Author
Listed:
- Sébastien Levionnois
(ECOSYS - Ecologie fonctionnelle et écotoxicologie des agroécosystèmes - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier)
- Noémie Gaudio
(AGIR - AGroécologie, Innovations, teRritoires - EI Purpan - Ecole d'Ingénieurs de Purpan - Comue de Toulouse - Communauté d'universités et établissements de Toulouse)
- Rémi Mahmoud
(AGIR - AGroécologie, Innovations, teRritoires - EI Purpan - Ecole d'Ingénieurs de Purpan - Comue de Toulouse - Communauté d'universités et établissements de Toulouse)
- Christophe Pradal
(UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier, Cirad-BIOS - Département Systèmes Biologiques - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement, IROKO - Sciences environnementales guidées par les données - Centre Inria d'Université Côte d'Azur - Inria - Institut National de Recherche en Informatique et en Automatique - LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier - CNRS - Centre National de la Recherche Scientifique - UM - Université de Montpellier - IMAG - Institut Montpelliérain Alexander Grothendieck - CNRS - Centre National de la Recherche Scientifique - UM - Université de Montpellier)
- Corinne Robert
(ECOSYS - Ecologie fonctionnelle et écotoxicologie des agroécosystèmes - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)
Abstract
Highlights: • Simulated intercropping decrease disease intensity and improve protectiveness while canopy indicators predict such effects. • Pea intercropped with wheat decreased disease intensity compared with faba bean. • Nitrogen fertilization increased disease intensity. • This study stressed the critical lack of experimental data on disease in intercropping. Abstract: Context : Intercropping is a promising strategy for integrated disease management and agroecological transition, although experimental and modelling studies are scarce. Objectives: This study aims to understand and quantify the impact of non-host species choice and nitrogen (N) fertilization on disease epidemics in the context of intercropping. Methods: We collected existing experimental data on LAI based on a literature survey of non-diseased wheat intercropped with different non-host legume species (pea and faba bean) and N fertilization treatments. Based on a foliar epidemic model for intercropping, we simulated epidemics directly on these experimental data of LAI. The model is parameterized for two wheat fungal diseases: Septoria tritici blotch, a rain-borne disease, and wheat leaf rust, an air-borne disease. Results: Our results indicate that intercropping can decrease disease intensity and improve protectiveness for both diseases. Effect depends however on species choice as pea intercropped with wheat leads to lower disease intensity and better intercropping protectiveness compared with faba bean, whereas N fertilization increased disease intensity. We also found that crop indicators describing wheat leaf area index (LAI) can predict disease intensity, whereas indicators describing companion LAI can better predict intercropping protectiveness. Conclusions: Intercropping can significantly reduce fungal epidemics on wheat, and intercropping management practices can be optimized for effective disease management in wheat-legume intercrops. The dilution effect is more related to disease intensity, while the barrier effect is more related to intercropping protectiveness. Implications: These findings pave the way for identifying field indicators to predict epidemics. However, this study also stressed the critical lack of experimental data on disease in intercropping.
Suggested Citation
Sébastien Levionnois & Noémie Gaudio & Rémi Mahmoud & Christophe Pradal & Corinne Robert, 2026.
"Impact of wheat-legume mix intercrops on wheat epidemics by modelling,"
Post-Print
hal-05328274, HAL.
Handle:
RePEc:hal:journl:hal-05328274
DOI: 10.1016/j.fcr.2025.110212
Note: View the original document on HAL open archive server: https://hal.science/hal-05328274v1
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