Aims: DOSAVIÑA® was developed with the aim of helping farmers to determine optimal volume rates for spray applications in vineyards. The final developed tool is a good example of bringing research to end users.
Aim: Pests have a high impact on yield and grape quality in viticulture. An objective and rapid detection of pests under field conditions is needed. New sensing technologies and artificial intelligence could be used for pests detection in digital viticulture. The aim of this work was to apply computer vision and deep learning techniques for automatic detection of spider mite symptoms in grapevine under field conditions.
Aim: Irrigated viticulture is expanding worldwide mainly as a short-term adaptation strategy to climate change. Plant-based methods are increasingly being used for irrigation scheduling in commercial vineyards. Canopy temperature (TC) has long been recognized as an indicator of plant water status. TC, but also the thermal stress indices, e.g. crop water stress index (CWSI) and stomatal
Aim: Downy mildew is a crucial disease in viticulture. In-field evaluation of downy mildew has been classically based on visual inspection of leaves and fruit. Nevertheless, non-invasive sensing technologies could be used for disease detection in grapevine. The aim of this study was to assess downy mildew severity in grapevine leaves using machine vision.