Tasting soils in Pinot noir wines of the Willamette valley, Oregon

Rhone Valley A.O.C. Vineyards cover more than 70 000 hectares, of wich more than 40 000 plantedwith Grenache N. The Grenache observatory was created in 1995.

Stems may bring various benefits to the wine such as alcoholic reduction, color protection or improvement of the tannic intensity.

During the 1985 harvest, I was able to notice in the taste perception a break in the harmony of the wine during even partial blends of grapes from different plots. At the same time, I noted a good reaction from customers for greater product customization. As a result, I was led to seek the objective limits of the terroir of a cuvée and by a constant and permanent refinement of the parameters specific to each of the terroirs.

For characterization, sensory designing and authentication rapid analytical technologies have become available. Some, like Proton Transfer Reaction Mass Spectrometry allow a rapid spectrum of the volatile compounds of wines. Combined with chemometrics wines can be characterized. The same approach can be used to calculate the results of virtual mixtures and allow formulation of constant quality blends. Other new techniques and portable devices based on spectroscopy allow measurements on production sites and in grocery stores, even for the smart consumer. We will present some examples of the application of these techniques for authentication of wines, both in the laboratory and on site.

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.