The assessment of physiological parameters in vineyards can be done by direct measurements or by remote, indirect methods. The latter option frequently yields useful data, and development of methods and techniques that make them possible is worthwhile. One of the parameters most looked for to define the quality status of a vineyard is the degree Brix of its grapes, a quantity usually determined by direct measurement.

Plasmopara viticola, the causal agent of downy mildew (DM), and Uncinula necator, the causal agent of powdery mildew (PM), are two of the main phytopathogenic microorganisms causing major economic losses in the primary sector, especially in the wine sector, by wilting bunches and leaves with a consequent decrease in the photosynthetic rate of the plant and in the annual yield. Currently, the most widespread methods for planning spraying are based on the 3-10 rule, which states that the first application should take place when: (i) the air temperature is greater than 10°C; (ii) shoots are equal or greater than 10 cm; and (iii) a minimum of 10 mm rainfall within 24–48 hours has occurred, or at the beginning of the bud break with periodic applications according to the manufacturer’s instructions.

Water scarcity, high air temperatures, high vapor pressure deficit, and increasing frequency and intensity of extreme climatic events, namely heat waves, exert huge pressure on viticulture, as is the case of Mediterranean climates. Therefore, farmers rely more and more on irrigation to overcome these constraints. Deficit irrigation is a proved strategy to optimize irrigation efficiency and wine quality. The present study intends to demonstrate the application of precision techniques, namely remote sensing derived vegetation indices (VI) and an open source software, SIMDualKc, to compute crop evapotranspiration using the dual crop coefficient approach (Kcb + Ke), for deficit irrigation management.

the phenological evolution is a crucial aspect of grapevine growth and development. Accurate detection of phenological stages can improve vineyard management, leading to better crop yield and quality traits. However, traditional methods of phenological tracking such as on-site observations are time-consuming and labour-intensive. This work proposes a scalable data-driven method to automatically detect key phenological stages of grapevines using satellite data. Our approach applies to vast areas because it solely relies on open and satellite data having global coverage without requiring any in-field data from weather stations or other sensors making the approach extensible to other areas.

Grapevine downy mildew is a disease of foliage caused by Oomycete Plasmopara viticola an endoparasite that develops inside grapevine organs and can infect virtually every green organ. Downy mildew is one of the most destructive diseases in wine-growing regions, drastically reducing yield and fruit quality. Traditional manual disease detection relies on farm experts. Human field scouting has been widely used for monitoring the disease progress, however, is costly, laborious, subjective, and often imprecise.

Vineyards face climate change, increasing temperatures, and drought affecting vine water status. Water deficit affects plant physiology and can ultimately decrease yield and grape quality when it is not well managed. Monitoring vine water status and irrigation can help growers better manage their vineyards.