Tracking Ideal Varieties and Cropping Techniques for Agroecological Weed Management: A Simulation-Based Study on Pea.

Area of Science:

• Agronomy
• Plant Breeding
• Ecology

Background:

• Pea (Pisum sativum) is a vital crop for diversification but lacks competitiveness against weeds.
• Developing weed-suppressing pea varieties is essential for sustainable agriculture.

Purpose of the Study:

• Identify key pea traits for crop production, weed control, and biodiversity.
• Determine optimal pea variety parameters and management for these goals.

Main Methods:

• Utilized the FLORSYS mechanistic simulation model for virtual experiments.
• Parameterized the model with seven pea varieties and created ten virtual varieties using Latin Hypercube Sampling (LHS).
• Conducted global sensitivity analysis across nine contrasting cropping situations and analyzed data with Classification and Regression Trees (CART).

Main Results:

• Identified plant height and leaf area in shaded conditions as key drivers of yield and weed competitiveness, varying by pea type (spring/winter) and system.
• Developed rules for farmers to select optimal pea varieties based on production goals and cropping systems.
• Highlighted trade-offs between yield potential and weed control, particularly for winter peas.

Conclusions:

• Pea breeding should focus on traits enhancing weed regulation through biological interactions.
• Specific variety traits are beneficial only in certain systems (e.g., delayed emergence with herbicides).
• Integrating variety traits with management strategies is key, especially when reducing herbicide or tillage use.