This study investigated the value of using real-time monitoring of Phytophthora infestans airborne inoculum as a complement to decision support systems (DSS). The experiment was conducted during the 2010, 2011 and 2012 potato production seasons in two locations in New Brunswick, Canada. Airborne sporangia concentrations (ASC) of P. infestans were monitored using 16 rotating-arm spore samplers placed 3 m above the ground. The first cases of late blight (2010 and 2011) were detected 6-7 days after the first ASC peak, and all samplers captured their first sporangia within the same week (at 3-and 9-day periods). The cumulative ASC curve and the risk curves from two DSS (PLANT-Plus and Pameseb Late Blight) had the same shape but different magnitudes. In both locations, the negative binomial distribution fitted the data better than the Poisson distribution, which is indicative of heterogeneity, and based on Taylor's power law, the heterogeneity increased with increasing ASC. Therefore, the present results suggest that spore-sampling network devices may be a suitable approach for early detection of incoming inoculum and, when combined with DSS, represent a potential aid for targeting the optimal time to apply a disease-control product. In this context, cumulative ASC can be a counterweight to the DSS risk estimate: a high risk combined with significant ASC will trigger fungicide spraying. Moreover, spore sampling can be used to assess the efficiency of management strategies by means of examining the area under the inoculum progress curve.

Real-time loop-mediated isothermal amplification (LAMP) and recombinase polymerase amplification (RPA) assays were developed targeting the internal transcribed spacer 2 region of the ribosomal DNA of Phytophthora infestans, the potato late blight causal agent. A rapid crude plant extract (CPE) preparation method from infected potato leaves was developed for on-site testing. The assay’s specificity was tested using several species of Phytophthora and other potato fungal and oomycete pathogens. Both LAMP and RPA assays showed specificity to P. infestans but also to the closely related species P. andina, P. mirabilis, P. phaseoli, and P. ipomoeae, although the latter are not reported as potato pathogen species. No cross-reaction occurred with P. capsici or with the potato pathogens tested, including P. nicotianae and P. erythroseptica. The sensitivity was determined using P. infestans pure genomic DNA added into healthy CPE samples. Both LAMP and RPA assays detected DNA at 50 fg/μl and were insensitive to CPE inhibition. The isothermal assays were tested with artificially inoculated and naturally infected potato plants using a Smart-DART platform. The LAMP assay effectively detected P. infestans in symptomless potato leaves as soon as 24 h postinoculation. A rapid and accurate on-site detection of P. infestans in plant material using the LAMP assay will contribute to improved late blight diagnosis and early detection of infections and facilitate prompt management decisions.

Spatial distribution of single-nucleotide polymorphisms (SNPs) related to fungicide resistance was studied for Botrytis cinerea populations in vineyards and for B. squamosa populations in onion fields. Heterogeneity in this distribution was characterized by performing geostatistical analyses based on semivariograms and through the fitting of discrete probability distributions. Two SNPs known to be responsible for boscalid resistance (H272R and H272Y), both located on the B subunit of the succinate dehydrogenase gene, and one SNP known to be responsible for dicarboximide resistance (I365S) were chosen for B. cinerea in grape. For B. squamosa in onion, one SNP responsible for dicarboximide resistance (I365S homologous) was chosen. One onion field was sampled in 2009 and another one was sampled in 2010 for B. squamosa, and two vineyards were sampled in 2011 for B. cinerea, for a total of four sampled sites. Cluster sampling was carried on a 10-by-10 grid, each of the 100 nodes being the center of a 10-by-10-m quadrat. In each quadrat, 10 samples were collected and analyzed by restriction fragment length polymorphism polymerase chain reaction (PCR) or allele specific PCR. Mean SNP incidence varied from 16 to 68%, with an overall mean incidence of 43%. In the geostatistical analyses, omnidirectional variograms showed spatial autocorrelation characterized by ranges of 21 to 1 m. Various levels of anisotropy were detected, however, with variograms computed in four directions (at 0°, 45°, 90°, and 135° from the within-row direction used as reference), indicating that spatial autocorrelation was prevalent or characterized by a longer range in one direction. For all eight data sets, the β-binomial distribution was found to fit the data better than the binomial distribution. This indicates local aggregation of fungicide resistance among sampling units, as supported by estimates of the parameter θ of the β-binomial distribution of 0.09 to 0.23 (overall median value = 0.20). On the basis of the observed spatial distribution patterns of SNP incidence, sampling curves were computed for different levels of reliability, emphasizing the importance of sample size for the detection of mutation incidence below the risk threshold for control failure.

Onion downy mildew (ODM) caused by Peronospora destructor has been increasing annually in south-western Québec since the early 2000s, reaching 33% of affected onion fields in 2014. Using observational data collected over a period of 31 consecutive years, this study aimed to investigate the variations in ODM incidence and epidemic onset and identify the meteorological variables that influence its polyetic development. A logistic model was fitted to each ODM epidemic to estimate and compare the onset of epidemics on a regional basis. Results of this analysis showed that the first observation date, 10% epidemic onset (b10) and mid-time (b) were, on average, 30.4, 15.1 and 11.3 days earlier in 2007–2017 than in 1987–1996. Results of a principal component analysis suggested that regional disease incidence was mostly influenced by the precipitation regime, the final regional disease incidence the previous year, and warmer temperature during the harvest period the previous fall. Subsequently, the data were divided in three periods of 10, 10 and 11 years, and a discriminant analysis was performed to classify each year in the correct period. Using a sufficient subset of five discriminating variables (temperature and rainfall at harvest the previous fall, winter coldness, solar radiation, and disease incidence the previous year), it was possible to classify 93.5% of the ODM epidemics in the period where they belong. These results suggest that P. destructor may overwinter under northern latitudes and help to highlight the need for more research on overwintering and for the development of molecular-based tools enabling the monitoring of initial and secondary inoculum.