Cover crop root system traits analysis for soil health and crop yield prediction

Overview

This research initiative investigates the relationship between root-system traits of 15 cover crop species and their associated benefits to soil health and cash crop productivity. Cover crops play a critical role in sustainable agriculture by reducing soil loss, minimizing chemical run-off, sequestering carbon, suppressing weeds, and increasing soil organic matter. Because root systems are the primary interface between plants and soil, understanding root traits and their correlation with ecosystem services and crop yields is essential for breeding improved cover crop varieties. The project addresses a significant gap by systematically collecting and analyzing paired data on root traits, shoot traits, soil quality, and cash crop yields.

Technical specifications

Research approach:

• Field trials with 15 cover crop species across four plant families: grasses (barley, winter rye, triticale, wheat varieties), legumes (alfalfa, Astragalus, pea, garbanzo bean, lentil, clover, hairy vetch), mustards (Daikon radish, mighty mustards), and buckwheat
• Collection of 2D and 3D root-system traits alongside shoot-system traits including biomass, growth rate, and flowering time
• Soil quality measurements including erosion indicators, chemical run-off, carbon sequestration, weed suppression, and organic matter content
• Yield tracking of maize and soybean cash crops planted on the same fields
• Computational modeling to predict soil health and cash crop yields from below- and above-ground plant shape data

Team expertise:

• Root genotyping and phenotyping
• Co-variation analysis between roots and shoots
• Plant shape analysis
• Predictive modeling

Technology readiness level

The project is in active validation phase. Initial field planting occurred in September 2020 at the Danforth Plant Science Center Field Research Site in O'Fallon, Missouri. The research is projected to take one year to complete, with the resulting data and models intended to serve as the foundation for future larger-scale studies and breeding applications. The team is actively seeking partnerships that provide expertise in data collection and analysis, as well as funding for sensing equipment and personnel.