Using open source software in viticultural research

A study of « terroirs » was achieved from 2003 to 2005 in the whole vineyard of the Ré island (17, France). Over more than 1,990 ha, a cartography at the 1/10.000 scale, including characterization of climatic, pedological, geological and hydrogeological components of « Basic Terroir Units » (B.T.U.) was made. Also, a survey among wine growers was conducted. All data were treated together in a G.I.S. connected to a data base. 22 kinds of map were built (B.T.U. and components, soil water reserve, vine functioning potentials, varieties, rootstocks, viticultural practices and soil management).

Pour prévoir et gérer chaque année les principales caractéristiques de la maturation en Champagne, le CIVC (Comité Interprofessionnel du Vin de Champagne) a développé un ensemble de moyens de prévision et d’information très performants qui permettent aux différents acteurs de la filière viti-vinicole de prendre en compte ces informations à l’échelle de chaque terroir communal pour la recherche d’une qualité optimale.

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. 

Climate change is having a profound effect on viticulture by altering the conditions under which vines grow, leading to increased water stress and earlier harvests, which in turn affect the quality and character of wines [1].

Accumulation of anthocyanins (Anth) on whole winegrape (Vitis vinifera L.) bunches attached to the vine was monitored by a fluorescence-based sensor (Multiplex) on ‘Aleatico’ and ‘Nero d’Avola’. Different water regimes were applied.