Understanding and managing wine production from different terroirs

Aim: The study aims to show how different pedo-climatic conditions (past, present, and future) in three Italian sites at different latitudes (from center to southern), affect the adaptation of two red grapevine cultivars: Aglianico and Cabernet Sauvignon.

Esca, one of the main grapevine trunk diseases, is a complex and poorly understood disease. Phaeoacremonium minimum and Phaeomoniella chlamydospora, two of the main pathogens associated to this disease, are thought to be responsible for the first trunk infections. Little is known concerning grapevine trunk defenses during pathogen infection.

Grapevine cultivars are vegetatively propagated to preserve their varietal characteristics. However, spontaneous somatic variations that occur and are maintained during cycles of vegetative growth offer opportunities for the natural improvement of traditional grape cultivars. One advantageous trait for winegrowing is reduced bunch compactness, which decreases the susceptibility to pests and fungal diseases and favor an even berry ripening.

In this study we have compared the predictive ability of two phenological models: a traditional Thermal Time (TT) and a version of the more recently develop Unified Model (UM).

It is fundamental for wineries to know the potential yield of their vineyards as soon as possible for future planning of winery logistics. As such, non-invasive image-based methods are being investigated for early yield prediction. Many of these techniques have limitations that make it difficult to implement for practical use commercially. The aim of this study was to assess whether yield can be estimated using images taken in-field with a smartphone at different phenological stages. The accuracy of the method for predicting bunch weight at different phenological stages was assessed for seven different varieties.