Data deluge: Opportunities, challenges, and lessons of big data in a multidisciplinary project

Riesling is the iconic grape variety of Germany and accounts for 23% of the German viticulture acreage, which comprises 45% of the worldwide Riesling plantings. Riesling wines offer a wide array of styles from crisp sparkling wines to highly concentrated and sweet Trockenbeerenauslese or Icewines. However, its thin berry skin makes Riesling more vulnerable to detrimental environmental threats than other white wine varieties.  

Pinot Blanc, an important grape variety grown in some mountain areas of Northern Italy such as South Tyrol over the last decades, with its cultivation covering 10.3% of the total vineyards, has compatible climatic conditions (e.g. heat requirements) which are normally found in the geographical areas of the mountain viticulture [1,2,3,4]. Climatic changes are hastening the growth of this variety at higher elevations, particularly for the production of high quality wine.

Il mal dell’esca é una malattia della vite della quale sono state studiate sintomatologia, eziologia, patogenesi ed epidemiologia. Essendo una malattia che colpisce soprattutto la parte epigea delle piante, le caratteristiche dei suoli non sono mai state considerate fra le responsabili della sua insorgenza e diffusione.

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.

This work began as an intellectual game, in order to discuss the notion of wine quality in terms of terroir and territory spatial structure. Vine and wine quality has long been questioned by scientists. Each discipline approaching it with his own tools.