Combination of NIR multispectral information acquired from a ground moving vehicle with AI methods to assess the vine water status in a Tempranillo (Vitis vinifera L.) commercial vineyard

The use of cover crops under the vines might be an alternative to the use of herbicides or tillage, improving grapevine quality and soil characteristics. The aim of this research was to study the implications of different management strategies of the soil under the vines (herbicide, cultivation or cover crops) on grapevine growth, water and nutritional status, gas exchange parameters and belowground microbial communities.
The experimental design consisted in 4 treatments applied on 35L-potted Tempranillo vegetative grapevines with 10 replicates each grown in an open-top greenhouse in 2022 and 2023. Treatments included two cover crop species (Trifolium fragiferum and Bromus repens), herbicide (glyphosate al 36%) and an untreated control.

Assessing grape composition is critical in vineyard management. It is required to decide the harvest date and to optimize cultural practices toward the achievement of production goals. The grape composition is variable in time and space, as it is affected by the ripening process and depends on soil and climate conditions.

Climate change presents a significant challenge for actual viticulture. In this context, recovering minority grape varieties can be a crucial strategy to ensure resilience, particularly those capable of maintaining quality and aromatic complexity under water stress.

Context and purpose of the study. Climate change is affecting wine production and induces a large variability in wine composition between vintages.

The aim of this study was to evaluate the effects of different soil types on the chemical composition of Mediterranean red wines, through untargeted and targeted 1H-NMR metabolomics. One milliliter of raw wine was analyzed by means of a Bruker Avance II 400 spectrometer operating at 400.15 MHz. The spectra were recorded by applying the NOESYGPPS1D pulse sequency, to achieve water and ethanol signals suppression. No modification of the pH was performed to avoid any chemical alteration of the matrix. The generation of input variables for untargeted analysis was done via bucketing the spectra. The resulting dataset was preprocessed prior to perform unsupervised PCA, by means of MetaboAnalyst web-based tool suite. The identification of compounds for the targeted analysis was performed by comparison to pure compounds spectra by means of SMA plug-in of MNova 14.2.3 software. The dataset containing the concentrations (%) of identified compounds was subjected to one-way analysis of variance (ANOVA) to highlight significant differences among the wines. The untargeted analysis, carried out through the PCA, revealed a clear differentiation among the wines. The fragments of the spectra contributing mostly to the separation were attributed to flavonoids, aroma compounds and amino acids. The targeted analysis leaded to the identification of 68 compounds, whose concentrations were significant different among the wines. The results were related to soils physical-chemical analysis and showed that: 1) high concentrations of flavan-3-ols and flavonols are correlated with high clay content in soils; 2) high concentrations of anthocyanins, amino acids, and aroma compounds are correlated with neutral and moderately alkaline soil pH; 3) low concentrations of flavonoids and aroma compounds are correlated with high soil organic matter content and acidic pH. The 1H-NMR metabolomic analysis proved to be an excellent tool to discriminate between wines originating from grapes grown on different soil types and revealed that soils in the Mediterranean area exert a strong impact on the chemical composition of the wines.