This last season (2023) we started assessing different soybean configurations to estimate the potential productivity (no resource or management limitation) for the three cropping systems (i.e, soybean sole crop, soybean after a cover crop, and soybean in a double cropping). Knowing that farmers require economically viable solutions while attaining sustainable systems, we considered that double cropping could be an alternative that brings most of the benefits of cover cropping while allowing for further intensification of the cropping systems. Ultimately, we assessed the effect of soybean maturity rate and inter-row spacing on soybean yield for different intensification alternatives. The question we successfully initiated to answer was: Which are the maturity rate and inter row spacing that maximize soybean yield for each cropping system?
Our results indicated that double cropping effectively can potentially increase land productivity in Minnesota compared with the other alternatives. There is a lot of room for assessing the fine tuning of soybean management and the interaction with different growing conditions, and one of the main questions that arose is – what is performance of intensified cropping systems on real farm fields, acknowledging the inherent complexities of diverse environments. Accelerating the transition from controlled experiments to on-farm trials is relevant. The sooner we implement real-world tests, the quicker we can gather valuable feedback on the limiting factors, and maybe facilitate a prompt understanding of how the system could be adapted to the complexities of actual farming practices. In this way, the project looks for collaboration between researchers and farmers. Farmers should engage with the research process, share their experiences, and collectively contribute to the advancement of sustainable and intensified cropping systems across our region.
In order to achieve this goal, we propose to conduct simple field experiments at a farm level comparing the three cropping systems. The management for each system should be based on the knowledge generated last season (tillage, planting dates, maturities, plant population, inter-row spacing). Complementary, it proposes to continue with the more controlled experiments that will continue to generate inputs for the fine tuning of each management practice at the farm level and also will feed crop simulation models that are going to be powerful tools to extend the system design to different locations, managements and weather conditions.