Volatile and phenolic composition of Agiorgitiko wines from eight different areas of PDO Nemea zone

The wine industry is increasingly focused on carbon accounting due to consumer’s demand and the industry’s goal of reducing carbon emissions.

Chardonnay is the world’s most planted white grape variety and has met a great commercial success for decades.

Grape quality potential for wine production is strongly influenced by environmental parameters and agronomic factors. Several studies underline the rootstock effect on scions vegetative growth and berry composition [1] with an impact on wine quality. Rootstocks are promising agronomic tools for climate change adaptation and in most grape-growing regions the potential diversity of rootstocks is not fully used and only a few genotypes are planted. Moreover, little is known about the effect of rootstock genetic variability on the aromatic composition in wines.

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.

Epigenetics corresponds to the complement of genetic information carried in chromatin beyond the DNA sequence.