Europe’s knowledge
platform for legumes

In this study, we employed 50 soybean genotypes to perform a multi-location trial at seven locations across Germany in 2021. Two environmental target regions were determined following the latitude of the locations.

Legume-supported cropping systems affect environmental, production, and economic impacts. In Europe, legume production is still marginal with grain legumes covering less than 3% of arable land. A transition towards legume-supported systems could contribute to a higher level of protein self-sufficiency and lower environmental impacts of agriculture. Suitable approaches for designing legume-supported cropping systems are required that go beyond the production of prescriptive solutions. We applied the DEED framework with scientists and advisors in 17 study areas in nine European countries, enabling us to describe, explain, explore, and redesign cropping systems. The results of 31 rotation comparisons showed that legume integration decreased N fertilizer use and nitrous oxide emissions (N2O) in more than 90% of the comparisons with reductions ranging from 6 to 142 kg N ha−1 and from 1 to 6 kg N2O ha−1, respectively. In over 75% of the 24 arable cropping system comparisons, rotations with legumes had lower nitrate leaching and higher protein yield per hectare. The assessment of above-ground biodiversity showed no considerable difference between crop rotations with and without legumes in most comparisons. Energy yields were lower in legume-supported systems in more than 90% of all comparisons. Feasibility and adaptation needs of legume systems were discussed in joint workshops and economic criteria were highlighted as particularly important, reflecting findings from the rotation comparisons in which 63% of the arable systems with legumes had lower standard gross margins. The DEED framework enabled us to keep close contact with the engaged research-farmer networks. Here, we demonstrate that redesigning legume-supported cropping systems through a process of close stakeholder interactions provides benefits compared to traditional methods and that a large-scale application in diverse study areas is feasible and needed to support the transition to legume-supported farming in Europe.

Biological nitrogen fixation mediated through symbiosis with rhizobial bacteria is a unique feature of legume crops. Under organic farming conditions, it is the main source of nitrogen in crop rotations. Therefore, nitrogen fixation of grain legumes has a substantial impact on crop performance, harvest product quality, and nitrogen balance of crop rotations. However, direct measurement of nitrogen fixation rate is laborious and technically demanding. In soybean breeding, selection for increased nitrogen fixation is desirable for improving seed protein content of genotypes and N balance of cropping systems. However, the lack of high-throughput screening methods for direct measurement of N2 fixation rates prohibits practical breeding efforts. Therefore, hyperspectral canopy reflectance measurement as a field-based phenotyping method was evaluated in three environments for indirect estimation of N fixation and uptake of soil nitrogen in a set of early maturity soybean genotypes exhibiting a wide range in seed protein content. Reflectance spectra were collected in repeated measurements during flowering and early seed filling stages. Subsequently, various spectral reflectance indices (SRIs) were calculated for characterizing nitrogen accumulation of individual genotypes. Moreover, prediction models for seed protein content as an end-of-season target trait were developed utilizing full spectral information in partial-least-square regression (PLSR) models. A number of N-related SRIs calculated from spectral reflectance data recorded at the beginning of the seed filling stage were significantly correlated to seed protein content. The best prediction of seed protein content, however, was achieved in PLSR models (validation R2=0.805 across all three environments). Environments lower in initial soil mineral N content appeared as more favorable selection sites in terms of prediction accuracy, because N fixation is not masked by soil N uptake in such environments. Hyperspectral reflectance data proved to be a valuable method for determining genetic variation in crop N accumulation, which might be implemented in high-throughput screening protocols for N fixation in plant breeding programs.