Dynamic model-based N management reduces surplus nitrogen and improves the environmental performance of corn production

Sela, S; Woodbury, PB; van Es, HM

HERO ID

5040439

Reference Type

Journal Article

Year

2018

Language

English

HERO ID 5040439
In Press No
Year 2018
Title Dynamic model-based N management reduces surplus nitrogen and improves the environmental performance of corn production
Authors Sela, S; Woodbury, PB; van Es, HM
Journal Environmental Research Letters
Volume 13
Issue 5
Abstract The US Midwest is the largest and most intensive corn (Zea mays, L.) production region in the world. However, N losses from corn systems cause serious environmental impacts including dead zones in coastal waters, groundwater pollution, particulate air pollution, and global warming. New approaches to reducing N losses are urgently needed. N surplus is gaining attention as such an approach for multiple cropping systems. We combined experimental data from 127 on-farm field trials conducted in seven US states during the 2011-2016 growing seasons with biochemical simulations using the PNM model to quantify the benefits of a dynamic location-adapted management approach to reduce N surplus. We found that this approach allowed large reductions in N rate (32%) and N surplus (36%) compared to existing static approaches, without reducing yield and substantially reducing yield-scaled N losses (11%). Across all sites, yield-scaled N losses increased linearly with N surplus values above similar to 48 kg ha(-1). Using the dynamic model-based N management approach enabled growers to get much closer to this target than using existing static methods, while maintaining yield. Therefore, this approach can substantially reduce N surplus and N pollution potential compared to static N management.
Doi 10.1088/1748-9326/aab908
Wosid WOS:000431146200003
Is Certified Translation No
Dupe Override No
Is Public Yes
Language Text English
Keyword N surplus; corn; yield-scaled N losses; crop simulation; dynamic model-based N management