Using open source software in viticultural research

During a three-year period, the vineyards of the Carnuntum wine district are investigated for their terroir characteristics. The interdisciplinary study is aimed at the description of the physiogeographic

AIM: Grape flavanols are involved in wine quality markers such as in-mouth sensations and colour stability.

Table grape production requires adequate nitrogen (N) supply to sustain vine performance and obtain high yields. However, excess agricultural N fertilization is a major source of groundwater contamination and air pollution. Therefore, there is a strong need for empirically based precision N fertilization schemes in vineyards, for optimizing grape yield and quality while minimizing their environmental impact.
Our aim was to unequivocally quantify table grape N requirements, elucidate the drivers of daily N uptake, and quantify the relationship between fertigation N levels and vine growth, fruit yield, composition, and quality. For this, forty ‘Early Sweet’ (early-maturing, white) and ‘Crimson seedless’ (late-maturing, red) vines were grown in 500L drainage-lysimeters for 2 fruiting seasons, while subjected to five continuous N fertigation treatments ranging from 10 to 200 ppm.

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.

In a context of reducing herbicide use, the most part of French vineyards are developing permanent grass cover crops on inter-rows alleys, while under the row chemical weeding remains the general case. The setting up of a controlled grass cover crop under the vine row could be a complementary alternative to mechanical weeding – which one is very restrictive – interesting from a technical and economical point of view. The present study aimed at assessing agronomic impacts of grass cover crop under the row in different climatic conditions and production objectives.