Clone performance under different environmental conditions in California

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.

Nowadays, it is well known that oxygen significantly impacts wine quality. The amount of oxygen wine consumes during the winemaking process depends on several factors, such as storage conditions, the number of rackings, the materials used for aging, and the type of closure chosen for bottling.

During wine aging, several complex phenomena of gas transfer take place in barrels due to the wine/oak contact. The efficiency of this gas transfer varies according to oak wood’s intrinsic physical properties. This research aims to better understand oxygen transfer phenomena through dry oak staves and especially through stave gaps, in order to reevaluate the importance of barrel-making on a barrel’s supply of oxygen. Experimentation was based on the development of an innovative permeameter of laboratory scale, for which the principal operating conditions concerning applied pressure, the choice of liquid phase/gas phase, and the grain type of oak are taken into account and investigated. With a specially developed tightening system, the existing pressure at stave gaps in a barrel could be reproduced on a laboratory scale in order to estimate its influence on oxygen transfer efficiency.

The main goal of the current study is the development of a cost-effective and easy-to-use method suitable for use in the laboratory of commercial wineries to analyze wine aroma. Additionally, this study attempted to establish a prediction model for wine quality gradings based on their aroma, which could reveal the important aroma compounds that correlate well with different grades of perceived quality METHODS: Parameters of the SHS−GC−IMS instrument were first optimized to acquire the most desirable chromatographic resolution and signal intensities. Method stability was then exhibited by repeatability and reproducibility. Subsequently, compound identification was conducted. After method development, a total of 143 end-ferment wine samples of three different quality gradings from vintage 2020 were analyzed with the SHS−GC−IMS instrument. Six machine learning methods were employed to process the results and construct a quality prediction model. Techniques that aim to explain the model to extract useful insights were also applied.

As the climate warms, the focus of concern in viticulture often turns to how higher temperatures may shift growing regions, change the character of AVAs, and alter fruit quality. However, climate warming is increasing most quickly during the winter dormancy cycle, a critical and often underappreciated portion of the grapevine life cycle. In response to decreasing temperatures and decreasing daylength, grapes initiate a series of physiological changes to enter dormancy, acquire freeze resistance, and time spring phenology such that the growing season begins after threat of frost.