Effects of hormone- and natural-based elicitors at the transcriptomic level in berries of cv. Tempranillo

Aim: Pests have a high impact on yield and grape quality in viticulture. An objective and rapid detection of pests under field conditions is needed. New sensing technologies and artificial intelligence could be used for pests detection in digital viticulture. The aim of this work was to apply computer vision and deep learning techniques for automatic detection of spider mite symptoms in grapevine under field conditions. 

Many wine styles require moderate or extended ageing to ensure optimal consumer experience. However, few consumers have the interest or ability to age wine themselves, and holding wine in optimal conditions for extended periods is expensive for producers. A study was conducted on the use of ul-trasound energy on wine, with particular reference to its impact on sensory and chemical profiles. The OIV has authorised the use of ultrasound for processing crushed grapes (must) in Resolution OENO 616-2019, but not yet for finished wine1,2.

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.

Wine grapes breeding has been concentrating a lot of efforts within the grape research community over the last decade. The quick phenotyping of genotype quality traits including aroma composition remains challenging. Selected Ion Flow Tube Mass Spectrometry (SIFT-MS), a technology first available in 2008 and developing rapidly, could be particularly valuable for this usage. The aims of this study were i) to use SIFT-MS, to analyze the whole volatilome from different grape varieties, ii) to assess the ability of this technology to discriminate varieties according to their grape aroma composition, and iii) to study the stability of SIFT-MS signal over maturation to define a sampling strategy.

In the bottom of Val d’Illasi (Verona province), one of the major valleys which passes through the Lessini mountains, viticulture is widely extended. In the territory belonging to Illasi and Tregnago villages, which includes ca. 1100 ha of vineyards, devoted to produce Soave and Valpolicella DOC wines, an experimental survey was conducted on a network of twenty five reference vineyards.