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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Adaptive Cropping Systems Laboratory » Research » Publications at this Location » Publication #239240
Title: Simulating nitrogen uptake and distribution in maize

Author
item YANG, YANG - University Of Maryland
item Timlin, Dennis
item Fleisher, David
item LOKHANDE, SURESH - Asian Institute Of Technology
item Chun, Jong
item QUEBEDEAUX, BRUNO - University Of Maryland
item Reddy, Vangimalla

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/14/2009
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Nitrogen is a dominant factor in the nutritional status of a maize crop. It is the most easily absorbed nutrient by corn crop and has the largest effect on yield. Leaf area development and light capture is dependent on the nitrogen status of the plant. Knowledge of the factors governing corn crop N demand and accurate prediction of N uptake and distribution within plants are essential in predicting the N needs of the crop under a wide range of field situations and the effects of N on maize growth and development. Functions were implemented in the coupled MaizSim-2DSOIL model to simulate the relationship between plant N concentration ([N]) and total mass, the faction of N partitioned to leaves, and N uptake and leaf N content of corn crop. Biomass of shoot and specific organs, N concentration, as well as SPAD meter measurement of specific leaves, were determined bi-weekly during the growing season at four sites for 2 years (2007 and 2008). Maize [N] declined with increase in shoot biomass following an exponential decay functions in both years. The fraction of N that was partitioned to leaves was a function of thermal time from emergence. [N] measurements indicated that whole plant nitrogen status can be represented by the nitrogen concentration of the youngest leaf. With the use of the [N]-biomass relationship to simulate N demand, the coupled model was able to predict the cumulative corn N uptake and distribution in aboveground tissues.