Remote sensing offers unique ability to characterize spatial patterns in nitrogen (N) deficiency symptoms within cornfields. Studies reported in this dissertation were conducted to learn how this unique ability could be used along with new precision farming technologies to address the practical problem of improving estimates of N fertilizer needs in production agriculture. A key focus was on development of methodology for diagnosing deficiencies of N in fields that are assumed to include important spatial variability in factors that influence both the supply and demand for N.;Studies were conducted in fields of the size normally used in production agriculture. Various rates of fertilizer N were applied in replicated strips going the length of the field. Aerial photographs of the entire field were taken to measure canopy reflectance at various times. Many observations were made in selected test areas with hand-held SPAD meters, which measure chlorophyll activity in individual leaves and are the currently accepted alternative to remote sensing. Yield data were collected with combines equipped with yield monitors. Yield and reflectance responses to N fertilizer were calculated and interrelated.;The results confirmed the ability of SPAD meters to detect N deficiencies, but only when yield responses were great enough to pay for 200 kg N ha -1 at prices usually found in the Corn Belt. Remote sensing had the ability to detect smaller N deficiencies, but non-linear relationships were identified as a serious problem that limited the ability to detect small deficiencies in the middle of the season. The results illustrate need to recognize that the problems in diagnosing deficiencies of N in production agriculture are much greater than the problems associated with diagnosing deficiencies to help interpret results in a controlled experiment at one site where yields are also measured.