Juvenile-to-adult vegetative phase transition in grapevine 

Recent developments in satellite technology have yielded a substantial volume of data, providing a foundation for various machine learning approaches. These applications, utilizing extensive datasets, offer valuable insights into Earth’s conditions. Examples include climate change analysis, risk and damage assessment, water quality evaluation, and crop monitoring. Our study focuses on exploiting satellite thermal and multispectral imaging, and vegetation indexes, such as NDVI, in conjunction with ground truth information about soil type, land usage (forest, urban, crop cultivation), and irrigation water sources in the Trentino region in North-East of Italy.

The past three decades of terrestrial remote sensing research have delivered unprecedented insights into our fundamental ability to detect, quantify, and differentiate plant disease (Gold 2021). However, much of our fundamental knowledge in this domain has come from studies in non-agricultural systems and until recently, most agricultural studies, when extant, have focused on tree crops where canopy closure and large plot and plant size facilitate stress detection at low spatial resolution. Recent engineering innovations and advancements in constellation architecture design have refined the accuracy and scalability of airborne and spaceborne sensing platforms, enabling us to monitor diverse specialty crops, including grapevine, planted in smaller, spatially varied fields.

Climate change is increasingly affecting wine production, leading to substantial variations in wine composition from one vintage to another.

The Valpolicella area (Veneto Region, Italy) is famous for its high quality wines: Amarone and Recioto, both obtained from partial post-harvest dehydrated red grapes. The main cultivars used for these wines are Corvina and Corvinone. In this Region hundreds of years ago a particular training system (Pergola, cordon/cane with horizontal shoot-positioning) was developed. In the last 20 years the Guyot have been introduced in the area; now Pergola and Guyot are equally widespread in the Valpolicella area. In two different environmental conditions (hill and floodplain) two vineyards, one for each type of training system, were studied along two years (2011-2012).

Context and purpose of the study ‐ The aim of this study is the examination of wines of 9 different clones of a Greek grape variety Xinomavro, (ΧE1, X19, X22, X28, ΧE2 X30, X31, X35, X36, X37), with regards to their phenolic and anthocyanin content and chemical composition.