Amyndeon‐naoussa: the two faces of Xinomavro

The wine sector is one of the most significant industries worldwide, with Spain being a leading country in wine production and export. A key factor in wine quality is its aroma, which is directly influenced by the volatile compounds present in the grape, with terpenes being among the most significant contributors.

Grapevine cultivars are vegetatively propagated to maintain their varietal characteristics. This process of multiplication leads to spontaneous somatic mutations that can eventually generate a variant phenotype, of potential interest for cultivar improvement and innovation. However, regardless their phenotypic effect, somatic mutations stack in the genome, and they can be used to reveal the origin and dissemination history of ancient cultivars. Here, a stringent somatic variant calling over whole genome resequencing data from 35 ‘Tempranillo Tinto’ clones or old vines from seven Iberian winemaking regions revealed 135 single nucleotide variations (SNVs) shared by some of the clonal lines.

The wine industry faces the consumer’s increasing demand for a sustainable and environmentally-friendly production [1]. This demand has been shared and boosted by the European Union within the European Green Deal in the Farm to Fork strategy that aims to reduce a 50% the pesticide utilisation in farming systems. Among the agronomical approaches so far proposed, the use of mould resitant hybrid varieties -based on crossings of Vitis vinifera with other Vitis spp [2]- with a high tolerance to the attack of vine patogens is gaining the vinegrowers attention and the production area is continuously increasing

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).

AIM: Proanthocyanidins are responsible in an important way for positive aspects in wines, such as body and color stability in red wines, but they are also responsible for sensory characteristics that can be negative for their quality when found in excessive concentrations.