Climatic indicators for crop infection risk: Application to climate change impacts on five major foliar fungal diseases in Northern France

Since weather has a major influence on the occurrence and development of crop diseases, valuable insight toward future agricultural planning emerges with assessment tools to evaluate fungal disease pressure and crop regional suitability under projected future climatic conditions. The aim of this study was to develop two climatic indicators, the average infection efficiency (AIE) and the number of infection days (NID), to quantify the potential effects of weather on the intensity and occurrence of pathogen infection. First, a simple and continuous infection function accounting for daily temperature and leaf wetness duration variations was implemented. The function was then parameterized from published data sets for five major contrasting fungal diseases affecting crops in Northern France: phoma of oilseed rape, late blight of potato, downy mildew of grape, leaf rust of wheat and net blotch of barley. Finally, AIE and NID were calculated for the recent past (1970-2000) and the future A1B climate scenario (2070-2100). An overall decrease in the risk of infection was shown for potato late blight and downy mildew of grapevine for all months during the period when the host plant is susceptible to infection. There were greater differences for the other three diseases, depending on the balance between warmer temperatures and lower humidity. The future climate would result in a later onset of disease and higher infection pressure in late autumn. In spring, for brown rust of wheat and net blotch of barley, the climatic risk for infection is expected to occur earlier but would result in lower infection pressure in May. These findings highlighted the need to use an infra-annual (monthly or seasonally) scale to achieve a relevant analysis of the impact of climate change on the infection risk. The described indicators can easily be adapted to other pathogens and may be useful for agricultural planning at the regional scale and in the medium term, when decision support tools are required to anticipate future trends and the associated risks of crop diseases. © 2014 Elsevier B.V.