Towards efficient N cycling in intensive maize: role of cover crops and application methods of digestate liquid fraction

Digestate, a by-product of biogas production, is widely recognized as a promising renewable nitrogen (N) source with high potential to replace synthetic fertilizers. Yet, inefficient digestate use can lead to pollutant N losses as ammonia (NH3) volatilization, nitrous oxide (N2O) emissions and nitrate (NO - 3) leaching. Cover crops (CCs) may reduce some of these losses and recycle the N back into the soil after incorporation, but the effect on the N balance depends on the CC species. In a one--year field study, we tested two application methods (i.e., surface broadcasting, BDC; and shallow injection, INJ) of the liquid fraction of separated co-digested cattle slurry (digestate liquid fraction [DLF]), combined with different winter cover crop (CC) options (i.e., rye, white mustard or bare fallow), as starter fertilizer for maize. Later, side--dressing with urea was required to fulfil maize N--requirements. We tested treatment effects on yield, N--uptake, N--use efficiency parameters, and N--losses in the form of N2O emissions and NO - 3 leaching. CC development and biomass production were strongly affected by their contrasting frost tolerance, with spring--regrowth for rye, while mustard was winter killed. After the CCs, injection of DLF increased N2O emissions significantly compared with BDC (emission factor of 2.69% vs. 1.66%). Nitrous oxide emissions accounted for a small part (11%-13%) of the overall yield-scaled N losses (0.46-0.97 kg N Mg grain-1). The adoption of CCs reduced fall NO - 3 leaching, being 51% and 64% lower for mustard and rye than under bare soil. In addition, rye reduced NO - 3 leaching during spring and summer after termination by promoting N immobilization, thus leading to -57% lower annual leaching losses compared with mustard. DLF application method modified N-loss pathways, but not the cumulative yield-scaled N losses. Overall, these insights contribute to inform an evidence-based design of cropping systems in which nutrients are recycled more efficiently.