Balearic varieties of grapevine: study of genetic variability in the response to water stress

Yield estimation is very important for the wine industry since provides useful information for vineyard and winery management. The early yield estimation of the grapevine provides information to winegrowers in making management decisions to achieve a better quantity and quality of grapes. In general, yield forecasts are based on destructive sampling of bunches and manual counting of berries per bunch and bunches per vine.

Agriculture, natural resource management and the production and sale of products such as wine are increasingly data-driven activities. Thus, the use of remote and proximal crop and soil sensors to aid management decisions is becoming commonplace and ‘Agtech’ is proliferating commercially; mapping, underpinned by geographical information systems and complex methods of spatial analysis, is widely used…

Volatile organic compounds (VOCs) are emitted by nearly all plant organs of the plants, including leaves. They play a key role in the communication with other organisms, therefore they are involved in plant defence against phytopathogens. In this study VOCs from grapevine leaves of two varieties of Vitis vinifera infected by Erysiphe necator were analysed. The varieties were selected based on their susceptibility to pathogen, Kishmish Vatkana has the Ren1 resistance gene and Zamarrica showed high susceptibility in previous trials.

The region with Origin Indication Vale dos Vinhedos (IPVV) is located in the cities of Bento Gonçalves, Garibaldi and Monte Belo do Sul. It was established in November 2002, through an act of Instituto Nacional de Propriedade Industrial, according to Resolução INPI Nº. 75, of 2000, and Law Nº. 9.279 of 1996. The changes on the grape growing and wine making in the last 15 years, with the expansion of grapevines Vitis viníferas cultivation, the installation of several modern family wine companies, making wine with competitive quality, among other aspects, have enabled the implementation of concepts of Geographical Indications.

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.