Postharvest ozone treatment in grapevine white cultivars: Effects on grape volatile composition

The conventional wisdom of vintners is that alkalinity, and thus less sour and more rounded taste, are enhanced in wine and grapes challenged by low-nutrient soils.

In Chile there is a dry farming area known as a traditional wine region, where varieties brought by the Spanish conquerors still persist. These varieties, in general, are cultivated under traditional systems, with low use of technical and economic resources, and low profitability for their grapes and wines. In this region, as in other wine grape growing areas, climatic conditions have changed significantly in recent decades. In particular, the occurrence of spring frosts, when bud break has already begun, have generated significant losses for these growers.

Biomass accumulation in yeast has been studied in this work in terms of their role in fermentation processes. So, biotin is involved in many reactions and nitrogen metabolism disorders

The quality of grapevines measured by yield and must density in the northern part of Europe conditons can be characterized as a type of “cool climate” – vary strongly from year to year and from one production site to another. One hundred year observations in Johannisberg from 1890 to 1991 demonstrate for the yield formation a clear dependancy from the year combined with a steady increase in productivity; latter a proof of positive clonal selection efforts.

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.