Biotic interactions: case of grapevine cultivars – the fungal pathogen Neofusicoccum parvum – biocontrol agents 

Amino acids play a crucial role in determining grape and wine quality [1]. Recently, research has suggested their metabolism is key to plant abiotic stress tolerance [2]. Therefore, the study of amino acid accumulation in grape berries and its response to environmental factors is of both scientific and economic importance.

Une étude préliminaire des situations météorologiques journalières a été réalisée pour l’Afrique du Sud et pour les mois de février (période de maturation des raisins dans la Province occidentale du Cap), à l’image de la classification synoptique réalisée aux latitudes tempérées en France (Jones & Davis, 2000), afin d’étudier les relations entre le climat et la viticulture à des latitudes plus basses.

Non-Saccharomyces yeasts have been associated, for many years, with challenging alcoholic fermentation processes. However, during the last decade the use of non-Saccharomyces yeasts in wine production has become increasingly widespread due to the advantages they can offer in mixed inoculations with Saccharomyces cerevisiae (Sc). In this respect, Hanseniaspora vineae (Hv), in synergy with Saccharomyces spp, represents an interesting opportunity to impart a positive contribution to the aroma complexity of wines. In fact, it is a well-known producer of pleasant esters, such as 2-phenylethyl acetate. This study compares the performances of Hv (strain Hv-205) in sequential inoculation modality to Sc in three Chardonnay musts for base sparkling wine production. No significant differences were observed in basic chemical parameters between wines except for titratable acidity, with a significantly decrease (up to 1.5 g/L) in Hv processes due to malic acid degradation. The analysis of the aroma compounds revealed remarkable differences in concentration of volatile metabolites, among others up to 37-fold increase of 2-phenylethyl acetate. In contrast, lower concentration of its alcohol were detected, suggesting higher acetylation activity by Hv.

Aim: Through machine-learning modelling of plant water status from environmental characteristics, this work aims to develop a model able to predict grape phenolic composition in space and time to guide selective harvest decisions at the estate scale.

Amarone is an Italian red wine produced in the Valpolicella area, in north-eastern Italy. Due to its elaboration with withered grapes