Interaction among grapevine cultivars (Sangiovese, Cabernet-Sauvignon and Merlot) and site of cultivation in Bolgheri (Tuscany)

The assessment of wine authenticity is of great importance for consumers, producers and regulatory agencies to guarantee the geographical origin of wines and grape variety as well. Since mid-infrared (MIR) spectroscopy with chemometrics represent a suitable tool to ascertain the wine composition, including features associated with the polyphenolic compounds, the aim of this study was to generate MIR spectra of red wines to be exploited for classification of red wines based on the relationship between grape variety and wine composition. Several multivariate data analyses were used, including Principal Component Analysis (PCA), Discriminant Analysis (DA), Support Vector Machine (SVM), and Soft Intelligent Modelling of Class Analogy (SIMCA).

AIM: Wine consumption in the last fifteen years showed a decrease in Europe [1]. New alternatives of wines appeared on the market. Those beverages are obtained by blending wines and fruit juices or flavoring wines with artificial or natural aromas and have medium alcohol content (from 8 to 10.5%) [2]. Recently, an innovative fruit wine has been proposed obtained by co-fermenting grape must and kiwi juice [3] whose potential attractiveness to consumers should be exploited. However, differences in product acceptability and perception, as well as the individuals’ willingness to consume and pay could change in function of subjects socio-demographic characteristics. The target group selected is represented by young adults (18-35 years old) consumption groups.

Terroir studies are common nowadays but few have used precise pedoclimatic measures in order to evaluate the precocity potential. The objectives of this work were (i) to assess the effect of main terroir parameters (soil, climate and topography) influencing the phenological development of the vine, and (ii) to evaluate a geostatistic approach by using a high number of already existing plots (higher variability) to analyze the terroir parameters’ impact.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Saccharomyces cerevisiae (SC) is the main driver of alcoholic fermentation however, in wine, non-Saccharomyces species can have a powerful effect on aroma and flavor formation. This study aimed to compare untargeted volatile compound profiles from SPME-GC×GC-TOF-MS of Sauvignon blanc and Shiraz wine inoculated with six different non-Saccharomyces yeasts followed by SC. Torulaspora delbrueckii (TD), Lachancea thermotolerans (LT), Pichia kluyveri (PK) and Metschnikowia pulcherrima (MP) were commercial starter strains, while Candida zemplinina (CZ) and Kazachstania aerobia (KA), were isolated from wine grape environments. Each fermentation produced a distinct chemical profile that was unique for both grape musts. The SC-monoculture and CZ-SC sequential fermentations were the most distinctly different in the Sauvignon blanc while the LT-SC sequential fermentations were the most different from the control in the Shiraz fermentations.