Agriculture Reference
In-Depth Information
ability. Likewise, the optimum N rate determined
from visual or sensor interpretation of the RCS
varies accordingly, thus requiring that N rates be
adjusted each year accordingly.
Ferguson, R.B., G.W. Hergert, J.S. Schepers, C.A. Gotway,
J.E. Cahoon, and T.A. Peterson. 2002. Site-specifi c nitro-
gen management of irrigated maize: Yield and soil residual
nitrate effects. Soil Sci. Soc. Am. J. 66:544-553.
Ferguson, R.B., J.S. Schepers, G.W. Hergert, and R.D.
Lohry. 1991. Corn uptake and soil accumulation of nitro-
gen: Management and hybrid effects. Soil Sci. Soc. Am. J.
55:875-880.
Food and Agriculture Organization. 2007. FAOSTAT: Agri-
cultural production [Online]. Available at http://faostat.
fao.org (verifi ed 19 Feb. 2008).
Johnson, G.V., and W.R. Raun. 2003. Nitrogen response
index as a guide to fertilizer management. J. Plant Nutr.
26:249-262.
Large, E.C. 1954. Growth stages in cereals: Illustration of the
Feekes Scale. Plant Pathol. 3:128-129.
Lobell, D.B., J.I. Ortiz-Monasterio, and G.P. Asner. 2004.
Relative importance of soil and climate variability for
nitrogen management in irrigated wheat. Field Crops Res.
87:155-165.
Mahler, R.L., F.E. Koehler, and L.K. Lutcher. 1994. Nitro-
gen source, timing of application, and placement: Effects
on winter production. Agron. J. 86:637-642.
Malakoff, D. 1998. Death by suffocation in the Gulf of
Mexico. Science 281:190-192.
Miao, Y., D.J. Mulla, P.C. Robert, and J.A. Hernandez.
2006. Within-fi eld variation in corn yield and grain quality
responses to nitrogen fertilization and hybrid selection.
Agron. J. 98:129-140.
Moges, S.M., W.R. Raun, R.W. Mullen, K.W. Freeman,
G.V. Johnson, and J.B. Solie. 2004. Evaluation of green,
red and near infrared bands for predicting winter wheat
biomass, nitrogen uptake, and fi nal grain yield. J. Plant
Nutr. 27:1431-1441.
Morris, K.B., K.L. Martin, K.W. Freeman, R.K. Teal, D.B.
Arnall, K. Desta, W.R. Raun, and J.B. Solie. 2006. Mid-
season recovery to nitrogen stress in winter wheat. J. Plant
Nutr. 29:727-745.
Mullen, R.W., K.W. Freeman, W.R. Raun, G.V. Johnson,
M.L. Stone, and J.B. Solie. 2003. Identifying an in-season
response index and the potential to increase wheat yield
with nitrogen. Agron. J. 95:347-351.
Ortiz-Monasterio, J.I., and W. Raun. 2007. Reduced nitrogen
for improved farm income for irrigated spring wheat in the
Yaqui Valley, Mexico, using sensor based nitrogen man-
agement. J. Agric. Sci. 145:1-8.
Randall, G.W., J.A. Vetsch, and J.R. Huffman. 2003. Corn
production on a subsurface-drained Mollisol as affected by
time of nitrogen application and nitrapyrin. Agron. J.
95:1213-1219.
Raun, W.R. 2008a. Long-term soil fertility experiments
at Oklahoma State University [Online]. Available at
http://www.nue.okstate.edu/Long_Term_Experiments.
htm (verifi ed 18 Feb. 2008).
Raun, W.R. 2008b. Predicting the potential response to
applied N [Online]. Available at http://www.nue.okstate.
edu/Index_RI.htm (verifi ed 19 Feb. 2008).
Raun, W.R., and G.V. Johnson. 1999. Improving nitrogen
use effi ciency for cereal production. Agron. J. 91:357-
363.
FUTURE PERSPECTIVES
There are still many unanswered needs relating
to improved N management in cereals. The
most important is generating improved yield-
prediction equations for midseason N applica-
tions. Current work is tailored at using soil-profi le
moisture in addition to NDVI values to refi ne
yield estimates, and that is certainly appropriate
in rainfed environments where moisture is often
limiting. If yield potential can be predicted, nutri-
ent removal can be easily estimated by multiplica-
tion with known grain and straw N concentrations.
Basing ensuing fertilizer N rates on projected
removal is logical. Also, added work is needed to
tailor N applications to the growth stage where N
assimilation is the greatest. Applying N at the
exact time when N demand is the greatest will
likely provide a signifi cant boost in resultant
NUE.
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