Lugana Protected Designation of Origin (PDO) wines are made from Turbiana grapes. The aroma of Lugana wines results from the combined contribution of esters, terpenes, norisprenoids, sulfur compounds and the benzenoid methyl salicylate. This study aims to investigate how volatile aroma compounds are affected by different nitrogen supplies and yeast strains. Wines were produced with a standard protocol with 2021 Turbiana grapes with two different yeasts Zymaflore Delta e Zymaflore X5 (Laffort, France).During the alcoholic fermentation of the must, when H2S appeared, additions of various nitrogen supply were made: inorganic nitrogen, organic nitrogen, a mix of inorganic and organic nitrogen and organic nitrogen with an addition of pure methionine. During wine fermentation, a daily measurement of hydrogen sulfide was carried out.

Eugenol has been identified as a quality marker in armagnac white spirits. In particular, those produced from the Baco blanc variety, the only hybrid variety authorised in a French PDO, bred since 1898 from noah (vitis labrusca x v.riparia) and folle blanche (v. Vinifera). The varietal compound of Baco blanc, eugenol has many original properties.

Volatile thiols contribute largely to the organoleptic characteristics and typicity of Sauvignon blanc wines. Among this family of odorous compounds, 3-sulfanylhexan-1-ol (3SH) and 4-methyl-4-sulfanylpentan-2-one (4MSP) have a major impact on wine flavor. These thiols are formed during alcoholic fermentation by the yeast from odorless and non-volatile precursors found in the berry and the must. The effect of vine nitrogen status on 3SH and 4MSP in Sauvignon blanc wine and on the glutathionylated and cysteinylated precursors of 3SH (Glut-3SH and Cys-3SH) was investigated in this study.

the phenological evolution is a crucial aspect of grapevine growth and development. Accurate detection of phenological stages can improve vineyard management, leading to better crop yield and quality traits. However, traditional methods of phenological tracking such as on-site observations are time-consuming and labour-intensive. This work proposes a scalable data-driven method to automatically detect key phenological stages of grapevines using satellite data. Our approach applies to vast areas because it solely relies on open and satellite data having global coverage without requiring any in-field data from weather stations or other sensors making the approach extensible to other areas.

Downy mildew, caused by Plasmopara viticola, is the most economically impactful disease affecting grapevines. This polycyclic pathogen triggers both primary and secondary infection cycles, resulting in significant yield losses when effective disease control measures are lacking. Over the winter, the pathogen survives by forming resting structures, the oospores, derived from sexual reproduction, which produce the inoculum for primary infections. To optimize grapevine downy mildew control and obtain the desired levels of production while minimizing chemical inputs, it is crucial to optimize the timeframe for fungicide application. Disease forecasting models are useful to identify the infection risk.