Matériel végétal et valorisation des terroirs viticoles

Production of volatile compounds by yeast is known to be modulated by must nitrogen. Nevertheless, various parameter of must quality have an impact on yeast fermentation. In this study we propose to evaluate the impact of nitrogen / lipids balance on a Sauvignon Blanc grape juice (Val de Loire).
Must was prepared from the same grapes at pilot scale. Three modalities were carried out: direct pressing, direct pressing with a pre-fermentation cold stabulation and pellicular maceration before pressing.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

Recently, foliar treatments with mineral-based compounds have shown positive effects on grapevine production by protecting grape from thermal excesses and reducing the decoupling between technological and phenolic maturity caused by climate change. Unraveling the effect of mineral particle applications on grape-associated microbes is pivotal for successful wine processing, due to the influence of the microbiota on wine composition and stability. To our knowledge, this is the first work that comprehensively studied the effects of kaolin and chabasite-rich zeolitites treatments on grape-related microorganisms (by real-time PCR quantification of total fungi, Hanseniospora uvarum, Metschnikowia pulcherrima, plant-associated bacteria and lactic acid bacteria), the expression of genes related to the flavonoid biosynthesis (PAL1, CHS1, F3H2, DFR, LDOX, UFGT, MYBA1, GST4, FLS4 genes) and the berry composition (°Brix, pH, acidity and anthocyanin concentrations) in cv. Sangiovese during ripening in two growing seasons (2019 and 2020).

Monitoring vine water status is a major challenge for vineyard management because it influences both yield and harvest quality. It is also a challenge at the territorial scale for identifying periods of high water restriction or zones regularly impacted by water stress. This information is of major importance for defining collective strategies, anticipating harvest logistic or applying for irrigation authorisation. At this spatial scale, existing tools and methods for monitoring vine water status are few and often require strong assumptions (e.g. water balance model). This paper proposes to consider a collaborative collection of observations by winegrowers and wine industry stakeholders (crowdsourcing) as an interesting alternative. Indeed, it allows the collection of a large number of field observations while pooling the collection effort. However, the feasibility of such a project and its interest in monitoring vine water status at regional scale has never been tested.

The objective of this article is to explore the possibility of making a regional map of vine water status based on crowdsourcing observations. It is based on the study of the free mobile application ApeX-Vigne, which allows the collection of observations about vine shoot growth. This information is easy to collect and can be considered, under certain conditions, as a proxy for vine water status. This article presents the first results obtained from the nearly 18,000 observations collected by winegrowers and wine industry stakeholders during 2019, 2020 and 2021 seasons. It presents the vine shoot growth maps obtained at regional scale and their evolution over the three vintages studied. It also proposes an analysis of the factors that favoured the number of observations collected and those that favoured their quality. These results open up new perspectives for monitoring vine water status at a regional scale but above they provide references for other crowdsourcing projects in viticulture.

La adaptación de nuevas variedades a zonas de cultivo fuera de su área de origen presenta múltiples interrogantes. En Castilla-La Mancha se está produciendo en los últimos años una gran inquietud por la diversificación y la reconversión de variedades.