New tool to evaluate color modifications during oxygen consumption in white and red wines

Botrytis cinerea, a well-known grapevine pathogen, has more than 1200 host plants causing grey rot in grapevine berries. However, it can also result in a desirable phenomenon called noble rot under specific microclimate conditions. An extraordinary demonstration of this natural process can be observed in the creation of aszú wines within Hungary’s Tokaj wine region. Beside B. cinerea other fungi and yeasts are involved in the secondary metabolic development of the grape berry which contributes to the sensory and analytical characterization of noble rot wines.

The ongoing climate change implies an increasing mean air temperature, which is signified by weather extremes or sudden changes between drought and local heavy rainfalls. These changing conditions are especially challenging for the established grapevine varieties growing under cool climate conditions due to an increased risk for fungal diseases like downy mildew (DM) and Botrytis bunch rot (BBR) as well as for grape sunburn. To meet that demand, the scope of most grapevine breeding programs is the selection of mildew fungus-resistant and climatic adapted grapevines with balanced, healthy yield and outstanding wine quality.

Volatile organic compounds (VOCs) are emitted by nearly all plant organs of the plants, including leaves. They play a key role in the communication with other organisms, therefore they are involved in plant defence against phytopathogens. In this study VOCs from grapevine leaves of two varieties of Vitis vinifera infected by Erysiphe necator were analysed. The varieties were selected based on their susceptibility to pathogen, Kishmish Vatkana has the Ren1 resistance gene and Zamarrica showed high susceptibility in previous trials.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

Deleterious mutations that severely reduce population fitness are rapidly removed from the gene pool by purifying selection. However, evolutionary drivers such as genetic drift brought about by demographic bottlenecks may comprise its efficacy by allowing deleterious mutations to accumulate, thereby limiting the adaptive potential of populations. Moreover, positive selection can hitchhike mildly deleterious mutations due to linkage caused by lack of recombination. Similarly, in the context of species domestication, artificial selection mimics these evolutionary processes, which can have undesirable consequences for production and resilience. In this study, we evaluated the extent of the accumulation of deleterious mutations and the magnitude of their effects (also known as genetic load) at the whole-genome scale for ca.