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a Dep. of Agron., 209A Waters Hall, Univ. of Missouri, Columbia, MO 65211
b Dep. of Soil Science, North Carolina State Univ., Raleigh, NC 27695-7619
c Dep. of Crop Science, North Carolina State Univ., Raleigh, NC 27695-7620
d Dep. of Statistics, North Carolina State Univ., Raleigh, NC 27695-8203
* Corresponding author (jeff_white{at}ncsu.edu)
Received for publication May 19, 2005. In-season, site-specific, variable-rate (SS) N management based on remote sensing (RS) may reduce N losses to groundwater while maintaining or increasing yield and N fertilizer-use efficiency. We compared in-season, RS-informed N management applied on a uniform, field-average (FA) or SS basis with the current uniform best management practice (BMP) based on "Realistic Yield Expectations" (RYE) in a typical 2-yr southeastern U.S. coastal plain rotation: winter wheat (Triticum aestivum L.)double-crop soybean [Glycine max (L.) Merr.]corn (Zea mays L.). Compared with the RYE-based BMP, RS-informed SS management achieved: (i) a maximum of 2.3 mg L1 less groundwater NO3N after 2001 wheat due to 39 kg ha1 less fertilizer N and a 25% greater harvest N ratio (N in grain or forage/total N applied); (ii) 370 kg ha1 more 2002 corn grain with 32 kg ha1 greater N applied, similar harvest N ratio, and 37 kg ha1 greater surplus N; (iii) 670 kg ha1 more 2003 wheat grain associated with 14 kg ha1 greater fertilizer N, 27% greater harvest N ratio, and 9 kg ha1 less surplus N. Excepting one corn FA treatment that received excessive N, RS-informed management produced equal or greater economic returns to N than RYE, and less surplus N for wheat. Treatments produced enduring effects on groundwater [NO3N] consistent with agronomic results, but small relative to temporal [NO3N] fluctuations that were positively correlated with water table elevation. To assess N management in leaching-prone soils, frequent, periodic groundwater monitoring during and after the cropping season appears essential.
Abbreviations: BMP, best management practice CIR, color infrared photography DGPS, differential global positioning system FA, uniform, field-averaged nitrogen management GDVI, green difference vegetation index GNDVI, green normalized difference vegetation index Go, Goldsboro soil GS, growth stage Ly, Lynchburg soil MCLG, maximum contaminant level goal NIR, near infrared No, Norfolk soil NormNIR, normalized near infrared NUE, nitrogen use efficiency RGDVI, relative green difference vegetation index RS, remote sensing RYE, uniform, Realistic Yield Expectation nitrogen management SS, in-season, site-specific, variable-rate nitrogen management
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