Alternatives to copper-based treatments for the control of grapevine downy mildew (Plasmopara viticola): 5-year synthesis of trials in France and Italy

Summary in the original language of the document

The objective of the UE-funded program REPCO (FP6) was to identify new alternatives to copper fungicides in organic farming. Two pathogens have been considered: grapevine downy mildew (Plasmopara viticola) and apple scab (Venturia inaequalis). Research on grapevine was carried out by GRAB (Avignon, France) and FEM-IASMA (San Michele all’Adige, Italy). Trials were carried out under natural conditions in order to test reduced doses of copper and copper-free alternatives. Five-year trials proved that copper is the best fungicide. However, the use of new low copper rate formulations and the association of copper-free alternatives with reduced doses of copper or with reduced number of copper applications (limited to the most susceptible grapevine growth stages) were able to control of downy mildew with a concomitant reduced impact to the environment. Among the tested products, Trichodex (Trichoderma harzianum T39), Mycosin (clay), Chitoplant (chitosan), Saponin (Yucca extract), and an experimental sage extract (Salvia officinalis) gave the best results. The level of plant protection was similar to copper (standard), but not significantly different from the untreated control. Efficacy was good under low or medium disease pressure, but decreased when the pressure increased. The trials carried out after REPCO project confirmed that blossom stage is the most risky period for downy mildew infection and that a reduction of the number of treatments, with consequent reduction of the yearly total amount of copper, is possible by applying treatments during this period. These results show that more research efforts are needed to substitute copper in organic grape growing, and at present the practical approach must focus on combining strategies (alternative products and reduced copper, understanding the most susceptible stages of the plant, applying disease forecasting models, etc.).