host-microbiome and metabolome phenotypes in the grape berry.Food chemistry: X · 2025Article
- Classification of grape seed residues from distillation industries in Europe according to the polyphenol composition highlights the influence of variety, geographical origin and color.Food chemistry: X · 2024Article
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Authors and funding
12 authors at 2 institutions in 1 country.
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Abstract
The composition of bioactive polyphenols from grape canes, an important viticultural byproduct, was shown to be varietal-dependent; however, the influence of soil-related terroir factors remains unexplored. Using spatial metabolomics and correlation-based networks, we investigated how continuous changes in soil features and topography may impact the polyphenol composition in grape canes. Soil properties, topography, and grape cane extracts were analyzed at georeferenced points over 3 consecutive years, followed by UPLC-DAD-MS-based metabolomic analysis targeting 42 metabolites. Principal component analyses on intra-vintage metabolomic data presented a good reproducibility in relation to geographic coordinates. A correlation-driven approach was used to explore the combined influence of soil and topographic variables on metabolomic responses. As a result, a metabolic cluster including flavonoids was correlated with elevation and curvature. Spatial metabolomics driven by correlation-based networks represents a powerful approach to spatialize field-omics data and may serve as new field-phenotyping tool in precision agriculture.
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Registered trials
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