Jump to main content
US EPA
United States Environmental Protection Agency
Search
Search
Main menu
Environmental Topics
Laws & Regulations
About EPA
Health & Environmental Research Online (HERO)
Contact Us
Print
Feedback
Export to File
Search:
This record has one attached file:
Add More Files
Attach File(s):
Display Name for File*:
Save
Citation
Tags
HERO ID
3857692
Reference Type
Journal Article
Title
Adaption of the AmaizeN model for nitrogen management in sweet corn (Zea mays L.)
Author(s)
Yuan, M; Ruark, MD; Bland, WL
Year
2017
Is Peer Reviewed?
1
Journal
Field Crops Research
ISSN:
0378-4290
EISSN:
1872-6852
Volume
209
Page Numbers
27-38
DOI
10.1016/j.fcr.2017.04.007
Web of Science Id
WOS:000403736100003
Abstract
Production of irrigated sweet corn on sandy soils requires ample N inputs and results in substantial leaching of nitrate to groundwater. The irrigation infrastructure of this system provides the opportunity for fertilizer additions throughout the season, opening the prospect for adaptive, real-time and site-specific management that might synchronize N availability with crop demand, minimizing leaching. This requires validated process-based and mechanistic simulations of the crop N budget and soil N cycling. We adapted the AmaizeN model to sweet corn, validated the model for groundwater NO3-N leaching estimation on sandy soils, and assessed the potential of model application for adaptive, in-season N management in this cropping system. The model was calibrated and tested with a two-season dataset by comparing predicted and measured leaf area index (LAI), above ground biomass (AGB), yield, and cumulative crop N uptake (CNUP). The model prediction and measurement comparisons yielded high coefficients of determination (R-2, 0.82-0.95) and low root-mean-square errors (RMSE, 6.0-9.5%) for the whole range of the target crop attributes across years and wide-ranging N treatments. The difference between simulated and measured groundwater NO3-N loadings from lysimeter experiments ranged from 2.1-19.8% as relative absolute errors in 2014, and 1.7-7.2% in 2015. The adaptive N management strategy was proposed and demonstrated in a moderate-N treatment using the model prediction for real-time soil N availability and crop N demand dynamics. This approach significantly enhanced crop productivity by approximately 40% compared to conventional practice, while reducing N fertilizer inputs and NO3-N loading by 30-48% and 27-52%, respectively, relative to the highest N input treatments. The adaptive strategy shows potential to achieve target crop yields while minimizing NO3-N leaching.
Keywords
Adaptive nitrogen management; AmaizeN model; Nitrate leaching; Sweet corn; Sandy soil
Tags
IRIS
•
Nitrate/Nitrite
Broad LitSearch 2016/1/1 - 2017/12/5
Refs found by LitSearch but not ATSDR/IARC
WoS
Refs found only by 2017 LitSearch or Citation Mapping
Ref Types 12/2017
All Others
Home
Learn about HERO
Using HERO
Search HERO
Projects in HERO
Risk Assessment
Transparency & Integrity