Research based crop-specific best management practices (BMPs) must be developed for sweet corn (Zea
mays L. var. saccharata) production to reduce the amount of nitrogen (N) leaching. The objective of this
study was to identify irrigation and nitrogen BMPs for sweet corn production on sandy soils in Florida
using the calibrated CERES-Maize model of the Decision Support System for Agrotechnology Transfer
(DSSAT). A total of 24 irrigation schedules, 21 N fertilizer levels, 30 N application splits, and 20 N
application rates per split were systematically evaluated in single factor simulations. Then, a set of 324
management scenarios composed of 6 irrigation timing/amount and 54 N fertilizer application strategies
selected in early single factor explorations, was explored in a multifactor analysis.
Irrigation frequency had a strong influence on sweet corn yield. If irrigation events were triggered
when maximum allowable depletion (MAD) of soil water content was greater than 60%, corn growth
suffered water stress and the simulated yield was reduced. The increase in yield approached zero above
168 kg N ha−1. Splitting N fertilizer applications did notinfluence yield ifthere was an N application during
the small-leaf stage or large-leaf stage;however,the lowest amount of N leaching occurred whenno N was
applied during the small-leaf stage. Simulated yield increased when application rates decreased from 100
to 70 kg N ha−1 per fertigation event, but changed only slightly at application rates less than 70 kg N ha−1
per fertigation. Smaller application rates per fertigation decreased N leaching substantially, especially
for rates less than 70 kg N ha−1. Six potential BMPs were selected from the 324 management scenarios as
optimizing yield while minimizing N leaching. These BMPs were composed of two irrigation schedules
(depths of 5.0 and 7.5 mm with MAD values of 20% and 30%), two N levels (196 and 224 kg N ha−1), two N
split plans (0-1/4-3/4 and 0-1/3-2/3 of total N applied in the small-leaf, large-leaf, and ear development
stages, respectively), and two N application rates per fertigation (30 and 40 kg N ha−1). It should be recognized
that these results are recommendations based on modeling assumptions and should be tested
in actual field production for their practical and economic validity