Towards a relationship between institutional clonal selection, mass selection and private clonal selection of grapevine cultivars

Fungus-resistant grape varieties (frgv) are an important field of research in viticulture, as they represent a way of reducing the use of copper-containing pesticides and thus minimising the environmental impact. The literature suggests that resistant grape varieties are a promising solution to the problem of using copper-containing pesticides in viticulture and that their quality has improved in recent years. However, there are still challenges in the acceptance and dissemination of FRGV by wine producers and consumers.

The valorization of winemaking byproducts is subordinated to the knowledge of their chemical characteristics. This work concerned the determination of the polyphenolic profile and the dietary fiber content of skins and seeds from unfermented and fermented pomace of different cultivars (Moscato bianco, Cortese, Arneis, Pinot Noir, Barbera, Grignolino, Nebbiolo), sampled from some wineries in the Piedmont area (Italy) during the 2020 harvest.

Studies suggest that ethanol (EtOH), triggers plant adaptation to various stresses at low concentrations (10 µM to 10 mM).

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.

Grapevine nitrogen (N) monitoring is essential for efficient N management plans that optimize fruit yield and quality while reducing fertilizer costs and the risk of environmental contamination. Unlike traditional vegetative-tissue sampling methods, remote sensing technologies, including hyperspectral imaging, have the potential to allow monitoring of the N status of entire vineyards at a per-vine resolution. However, differential N partitioning, variable spectral properties, and complex canopy structures hinder the development of a robust N retrieval algorithm. The present study aimed to establish a solid understanding of vine spectroscopic response at leaf and canopy levels by evaluating the different nitrogen retrieval approaches, including the radiative transfer model.