Soil management with respect to nitrogen mobilization and nutrient supply of grapevines on loess soil

Yeast assimilable nitrogen (YAN) in the grape must is a key variable for wine quality as a source of aroma precursors. In a situation of YAN deficiency, a foliar urea application upon the vine at veraison enhances YAN concentration and facilitates must fermentation. In 2013, Agroscope investigated the impact of leaf-fruit ratio on the nitrogen (N) assimilation and partitioning in grapevine Vitis vinifera cv. Chasselas following foliar-urea application with the aim of improving its efficiency on the YAN concentration.

According to the World Economic Forum and the European Union’s Biodiversity Strategy for 2030, the loss of biodiversity and the collapse of ecosystems are major threats facing humanity in the future.

Grapevine yield and fruit quality are two major drivers of input allocation and, ultimately, revenue for grape producers. Because yield and fruit quality vary substantially from year-to-year and within a single block, opportunities exist for optimization via precision management activities that could lead to more profitable and sustainable grape production. Here, we review recent advances in the techniques and technology used to measure, estimate, and forecast grapevine yield and fruit quality. First, we discuss direct “measurement” of yield and quality (i.e. ground-truth data generation), with an emphasis on potential for scalability and automation. Second, we discuss technology and techniques that do not directly measure yield and quality, but use correlated measurements for their estimation.

Multiple Factor Analysis (MFA) According to the Chenin blanc Association of South Africa, there are three recognized dry wine styles, Fresh and Fruity (FF), Rich and Ripe Unwooded (RRU), and Rich and Ripe Wooded (RRW), classically attributed with the help of sensory evaluation. One of the “rapid methods” has drawn our attention for the purpose of simplifying and making style attribution for large sample sets, evaluated during different sessions, more robust. Polarized Projective Mapping (PPM) is a hybrid of Projective Mapping (PM) and Polarised Sensory Positioning (PSP). It is a reference-based method in which poles
(references) are used for the evaluation of similarities and dissimilarities between samples.

We evaluate wine ratings by comparing data from two crowdsourcing platforms – Vivino, which aggregates the opinions of a large number of wine lovers, and Global Wine Medal Rating, which aggregates the scores from more than 1030 international wine competitions since 2020.