Metabolic mapping for precision grape maturation: Application of a tomography-like method for site-specific management

• A tomography-like (TL) based on Vis-NIR sensors allows grape metabolic maps. • TL uses a superset for spectral bi-directional pulp, skin and seed reconstruction. • TL non-destructively predicts in situ physicochemical parameters of grape tissues. • TL relates the agri-environment of maturation for precision viticulture. This study demonstrates the application of a tomography-like (TL) method to monitor grape maturation dynamics over two growing seasons (2021–2022) in the Douro Wine Region. Using a Vis-NIR point-of-measurement sensor, which employs visible and near-infrared light to penetrate grape tissues non-destructively and provide spectral data to predict internal composition, this approach captures non-destructive measurements of key physicochemical properties, including soluble solids content (SSC), weight-to-volume ratio, chlorophyll and anthocyanin levels across internal grape tissues - skin, pulp, and seeds - over six post-veraison stages. The collected data were used to generate detailed metabolic maps of maturation, integrating topographical factors such as altitude and NDVI-based (normalised difference vegetation index) vigour assessments, which revealed significant ( p < 0.05) variations in SSC, chlorophyll, and anthocyanin levels across vineyard zones. The metabolic maps generated from the TL method enable high-throughput data to reveal the impact of environmental variability on grape maturation across distinct vineyard areas. Predictive models using random forest (RF) and self-learning artificial intelligence (SL-AI) algorithms showed RF’s robustness, achieving stable predictions with R² ≥ 0.86 and MAPE ≤ 33.83 %. To illustrate the TL method’s practical value, three hypothetical decision models were developed for targeted winemaking objectives based on SSC, chlorophyll in the pulp, and anthocyanin in the skin and seeds. These models underscore the TL method’s ability to support site-specific management (SSM) by providing actionable agricultural practices (e.g. harvest) into vineyard management, guiding winemakers to implement tailored interventions based on metabolic profiles rather than only cultivar characteristics. This precision viticulture (PV) approach enhances wine quality and production efficiency by aligning vineyard practices with specific wine quality goals.