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Carisse O.,Agriculture and Agri Food Canada | Levasseur A.,Agriculture and Agri Food Canada | Van der Heyden H.,Compagnie de Recherche Phytodata Inc.
Plant Pathology | Year: 2012

Botrytis leaf blight (BLB) caused by Botrytis squamosa is a major leaf disease of onion. Various forecasting systems have been developed to help growers manage the disease. To improve forecasting reliability, the influence of temperature and wetness duration on B. squamosa infection was quantified by inoculating onion leaves with a conidial suspension and incubating them under various combinations of temperature (10-30°C) and leaf wetness duration (0-84h). Infection was measured as the number of lesions per cm 2 of leaf and converted to the proportion of maximum infection (PMI). Regardless of leaf wetness duration, only a few lesions developed at 30°C and the number of lesions increased as the temperature rose from 10 to 20°C but decreased at 25°C. Between 10 and 25°C the number of lesions per cm 2 of leaf area increased gradually with increasing leaf wetness duration from 12 to 72h. Relative infection was modelled as a function of both temperature and wetness duration using a modified version of the Weibull equation, which provided a precise description of the response of B. squamosa (R 2=0·88). To facilitate field validation, receiving operating characteristic curve analysis was performed to determine the accuracy of various sets of criteria for establishing the length of an infection event based on field weather data. The total number of leaf wetness and RH >90% hours over a 72h period was the best criterion, regardless of the wetness interruption pattern (sensitivity=90·91, specificity=84·62, area under the receiving operating curve=0·878). The model describing the relationship of PMI to temperature and leaf wetness duration, and field observations on airborne conidium concentration (ACC) were used to calculate the risk of infection (RI BLB) as RI BLB=PMI×ACC. In 2009 and 2010, this risk index was compared to the observed rate of BLB progress (Rate BLB+5days) during the following 5days. There was a linear relationship between RI BLB and Rate BLB+5days indicating that this new risk indicator was reliable for predicting the risk of BLB development. These findings will help to improve the timing of fungicide applications for BLB management. © 2012 The Authors. Plant Pathology © 2012 BSPP.


Carisse O.,Agriculture and Agri Food Canada | Lefebvre A.,Agriculture and Agri Food Canada | Van der Heyden H.,Compagnie de recherche Phytodata Inc. | Roberge L.,Compagnie de recherche Phytodata Inc. | Brodeur L.,Compagnie de recherche Phytodata Inc.
Plant Disease | Year: 2013

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 11 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 [R2] 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-field-grown Junebearing cultivars (R2 = 0.90), for the open-field-grown day-neutral cultivar (Seascape, R2 = 0.91), and for June-bearing cultivars grown in plastic tunnels (R2 = 0.92). From these results, it was concluded that strawberry 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.


Fall M.L.,Université de Sherbrooke | Van der Heyden H.,Compagnie de recherche Phytodata Inc. | Brodeur L.,Compagnie de recherche Phytodata Inc. | Leclerc Y.,McCain Foods Ltd. | And 2 more authors.
Plant Pathology | Year: 2015

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. © 2014 British Society for Plant Pathology.


Van Der Heyden H.,McGill University | Van Der Heyden H.,Compagnie de Recherche Phytodata Inc. | Van Der Heyden H.,Agriculture and Agri Food Canada | Dutilleul P.,McGill University | And 2 more authors.
Phytopathology | Year: 2014

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.,Agriculture and Agri Food Canada | Van Der Heyden H.,Compagnie de recherche Phytodata Inc
Plant Disease | Year: 2015

Gray mold, caused by Botrytis cinerea, is an important threat for tomato greenhouse producers. The influence of airborne conidia concentration (ACC) on both flower and stem-wound infections was studied in a greenhouse maintained at a temperature of 15, 20, or 25°C using diseased tomato leaves as the unique source of dry inoculum. Spore samplers were used to monitor ACC, and a previously developed real-time qPCR assay was used to quantify airborne B. cinerea conidia. The proportion of infected flowers remained low at ACC < 10 conidia/m3; above this concentration, flower infection increased with increasing ACC. The influence of ACC on proportion of infected flowers was well described by a sigmoid model (R2 = 0.90 to 0.92). The mean proportion of infected stem wounds over the three trials was 0.021; no infected wounds were observed at ACC < 100 conidia/m3. Based on logistic regression, the probability that a stem becomes infected increased rapidly with mean probabilities of 0.24 and 0.87 at ACCs of 315 and 3,161 conidia/m3, respectively. The results suggest that the amount of airborne B. cinerea inoculum in the greenhouse is often above the action threshold for flower infection and that monitoring airborne B. cinerea inoculum could help in timing de-leafing operations. © 2015 The American Phytopathological Society.


Van der Heyden H.,Compagnie de Recherche Phytodata inc | Lefebvre M.,Compagnie de Recherche Phytodata inc | Roberge L.,Compagnie de Recherche Phytodata inc | Brodeur L.,Compagnie de Recherche Phytodata inc | Carisse O.,Agriculture and Agri Food Canada
Plant Disease | Year: 2014

The relationship between strawberry powdery mildew and airborne conidium 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 × ananassa) cultivar Jewel. Disease incidence, expressed as the proportion of diseased leaflets, and ACC were monitored in fields divided into 3 × 8 grids containing 24 100 m2 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 (ACC0.35m) and for ACC sampled at 1.0 m from the ground (ACC1.0m), 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 ACC1.0m and ACC0.35m. For disease incidence data, the beta-binomial distribution provided a good fit of 75% of the data sets. Taylor's power law indicated that, for ACC at both sampling heights, heterogeneity increased with increasing mean ACC, whereas the binary form of the power law suggested that heterogeneity was not dependent on the mean for disease incidence. When the spatial location of each sampling location was taken into account, Spatial Analysis by Distance Indices showed low aggregation indices for both ACCs and disease incidence, and weak association between ACC and disease incidence. Based on these analyses, it was found that the distribution of strawberry powdery mildew was weakly aggregated. Although a higher level of heterogeneity was observed for airborne inoculum, the heterogeneity was low with no distinct foci, suggesting that epidemics are induced by well-distributed inoculum. This low level of heterogeneity allows mean airborne inoculum concentration to be estimated using only one sampler per field with an overall accuracy of at least 0.841. The results obtained in this study could be used to develop a sampling scheme that will improve strawberry powdery mildew risk estimation. © 2014 Department of Agriculture and Agri-Food, Government of Canada.


Fall M.L.,Université de Sherbrooke | Fall M.L.,Compagnie de Recherche Phytodata inc. | Van Der Heyden H.,Compagnie de Recherche Phytodata inc. | Carisse O.,Agriculture and Agri Food Canada
PLoS ONE | Year: 2016

Lettuce downy mildew, caused by the oomycete Bremia lactucae Regel, is a major threat to lettuce production worldwide. Lettuce downy mildew is a polycyclic disease driven by airborne spores. A weather-based dynamic simulation model for B. lactucae airborne spores was developed to simulate the aerobiological characteristics of the pathogen. The model was built using the STELLA platform by following the system dynamics methodology. The model was developed using published equations describing disease subprocesses (e.g., sporulation) and assembled knowledge of the interactions among pathogen, host, and weather. The model was evaluated with four years of independent data by comparing model simulations with observations of hourly and daily airborne spore concentrations. The results show an accurate simulation of the trend and shape of B. lactucae temporal dynamics of airborne spore concentration. The model simulated hourly and daily peaks in airborne spore concentrations. More than 95% of the simulation runs, the daily-simulated airborne conidia concentration was 0 when airborne conidia were not observed. Also, the relationship between the simulated and the observed airborne spores was linear. In more than 94% of the simulation runs, the proportion of the linear variation in the hourly-observed values explained by the variation in the hourly-simulated values was greater than 0.7 in all years except one. Most of the errors came from the deviation from the 1:1 line, and the proportion of errors due to the model bias was low. This model is the only dynamic model developed to mimic the dynamics of airborne inoculum and represents an initial step towards improved lettuce downy mildew understanding, forecasting and management. ©2016 Fall et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Carisse O.,Agriculture and Agri Food Canada | Morissette-Thomas V.,Université de Sherbrooke | Van Der Heyden H.,Compagnie de recherche Phytodata Inc.
Phytopathology | Year: 2013

Knowledge about epidemiology and the impact of disease on yield is fundamental for establishing effective management strategies. The purpose of this study was to investigate the relationship between foliar strawberry mildew severity, Podosphaera aphanis airborne inoculum concentration, weather, and subsequent crop losses for day-neutral strawberry. The experiment was conducted at three, five, and four sites in 2006, 2007, and 2008, respectively, for a total of 12 epidemics. At each site, data were collected on 25 plants at 2-day intervals from the end of May to early October for a total of 60 to 62 samplings annually. First, seasonal crop losses were statistically described; then, a lagged regression model was developed to describe crop losses from the parameters that were significantly associated with losses. There was a strong positive linear relationship between seasonal crop losses and the area under the leaf disease progress curve (R2 = 0.90) and daily mean airborne conidia concentration (R2 = 0.86), and a negative linear relationship between crop losses and time to 5% loss (R2 = 0.76) and time to 5% leaf area diseased (R2 = 0.61). Among the 53 monitoring- and weather-based variables analyzed, percent leaf area diseased, log 10-transformed airborne inoculum concentration, and weather variables related to temperature were significantly associated with crop losses. However, polynomial distributed lag regression models built with weather variables were not accurate in predicting losses, with the exception of a model based on a combined temperature and humidity variable, which provided accurate prediction of the data used to construct the model but not of independent data. Overall, the model based on log10- transformed airborne inoculum concentration did not provide accurate crop loss predictions. The model built using percent leaf area diseased with a time lag of 8 days (n = 4) and a polynomial degree of 2 provided a good description of the crop-loss data used to construct the model (r = 0.99 and 0.90) and of independent data (r = 0.92). For the 12 epidemics studied, 5% crop loss was reached when an average of 17% leaf area diseased was observed since the beginning of symptom development. These results indicate that information on foliar powdery mildew must be considered when making strawberry powdery mildew management decisions. © 2013 The American Phytopathological Society.


Van der Heyden H.,Compagnie de recherche Phytodata Inc. | Carisse O.,Agriculture and Agri Food Canada | Brodeur L.,Compagnie de recherche Phytodata Inc.
Crop Protection | Year: 2012

Botrytis leaf blight (BLB) of onion is a well-documented disease and several management tools are available. However, achieving good control with minimum use of fungicides is time consuming and requires dedication on the part of growers. In this study, three indicators for the initiation of fungicide spray programs were compared. The study was conducted in 2008, 2009 and 2010 at commercial onion farms located in the muck soil area southwest of Montreal. The indicators evaluated were: 1) first airborne Botrytis squamosa conidia detected; 2) cumulative airborne conidium concentration (ACC) of 15conidiam -3; 3) first lesion caused by B. squamosa detected. The interval between subsequent fungicide applications was determined by taking into account sporulation potential, airborne conidium concentration and lesion density. Reliability of the indicators was evaluated on the basis of observed maximum disease level, area under the disease progress curve and rate of disease progress. Initiation of the fungicide spray program when the first airborne B. squamosa conidia were detected resulted in the lowest values for maximum disease level and area under the disease progress curve, followed by initiation when a cumulative concentration of 15conidiam -3 was reached, and by initiation when the first lesion was detected. However, there was no significant difference in rate of disease progress, calculated using data from fields where spray programs were initiated based on the different indicators. The critical disease level for curative fungicide applications (ten lesions per leaf) was not reached when the spray program was initiated upon detection of the first conidia; was reached a few days after bulb initiation for a spray program initiated at a cumulative ACC of 15conidiam -3; and was reached prior to bulb initiation for the spray program initiated when the first lesion was detected. These results suggest that to avoid yield reduction, BLB should be managed such that the disease does not reach the exponential phase. This was achieved by initiating the fungicide spray program based on first conidia detected. © 2011.


PubMed | Compagnie de Recherche Phytodata Inc., Université de Sherbrooke and Agriculture and Agri Food Canada
Type: Journal Article | Journal: Pest management science | Year: 2016

The genetic underlying resistance mechanisms in the population of the phytopathogenic fungus Botrytis cinerea are well documented. Specifically, several genetic substitutions associated with succinate dehydrogenase inhibitor (SDHI)-based fungicide resistance have been identified in the succinate dehydrogenase gene. The objective of the present work was to develop a molecular tool for accurate quantification of these genetic substitutions within Botrytis populations. A test using the PyroMark Q24 instrument was designed to detect and quantify five genetic substitutions associated with SDHI resistance.The technique is based on sequencing by synthesis, and it generated quantitative and accurate data with a limit of quantification of a minimum of 500 spores. There was a linear relationship between the known and estimated percentages of spores with the targeted genetic substitutions and wild-type strains at ratios of 0-100%, with a 20% increment.With the pyrosequencing assay developed in this study, a large number of Botrytis spp. individuals can be characterised in a timely fashion with greater accuracy than by commonly used methods. Hence, pyrosequencing-based methods will be useful for improving our understanding of fungicide resistance, detecting the arrival of new genetic substitutions, monitoring shifts in fungal populations and assessing the effectiveness of antiresistance strategies, and for routine monitoring of fungicide resistance.

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