The history of the first demarkated wine region of the world – the Tokaj wine region

In a long-term experiment carried out in Chinon vineyard (37, France) during 23 years, the effects of several organic amendments were studied on soil, vine, grapes and wine. Four main treatments were compared on a calcareous sandy soil: control without organic amendment, dry crushed pruning wood at 2.1.t-1.ha-1.year-1 (D1), cow manure at 10 t-1. ha-1.year-1 (D1) and cow manure applied at 20 t-1.ha-1.year-1 (D2). D1 levels were calculated to fill the annual humus losses by mineralization.

The mechanization of vineyard work originally led to a reduction in planting densities due to the lack of machinery adapted to the vineyard. The current availability of specific machinery makes it possible to establish higher planting densities. In this work, three planting densities (1.40×0.80 m, 1.80×1 m and 2.20×1.20 m, corresponding to 8928, 5555 and 3787 plants/ha respectively) were studied with four varieties autochthonous of Galicia (northwestern Spain): Albariño and Treixadura (white), Sousón and Mencía (red). The vines were trained in a vertical shoot positioning system using a single Royat cordon, and pruned to spurs with two buds each. Agronomic data (yield, pruning wood weight, Ravaz index) and oenological data in must were collected. The higher planting density (1.40×0.80 m) had no significant effect on grape yield per vine in white varieties, although production per hectare was much higher due to the greater number of plants. In red varieties, this planting density resulted in a significantly lower production per vine, compensated by the greater number of plants. In addition, it significantly reduced the Brix degree in the must of the Albariño, Treixadura and Sousón varieties, and increased the total acidity in the latter two and Mencía. It also caused an increase in extractable and total anthocyanins and IPT in red grapes. The effects of high planting density on grapes are of great interest for the adaptation of varieties in the context of climate change. In the future, it could be advisable to modify the limits imposed by the appellations of origin on the planting density of these varieties in order to obtain more balanced wines.

Certain yeast species belonging to the Pichia genus are known to form a distinctive film on grape must and wine. In a mixed-culture type fermentation, Pichia spp. (P. kluyveri in particular) are known to impart beneficial oenological attributes. In this study, we report on an easy isolation method of Pichia spp. from grape must by exploiting their film-forming capacity on media containing 10% ethanol. We isolated and identified two Pichia species, namely Pichia kudriavzevii and Pichia kluyveri, and subsequently co-inoculated them with Saccharomyces cerevisiae to ferment Gewürztraminer musts. Noteworthy differences included a significant increase in the 2-phenethyl acetate levels with the P. kluyveri co-fermentation and a general increase in ethyl esters with the P. kudriavzevii co-fermentation. Both Pichia co-inoculations yielded higher levels of glycerol in the final wines. Based on all the wine parameters we tested, the P. kluyveri strain that was isolated performed similarly to a commercial P. kluyveri strain.

Spatial climate data at a 1 km resolution has allowed for a comprehensive mapping and assessment of viticulture DOs regions in Portugal. Overall the 50 regions and sub-regions in Portugal range

Geospatial technologies have significant contribution to viticulture, especially in small-scale vineyards, which require precise management. Geospatial data collected by modern technologies, such as Unmanned Aerial Vehicle (UAV) and satellite imagery, can be processed by modern software and easily be stored and transferred to GIS environments, highlighting important information about the health of vine plants, the yield of grapes and the wine, especially in wine-making varieties. The identification of field variability is very important, particularly for the production of high quality wine. Modern geospatial data management technologies are used to achieve an easy and effortless localization of the fields’ variability.