Using wheat cultivar mixtures as a control method against septoria tritici blotch: experimental and modeling approaches. Gigot, C., Saint-Jean, S., Huber, L., Maumené, C., Leconte, M., & de Vallavieille-Pope, C. In pages 1, Minneapolis, Minnesota, USA, August, 2014. bibtex: Gigot:14aabstract bibtex Septoria tritici blotch, caused by the fungus Mycosphaerella graminicola, is the predominant foliar rain-borne disease on wheat crops, and it is regularly responsible for substantial yield losses (up to 40%). In the agricultural context of input reduction, cultivar mixtures have been shown as a way of controlling wind-borne fungal diseases, and they are already used at large scale in some countries. The relevancy of such plant diversity within crops to reduce epidemics of rain-borne diseases has to be assessed. To characterize the impacts of natural septoria tritici blotch epidemics in a fungicide-free cultivar mixture, field experiments were conducted from 2008 to 2011. The mixture consisted of two wheat cultivars with contrasted resistance to M. graminicola, in a 1:3 susceptible:moderately high resistant ratio. Weekly assessments of the number of sporulating lesions, pycnidial leaf area and green leaf area were done on the same stems, for each level of still green leaves. After the major rain dispersal event of each spring, the number of sporulating lesions on the susceptible cultivar was reduced on average by 47% within the mixture compared to the pure stand. All the measurements achieved corroborated that, on one hand, the susceptible component was always less diseased in the mixture than in the pure stand (on average, 42% less leaf area covered with pycnidia on the three upper leaves), and, on the other hand, the resistant component was not significantly more affected by septoria tritici blotch within the mixture. Complementary to the field experiments, a theoretical approach, based on the development of a mechanistic-stochastic model, aims to describe the progression of septoria tritici blotch within a heterogeneous 3D-canopy. This model includes both physical and epidemiological approaches. Firstly, a raindrop size distribution, which describes a rainfall event, is sampled based on numerical integration techniques that rely on Monte Carlo methods. Then, for the raindrops that impact on the virtual canopy, splash droplets are generated based on raindrop and plant surface properties. The trajectory of each droplet and the interception by a plant or by the ground are computed. From this set of trajectories, the potential progression pattern of septoria tritici blotch is assessed on the whole canopy, taking into account cultivar resistance levels of the intercepted surfaces. The polycyclic nature of epidemics is modeled by iterating the previous calculations. The results of the modeling approach will be compared to the experimental ones in order to identify which processes are involved in the reduction of splash-dispersed disease severity within wheat cultivar mixtures.
@inproceedings{gigot_using_2014,
address = {Minneapolis, Minnesota, USA},
title = {Using wheat cultivar mixtures as a control method against septoria tritici blotch: experimental and modeling approaches},
abstract = {Septoria tritici blotch, caused by the fungus Mycosphaerella graminicola, is the predominant foliar rain-borne disease on wheat crops, and it is regularly responsible for substantial yield losses (up to 40\%). In the agricultural context of input reduction, cultivar mixtures have been shown as a way of controlling wind-borne fungal diseases, and they are already used at large scale in some countries. The relevancy of such plant diversity within crops to reduce epidemics of rain-borne diseases has to be assessed. To characterize the impacts of natural septoria tritici blotch epidemics in a fungicide-free cultivar mixture, field experiments were conducted from 2008 to 2011. The mixture consisted of two wheat cultivars with contrasted resistance to M. graminicola, in a 1:3 susceptible:moderately high resistant ratio. Weekly assessments of the number of sporulating lesions, pycnidial leaf area and green leaf area were done on the same stems, for each level of still green leaves. After the major rain dispersal event of each spring, the number of sporulating lesions on the susceptible cultivar was reduced on average by 47\% within the mixture compared to the pure stand. All the measurements achieved corroborated that, on one hand, the susceptible component was always less diseased in the mixture than in the pure stand (on average, 42\% less leaf area covered with pycnidia on the three upper leaves), and, on the other hand, the resistant component was not significantly more affected by septoria tritici blotch within the mixture. Complementary to the field experiments, a theoretical approach, based on the development of a mechanistic-stochastic model, aims to describe the progression of septoria tritici blotch within a heterogeneous 3D-canopy. This model includes both physical and epidemiological approaches. Firstly, a raindrop size distribution, which describes a rainfall event, is sampled based on numerical integration techniques that rely on Monte Carlo methods. Then, for the raindrops that impact on the virtual canopy, splash droplets are generated based on raindrop and plant surface properties. The trajectory of each droplet and the interception by a plant or by the ground are computed. From this set of trajectories, the potential progression pattern of septoria tritici blotch is assessed on the whole canopy, taking into account cultivar resistance levels of the intercepted surfaces. The polycyclic nature of epidemics is modeled by iterating the previous calculations. The results of the modeling approach will be compared to the experimental ones in order to identify which processes are involved in the reduction of splash-dispersed disease severity within wheat cultivar mixtures.},
author = {Gigot, C. and Saint-Jean, S. and Huber, L. and Maumené, C. and Leconte, M. and de Vallavieille-Pope, C.},
month = aug,
year = {2014},
note = {bibtex: Gigot:14a},
keywords = {Acte, Poster},
pages = {1}
}
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In the agricultural context of input reduction, cultivar mixtures have been shown as a way of controlling wind-borne fungal diseases, and they are already used at large scale in some countries. The relevancy of such plant diversity within crops to reduce epidemics of rain-borne diseases has to be assessed. To characterize the impacts of natural septoria tritici blotch epidemics in a fungicide-free cultivar mixture, field experiments were conducted from 2008 to 2011. The mixture consisted of two wheat cultivars with contrasted resistance to M. graminicola, in a 1:3 susceptible:moderately high resistant ratio. Weekly assessments of the number of sporulating lesions, pycnidial leaf area and green leaf area were done on the same stems, for each level of still green leaves. After the major rain dispersal event of each spring, the number of sporulating lesions on the susceptible cultivar was reduced on average by 47% within the mixture compared to the pure stand. All the measurements achieved corroborated that, on one hand, the susceptible component was always less diseased in the mixture than in the pure stand (on average, 42% less leaf area covered with pycnidia on the three upper leaves), and, on the other hand, the resistant component was not significantly more affected by septoria tritici blotch within the mixture. Complementary to the field experiments, a theoretical approach, based on the development of a mechanistic-stochastic model, aims to describe the progression of septoria tritici blotch within a heterogeneous 3D-canopy. This model includes both physical and epidemiological approaches. Firstly, a raindrop size distribution, which describes a rainfall event, is sampled based on numerical integration techniques that rely on Monte Carlo methods. Then, for the raindrops that impact on the virtual canopy, splash droplets are generated based on raindrop and plant surface properties. The trajectory of each droplet and the interception by a plant or by the ground are computed. From this set of trajectories, the potential progression pattern of septoria tritici blotch is assessed on the whole canopy, taking into account cultivar resistance levels of the intercepted surfaces. The polycyclic nature of epidemics is modeled by iterating the previous calculations. 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In the agricultural context of input reduction, cultivar mixtures have been shown as a way of controlling wind-borne fungal diseases, and they are already used at large scale in some countries. The relevancy of such plant diversity within crops to reduce epidemics of rain-borne diseases has to be assessed. To characterize the impacts of natural septoria tritici blotch epidemics in a fungicide-free cultivar mixture, field experiments were conducted from 2008 to 2011. The mixture consisted of two wheat cultivars with contrasted resistance to M. graminicola, in a 1:3 susceptible:moderately high resistant ratio. Weekly assessments of the number of sporulating lesions, pycnidial leaf area and green leaf area were done on the same stems, for each level of still green leaves. After the major rain dispersal event of each spring, the number of sporulating lesions on the susceptible cultivar was reduced on average by 47\\% within the mixture compared to the pure stand. All the measurements achieved corroborated that, on one hand, the susceptible component was always less diseased in the mixture than in the pure stand (on average, 42\\% less leaf area covered with pycnidia on the three upper leaves), and, on the other hand, the resistant component was not significantly more affected by septoria tritici blotch within the mixture. Complementary to the field experiments, a theoretical approach, based on the development of a mechanistic-stochastic model, aims to describe the progression of septoria tritici blotch within a heterogeneous 3D-canopy. This model includes both physical and epidemiological approaches. Firstly, a raindrop size distribution, which describes a rainfall event, is sampled based on numerical integration techniques that rely on Monte Carlo methods. Then, for the raindrops that impact on the virtual canopy, splash droplets are generated based on raindrop and plant surface properties. 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