Soils and plant material in prestigious Bordeaux vineyards impacts on yield and quality

Aromas are one of the key points in food analysis since they are related to character, quality and consequently consumer acceptance. It is not different in the winery industry, where the aromatic profile is a combination of viticultural and oenological practices. Based on the development of more aromatic clones and on the potential to produce sparkling wines at Caldas, in the southern region of Minas Gerais (Brazil) (21°55´S and 46°23´W, altitude 1,100m), the aim of this work was the determination of volatile compounds in six different clones of Chardonnay grape berries to better understand which compounds add bouquet to the wine, and additionally comprehend the impacts of the edaphoclimatic and annual conditions on the improvement of grape-growing and winemaking practices.

The quality of a wine is largely related to the balance between its sourness, bitterness and sweetness. Recently, molecules coming from grapes have been showed to notably contribute to sweet taste of dry wines. To study the viticultural and oenological parameters likely to affect their concentration, their quantification appears of high interest and subsequently requires powerful analytical techniques. Therefore, a new method using liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) was developed and validated to quantify epi-DPA-3′-O-β-glucopyranoside acid (epi-DPA-G) and astilbin, sweet molecules identified in wine. Three gradients were tested on five different C18 columns (Hypersil Gold, HSS T3, BEH, Syncronis and Kinetex).

Context and purpose of the study. The seasons immediately following planting are key growth stages where young vines are particularly susceptible to various forms of damage.

The results of experimental studies of the method based on the usage of ethyl alcohol as an internal standard for the direct determination of volatile compounds in wines and others alcohol contained products are presented. The method was validated in terms of precision, accuracy, limits of detection and quantification (lod and loq), linearity, and robustness.

Aim: Pests have a high impact on yield and grape quality in viticulture. An objective and rapid detection of pests under field conditions is needed. New sensing technologies and artificial intelligence could be used for pests detection in digital viticulture. The aim of this work was to apply computer vision and deep learning techniques for automatic detection of spider mite symptoms in grapevine under field conditions.