Mandipropamid is an active ingredient in the carboxylic acid amide group of fungicides and plays a key role in current potato late blight ( Phytophthora infestans ) management programmes. However, reports from Danish potato growers in 2022 suggested that mandipropamid had lost its efficacy. A study was therefore conducted to investigate the sensitivity of isolates collected from fields in which mandipropamid had been reported to be ineffective. Seventy‐two isolates of P . infestans collected from potato fields in Denmark were genotyped using microsatellite markers, revealing a dominance of the clonal lineage EU43 and fewer isolates of EU41 and ‘other’ genetically distinct genotypes. Isolates belonging to the EU43 and EU41 lineages were selected, in addition to representative isolates of clones EU36 and EU37 from Scotland, and tested for sensitivity to mandipropamid at five concentrations ranging from 0.1 to 10 μg/mL on potato leaf discs (cultivar Maris Piper). The EU43 genotype infected leaf discs at all tested concentrations, and therefore no dose–response curve could be calculated. A dose response was observed for isolates of genotypes EU36, EU37 and EU41 with EC ₅₀ values ranging from 0.35 to 0.75 μg/mL. Field experiments confirmed resistance of tested isolates of genotype EU43 to mandipropamid, with no significant difference in the area under the disease curve between the untreated and mandipropamid treatments. Analysis of the Danish population of P . infestans showed that EU43 was widely distributed across the country. To our best knowledge, this is the first report of resistance to mandipropamid in P . infestans .

Until recently, genotypes of Phytophthora infestans were regionally distributed in Europe, with populations in western Europe being dominated by clonal lineages and those in northern Europe being genetically diverse because of frequent sexual reproduction. However, since 2013 a new clonal lineage (EU_41_A2) has successfully established itself and expanded in the sexually recombining P. infestans populations of northern Europe. The objective of this study was to study phenotypic traits of the new clonal lineage of P. infestans, which may explain its successful establishment and expansion within sexually recombining populations. Fungicide sensitivity, aggressiveness, and virulence profiles of isolates of EU_41_A2 were analyzed and compared with those of the local sexual populations from Denmark, Norway, and Estonia. None of the phenotypic data obtained from the isolates collected from Denmark, Estonia, and Norway independently explained the invasive success of EU_41_A2 within sexual Nordic populations. Therefore, we hypothesize that the expansion of this new genotype could result from a combination of fitness traits and more favorable environmental conditions that have emerged in response to climate change.

In recent years, early blight epidemics have been frequently causing important yield loses in potato crop. This fungal disease develops quickly when weather conditions are favorable, forcing the use of fungicides by farmers. A Limia is one of the largest areas for potato production in Spain. Usually, early blight epidemics are controlled using pre-established schedule calendars. This strategy is expensive and can affect the environment of agricultural areas. Decision support systems are not currently in place to be used by farmers for managing early blight. Thus, the objective of this research was to evaluate different early blight forecasting models based on plant or/and pathogen requirements and weather conditions to check their suitability for predicting the first symptoms of early blight, which is necessary to determine the timings of the first fungicide application. For this, weather, phenology and symptomatology of disease were monitored throughout five crop seasons. The first early blight symptoms appeared starting the flowering stage, between 37 and 40 days after emergence of plants. The forecasting models that were based on plants offered the best results. Specifically, the Wang-Engel model, with 1.4 risk units and Growing Degree-Days (361 cumulative units) offeredthe best prediction. The pathogen-based models showed a conservative forecast, whereas the models that integrated both plant and pathogen features forecasted the first early blight attack markedly later.