Keg wine on tap: a sustainability-oriented innovation

Wine quality is defined by sensory and physico-chemical characteristics. In particular, sensory features are very important since they strongly condition wine acceptability by consumers. However, the evaluation of sensory quality can be subjective, unless performed by a tasting panel of experienced tasters. Therefore, it is of great relevance to establish relationships between objective chemical parameters and sensory perceptions, even though the complexity of wine composition makes it difficult. In this sense, more reliable relationships can be found for a particular wine typology or variety. The present study aimed to predict the perceived sensory quality from the physico-chemical parameters of ‘Barbera d’Asti’ DOCG red wines (Italy).

Teran is an important native variety grown in Istria known for its high level of polyphenols and intensive fruity character of wines. Teran’s yield and wine typicity have recently decreased due to climate changes (increased temperature and severe drought). Four drip irrigation treatments (25%, 50%, 75%, 100% of total evapotranspiration) and control were investigated for the influence on Teran yield and quality, where focus was given to the content and composition of main polyphenolic and volatile compounds in grapes. Irrigation positively influenced yield since the berry weight also increased with increased irrigation. This resulted in the highest yield for 100% ETc. The highest concentration of polyphenols had control, while the irrigation treatments did not differ significantly. However, there was a tendency to decrease concentration with increased irrigation probably due to the increased berry size, which led to a dilution effect. Regarding the volatile compounds, the most abundant group was alcohols, followed by acids.

Aim: To quantify the extent to which national mixes of wine grape varieties (in terms of vineyard bearing area) have become more or less diversified, and ‘internationalized’, since wine globalization accelerated from the 1990s.

I territori della Riserva Geologica del Piacenziano sono parte del pedeappennino piacentino e sono noti per essere la culla del Pliocene, quel periodo di storia della Terra compreso tra 5.3 e 1.8 milioni di anni fa. Gli strati argillosi e sabbiosi riccamente fossiliferi qui presenti sono da sempre oggetto di studi geo-paleontologici tant’è che il Pliocene medio (3.6-2.6 milioni di anni fa) è internazionalmente noto come Piacenziano. Le analisi sensoriali strutturate dei vini qui prodotti hanno evidenziato, soprattutto per il vino Monterosso, le positive peculiarità dei loro caratteri sensoriali e descritto gli scostamenti significativi del loro profilo sensoriale rispetto agli altri vini presi a riferimento.

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.