Mapping natural terroir units using a multivariate approach and legacy data

La topographie du vignoble de Côte Rôtie, la prédominance de la non culture ainsi que la structure très légère des sols amènent les vignerons à s’interroger sur l’entretien du sol, la conduite de la fertilisation de leurs parcelles ainsi que sur le développement racinaire de la vigne.

FNB Top 10 Sauvignon Blanc competition, presented by the Sauvignon Blanc Interest Group of South Africa and sponsored by First National Bank, is the country’s foremost platform for producers of this cultivar to showcase and benchmark their wines. Wines entered in the competition originated from all over the winegrowing regions of the country and the winning wines showed good representation of quality South African Sauvignon blanc wines. The ten selected wines were subjected to various chemical analyses including volatile thiol and methoxypyrazine determination, while the sensory profile of each wine was determined using projective mapping.

Aim: to elucidate if it is possible to detect variations in the source of nitrogen (organic vs. inorganic) measuring nitrogen isotope ratio (δ15N) in berries and to examine the degree of variation occurring for this parameter naturally within a vineyard.

Extraction of anthocyanins and tannins have been studied for two grape varieties, Carignan and Grenache, two maturation levels and two vintages, in model solutions and in wines, using UHPLC-MS/MS in the MRM mode  and HPSEC.

Knowledge on the reflectance spectrum of soil is potentially useful since it carries information on soil chemical composition that can be used to the planning of agricultural practices. If compared with analytical methods such as conventional chemical analysis, reflectance measurement provides non-destructive, economic, near real-time data. This paper reports results from reflectance measurements performed by spectroradiometry on soils from two vineyards in south Brazil. The vineyards are close to each other, are on different geological formations, but were subjected to the same management. The objective was to detect spectral differences between the two areas, correlating these differences to variations in their chemical composition, to assess the technique’s potential to predict soil attributes from reflectance data.To that end, soil samples were collected from ten selected vine parcels. Chemical analysis yield data on concentration of twenty-one soil attributes, and spectroradiometry was performed on samples. Chemical differences significant to a 95% confidence level between the two studied areas were found for six soil attributes, and the average reflectance spectra were separated by this same level along most of the observed spectral domain. Correlations between soil reflectance and concentrations of soil attributes were looked for, and for ten soil traits it was possible to define wavelength domains were reflectance and concentrations are correlated to confidence levels from 95% to 99%. Partial Least Squares Regression (PLSR) analyses were performed comparing measured and predicted concentrations, and for fifteen out of 21 soil traits we found Pearson correlation coefficients r > 0.8. These preliminary results, which have to be validated, suggest that variations of concentration in the investigated soil attributes induce differences in reflectance that can be detected by spectroradiometry. Applications of these observations include the assessment of the chemical content of soils by spectroradiometry as a fast, low-cost alternative to chemical analytical methods.