Ecological Regulation of Black Leaf Streak Disease Driven by Plant Richness in Banana Agroecosystems

How do hedgerow characteristics alter the dispersal of Pseudocercospora fijiensis propagules?

BACKGROUND

Hedgerows represent an agroecological lever for pest management. To date, few studies have shown that they can be used as a lever for the control of aerial fungal diseases, especially as a barrier to dispersal. On banana production, the main disease is black leaf streak disease (BLSD), which is a fungal disease caused by Pseudocercospora fijiensis. This pathogen disperses through two types of spores: ascospore and conidia. The aim of this study was to observe and to quantify the effect of hedgerows on BLSD dispersal. Trap plants were placed at the same distance to an artificial source of inoculum with a hedgerow on one side. Lesions were counted to establish the daily lesion density of each trap plant. The combination of hedgerow characteristics such as height, width, and optical porosity were used to evaluate its potential capacity to intercept spores.

RESULTS

When ascospores were used as a source of inoculum, the lesion density on traps plant decreased up to 50% between the hedgerow with the lowest interception capacities and the one with the highest interception capacities. For conidia, hedgerow height and side of the trap plants (with or without hedgerow between them and the source) were not significant, but low porosity of the hedgerow reduced the lesion density. On the contrary, for ascospore, the hedgerow effect was anisotropic; the trap plants on hedgerow side had less lesions.

CONCLUSION

Our study is the first experimental proof of the effect of hedgerows on P. fijiensis dispersion, both on conidia and ascospore. We showed that hedgerow characteristics impact the capacity of interception of the hedgerow. © 2023 Society of Chemical Industry.

Disentangling the Factors Affecting the Dynamic of Pseudocercospora fijiensis: Quantification of Weather, Fungicide, and Landscape Effects

Quantifying the effect of landscape composition on disease dynamics remains challenging because it depends on many factors. In this study, we used a hybrid process-based/statistical modeling approach to separate the effect of the landscape composition on the epidemiology of banana leaf streak disease (BLSD) from weather and fungicide effects. We parameterized our model with a 5-year dataset, including weekly measures of BLSD on 83 plots in Martinique. After estimating the intrinsic growth parameters of the stage evolution of the disease (SED), we evaluated the dynamic effect of five fungicides. Then, we added the intra- and inter-annual effect on disease dynamics using a generalized linear model. Finally, the whole model was used to assess the annual effect of the landscape on the SED for 11 plots. We evaluated the significance of the landscape composition (proportions of landscape elements in 200-, 500-, 800-, 1,000-m-radius buffer zones) on the landscape effect evaluated with the model. The percentage of hedgerows in a 200-m-radius buffer zone was negatively correlated to the landscape effect, i.e., it acted as a constraint against BLSD spreading and development. The proportion of managed-banana-plants in a 1,000-m-radius buffer zone was negatively correlated to the landscape effect, probably due to a mass effect of fungicide treatments. Inversely, the proportions of forest and the proportion of unmanaged-banana-plants, both in 1,000-m-radius buffer zones, were positively correlated with the landscape effect. Our study provides a holistic approach of the role biotic and abiotic factors play on the dynamics of BLSD.

Unraveling the Complexity of Coffee Leaf Rust Behavior and Development in Different Coffea arabica Agroecosystems

Crop health management systems can be designed according to practices that help to reduce crop losses by restricting pathogen development and promoting host plant growth. A good understanding of pathogen and host dynamics, which are interdependent, is therefore needed. In this article, we used a holistic approach to explain the behavior of coffee leaf rust (CLR), a major coffee disease. We monitored coffee plant and CLR dynamics simultaneously in plots under different disease management and agroforestry systems. Diseased leaves were also collected to characterize inoculum stock and rust life stages (latent rust area, area with uredospores, necrosis due to rust) through picture analysis. We used structural equation modeling to obtain an overview of CLR pathosystem functioning on a plant scale. This overview integrates processes such as disease dilution by host leaf renewal, direct and indirect effects of fruit load on CLR development, antagonistic effects of shading depending on rust life stages, the tonic effect of copper-based fungicides on leaf retention, and effects on rust life stages depending on fungicide types. From our results, we also deduced that the inoculum stock could be calculated in unsprayed plots from the rust area with uredospores, with uredospores at 58 × 10³ cm^-2, on average.