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.

Botrytis leaf blight (BLB) of onion (Allium cepa) is caused by Botrytis squamosa. The disease has been reported on onion crops in several of the onion production areas of the world including North and South America, Europe, Asia, and Australia, although it is not a problem in arid production regions such as the western United States. In eastern Canada, the disease is generally present every year and is especially severe on cultivars of yellow globe onion. The pathogen biology and disease epidemiology have been intensively researched. Over the last few decades, in the organic soil area of Quebec, extensive research effort has been devoted to the development and evaluation of predictive models and disease management strategies. There has been an active integrated pest management program for onions since the early 1980s, and scouting for disease has played a major role in disease management. In this article, the story of BLB management in eastern Canada over a period of two decades is summarized.

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Botrytis leaf blight, caused by Botrytis squamosa, is a common and frequently damaging disease of onion crops, but the severity of epidemics varies widely from year to year. The disease is initiated and spread by airborne conidia. The relationship between airborne conidium concentration (ACC) and lesion development was studied in the field. A linear relationship was found between ACC and number of lesions per leaf: ACC values of 10 to 15 and 25 to 35 conidia m-3 were associated with 1 and 2.5 lesions per leaf, respectively. In 2000 and 2001, at three sites, four different criteria were used to start a fungicide spray program and their effect on epidemic development was compared with that of a grower's conventional schedule. The criteria were: at the fourth-true-leaf growth stage; according to an inoculum production index; when the ACC reached 10 to 15 conidia m-3; and when the ACC reached 25 to 35 conidia m-3. A nonsprayed control plot was included in the trial. Fungicide programs started when the ACC reached 10 to 15 conidia m-3 were as effective as the conventional program, but used fewer sprays. A fungicide spray program based on measurements of ACC and disease severity was evaluated in 2002 and 2003 in five and three commercial onion fields, respectively. At each site, half of the field was sprayed according to the grower's schedule and, in the other half, fungicide sprays were initiated when a threshold of 10 to 15 conidia m-3 or five lesions on the lower leaf (whichever came first) was reached. Overall, the number of fungicide applications was reduced by 75 and 56% in 2002 and 2003, respectively, without causing significant yield reduction. In both years, the reduction in number of fungicide applications was due mainly to the delay in initiation of the fungicide program.

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.

Carisse, O., Lefebvre, A., Van der Heyden, H., Roberge, L., and Brodeur, L. 2013. Analysis of incidence-severity relationships for strawberry powdery mildew as influenced by cultivar, cultivar type, and production systems. Plant Dis. 97:354-362.The relationships between strawberry powdery mildew incidence (I) and severity (S) were investigated for various cultivars, for Junebearing and day-neutral cultivars, and for production systems (openfield and plastic-tunnel) with the objective of deriving a simple relationship for predicting severity (proportion of leaf area diseased [PLAD]) from incidence (proportion of diseased leaves). Data were collected from 2006 to 2011 at II commercial and experimental sites, for a total of 2,326 observations {n). For the cultivars grown in open fields, higher severity was observed on 'Seascape', with mean PLAD of 0.299 {n = 427); followed by 'Chambly', with 0.133 {n = 334); 'Cavendish', with 0.115 {n = 250); 'Darselect', with 0.111 (n = 321); and 'Jewel', with 0.105 {n = 276). In general, mean severity was higher when the strawberry plants were grown in plastic tunnels, with PLAD of 0.204, 0.199, and 0.181 for Chambly (n = 204), Darselect (n = 261), and Jewel {n = 253), respectively. A linear model based on complementary log-log transformation of I and S provided a good fit of the data (coefficient of determination [R~] adjusted for degrees of freedom from 0.82 to 0.96).A covariance analysis indicated that the sampling year and site of sampling did not significantly influence the estimated slope of the I-S relationship, nor did the specific cultivar among the June-bearing ones, whereas the production system (open-field versus plastic-tunnel) and the cultivar type (June-bearing versus day-neutral) significantly influenced the estimated slope. From this analysis, we were able to develop three specific models for open-ficld-grown Junehearing cultivars {R-= 0.90), for the open-field-grown day-neutral cultivar (Seascape, R^ = 0.91), and for June-hearing cultivars grown in plastic tunnels (R-= 0.92). From these results, it was concluded that strawherry powdery mildew leaf severity can be accurately estimated from incidence of diseased leaves. The I-S relationships developed in the present study may be used in making practical disease management decisions, especially for management programs that use information on disease level in the field to initiate fungicide spraying programs or to time the interval between sprays.

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Van der Heyden, H., Lefebvre, M., Roberge, L., Brodeur, L., and Carisse, O. 2014. Spatial pattern of strawberry powdery mildew (Podosphaera aphanis) and airborne inoculum. Plant Dis. 98:43-54.The relationship between strawberry powdery mildew and airborne eonidium concentration (ACC) of Podosphaera aphanis was studied using data collected from 2006 to 2009 in 15 fields, and spatial pattern was described using 2 years of airborne inoculum and disease incidence data collected in fields planted with the June-bearing strawberry (Fragaria x ananassa) cultivar Jewel. Disease incidence, expressed as the proportion of diseased leaflets, and ACC were monitored in fields divided into 3x8 grids containing 24 100 m-quadrats. Variance-tomean ratio, index of dispersion, negative binomial distribution. Poisson distribution, and binomial and beta-binomial distributions were used to characterize the level of spatial heterogeneity. The relationship between percent leaf area diseased and daily ACC was linear, while the relationship between ACC and disease incidence followed an exponential growth curve. The V/M ratios were significantly greater than 1 for 100 and 96% of the sampling dates for ACC sampled at 0.35 m from the ground (ACCo 35^) and for ACC sampled at 1.0 m from the ground (ACCiom). respectively. For disease incidence, the index of dispersion D was significantly greater than 1 for 79% of the sampling dates. The negative binomial distribution fitted 86% of the data sets for both ACC| om and ACCoijn,. For disease incidence data, the beta-binomial distribution provided a good fit of 75% of the data sets.