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ARS Home » Pacific West Area » Pendleton, Oregon » Columbia Plateau Conservation Research Center » Research » Publications at this Location » Publication #204429
Title: PRECISION FARMING FOR NITROGEN MANAGEMENT

Author
item Long, Daniel
item PIERCE, F. - WASHINGTON STATE UNIV.

Submitted to: Soil and Water Conservation Society
Publication Type: Book / Chapter
Publication Acceptance Date: 2/12/2007
Publication Date: 12/1/2010
Citation: Long, D.S., Pierce, F.J. 2010. PRECISION FARMING FOR NITROGEN MANAGEMENT. Soil and Water Conservation Society. pp 184-205.

Interpretive Summary: Approaches to precision nitrogen management vary from region to region depending on crop, soils, landscape, and climate yet all strategies essentially attempt to estimate crop nitrogen demand or plant available nitrogen. In this chapter, we provide case studies that illustrate precision nitrogen management in major crops and compare their benefits and limitations. A comprehensive strategy is proposed based on three approaches that are described in the literature: namely, use of previous season(s) data, start of current season data, and in-season data. Previous season(s) data derive from crop yield maps, crop quality maps, or remote sensing; start of current season data from soil testing, soil sensing, and simulation modeling; and in-season data from proximal sensing and remote sensing. Such integration that combines all three data sources in a unified strategy may lead to improve nitrogen management and provide the confidence that is needed for widespread adoption by growers.

Technical Abstract: Approaches to precision nitrogen management vary from region to region depending on crop, soils, landscape, and climate yet all strategies essentially attempt to estimate crop nitrogen demand or plant available nitrogen. In this chapter, we provide case studies that illustrate precision nitrogen management in major crops and compare their benefits and limitations. A comprehensive strategy is proposed based on three approaches that are described in the literature: namely, use of previous season(s) data, start of current season data, and in-season data. Previous season(s) data derive from crop yield maps, crop quality maps, or remote sensing; start of current season data from soil testing, soil sensing, and simulation modeling; and in-season data from proximal sensing and remote sensing. Such integration that combines all three data sources in a unified strategy may lead to improve nitrogen management and provide the confidence that is needed for widespread adoption by growers.