A wide variety of mathematical models have been used to relate crop pr
oduction to management factors such as applied Ei and water availabili
ty These include power functions and exponential functions. The object
ive of this analysis was to use an extended logistic model to relate d
ry matter yields and plant N removal to applied N for corn (Zea mays L
.) for three soils in North Carolina. In this model, response of both
dry matter yield and plant N removal to applied N were described by lo
gistic equations. Plant N concentration was then related to applied N
by the ratio of these logistic equations. Model parameters were estima
ted by nonlinear regression. Analysis of variance showed that the N re
sponse coefficient c was common for dry matter yield and plant N remov
al for each soil. Overall correlation coefficients of yield and plant
N removal with applied N were very high for all three soils (R > 0.99)
. It was shown that approximate to 50% of the total dry matter and 80%
of total plant N were contained in the grain at all applied N levels.
Maximum potential grain yield of 25.9 Mg ha(-1) agreed closely with a
n estimate in the literature of 26.5 Mg ha(-1) (500 bushels acre(-1)).
Dependence of plant N concentration on plant N removal was shown to f
ollow a Linear relationship. The present model provides a rational bas
is for coupling of dry matter yield and plant N removal in response to
applied N. It can be used in design and management decisions related
to agricultural production and environmental quality.