Characterisation of viticultural and oenological practices in two French AOC in the middle Loire Valley: comparison of different methods to extract information from a survey among winegrowers

The utilization of non-Saccharomyces yeasts in the wine industry has increased significantly in recent years. Alternative species need commonly be employed in combination with Saccharomyces cerevisiae to avoid stuck fermentation, or microbial spoilage. The employment of more than one yeast starter can lead to interactions between different species with an impact on the outcome of wine fermentation. Previous studies[1] demonstrated that S. cerevisiae elicits transcriptional responses with both shared and species-specific features in co-culture with other yeast species.

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Table grape production requires adequate nitrogen (N) supply to sustain vine performance and obtain high yields. However, excess agricultural N fertilization is a major source of groundwater contamination and air pollution. Therefore, there is a strong need for empirically based precision N fertilization schemes in vineyards, for optimizing grape yield and quality while minimizing their environmental impact.
Our aim was to unequivocally quantify table grape N requirements, elucidate the drivers of daily N uptake, and quantify the relationship between fertigation N levels and vine growth, fruit yield, composition, and quality. For this, forty ‘Early Sweet’ (early-maturing, white) and ‘Crimson seedless’ (late-maturing, red) vines were grown in 500L drainage-lysimeters for 2 fruiting seasons, while subjected to five continuous N fertigation treatments ranging from 10 to 200 ppm.

Schiava cv. (germ. Vernatsch) is a group of grape varieties used for winemaking (e.g. Kleinvernatsch-Schiava gentile, Grauvernatsch-Schiava grigia, Edelvernatsch-Schiava grossa) historically reported in Northern Italy, Austria, Germany and Croatia. Beside common phenotypic traits, these varieties have been also hypothesized to share a common geographical origin in Slavonia (Eastern Croatia). Nowadays, Schiava cv. are considered historical grape varieties of northern regions of Italy such as Lombardy, Trentino and South Tyrol. Traditionally widely consumed locally and also exported, over the past decades there has been a steady drop in production of these grapes, although with a parallel increase in wine quality. In this report, the effects of three main enological variables on the chemical components of Schiava produced in South Tyrol (var. Schiava grossa) are investigated from grape to bottle.

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.