From genes to vineyards: system biology and new breeding technologies for water stress tolerance in grapevines

Through the years, extensive studies have been conducted on fungal biodiversity during the winemaking process: from the vineyard until aging.

An undesirable note called “floral taint” has been observed in red wines by winemakers in the Niagara region caused by large volumes of frozen leaves and petioles [materials-other-than-grapes (MOG)] introduced during mechanical harvest and subsequent winemaking late in the season. The volatiles, which we hypothesized are responsible, are primarily terpenes, norisoprenoids, and specific esters in frozen leaves and petioles. The purpose of this study was to investigate the volatile compounds which may cause the floral taint problem and explore how much of them (thresholds) may lead to the problem. Also, the glycosidic precursors of some of these compounds were analyzed to see the changes happening during frost events.

With the Federation of Wine Syndicates of Anjou and the Wine Syndicate of Angevin for direct sale to the Property, the Higher School of Agriculture of Angers was led to carry out, in 1995, a survey of winegrowers in Maine and Loire, with a view to grouping the supply of some of the wines intended for direct sale (Huet, 1995).

Accurate grape yield estimation is essential for effective vineyard management, crop planning, and resource allocation. Traditional methods often involve time-consuming and labour-intensive processes, which may introduce errors due to the large size and inherent spatial variability of the vineyard blocks.

Current environmental, ecological and economic issues require a better vineyard production management. In fact, a poor use of fertilizing could lead to harmful impact on environment. Another issue concerns the cultures themselves which couldn’t use fertilizers efficiently, leading to a loss of income or too much expense for farmers. Presently, estimation of fertilization’s needs is realized by the laboratory analysis of leaves selected through a random sampling. The present study aims at optimizing fertilization’s management by using a map of biophysical parameters estimated from satellite images.