Influence of the year and the environmental factors on condensed tannins from Cabernet franc grapes

Grapevine leaf removal (LR) in the cluster area is typically done between fruit set and cluster closure to create an unfavorable microclimate for fungal diseases, such as Botrytis cinerea and powdery mildew. Grape growers are now turning their attention to pre-flowering LR, which has additional benefits under certain conditions. When applied before flowering, LR strongly affects fruit set and thus the number of berries per cluster. It is therefore a good yield control tool, replacing time-consuming manual cluster thinning (Poni et al. 2006). It also improves berry structure, that is, skin thickness, skin-to-pulp ratio, and berry composition (total soluble solids, titratable acidity, and polyphenols) (Palliotti et al. 2012; Komm and Moyer 2015). By exacerbating competition for assimilates between reproductive and vegetative organs, pre-flowering LR also poses some risks. Excessive yield loss at the same year’s harvest due to a too low fruit set rate is the main concern: intensive pre-flowering LR (100% of the cluster area) can induce up to 50% yield loss in potted vines (Poni et al. 2005). Other parameters, such as cool climatic conditions during flowering, also affect fruit set rate and make it difficult to predict potential yield at harvest. Repeated and overly intensive preflowering LR can have repercussions over time and induce a decline in bud fruiting and plant vigor (Risco et al. 2014).

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.

Tomatoes and Grapes are berries that are genetically related and therefore at least partially their developmental pathways leading to a fleshy fruit should share some of the components. In a sense knowledge obtained from the model plant tomato could be useful for grape and conversely the more amenable tomato can be used to test some hypothesis that would be difficult to obtain in grape. Research in my lab and other labs have led to a better understanding of the molecular genetics mechanisms underlying fruit development and ripening in tomato and more specifically those related to metabolite accumulation that may lead to changes in fruit nutritional and flavor composition. This research has involved the use of genetic variability in natural population, but also biparental population and genetically engineered lines that are easy to develop in tomato tomato but not in grape. NGTs also can be easily implemented in tomato to not only speed up the gene-to-trait but also develop new tomato varieties.

Wine aroma represents one of the most important quality parameter and it is influenced by various factors (viticulture and vinification techniques, climate or storage conditions etc.). Wines produced from conventionally and ecologically grown grapes of same variety have different chemical composition and aroma profile [1]. Aroma profile of wine can be also influenced by additional treatment of wine, such as concentration of wine by reverse osmosis (RO). Reverse osmosis represents a pressure-driven membrane separation technique that separates the initial wine on the retentate or concentrate that is retained on the membrane, and permeate that passes through it [2]. Wine permeate usually containes water, ethanol, acetic acid and several low molecular weight compounds that can pass through the membrane. This property enables the use of reverse osmosis membranes for wine concentration, partial dealcoholization, acetic acid or aroma correction [3,4].

Le terme ”Albariza” (du latin “albus“, blanc) déterminait à l’origine un type particulier du terrain calcaire, mais à présent il sert aussi à définir les sols et la bibliographie géologique actuelle le cite également pour de roches sédimentaires originaires du Neogene Betic.