|SCHARF, PETER - University Of Missouri|
Submitted to: GIS Applications in Agriculture, Volume II, Nutrient Management for Energy Efficiency
Publication Type: Book / Chapter
Publication Acceptance Date: 12/10/2010
Publication Date: 2/2/2011
Citation: Bronson, K.F., Scharf, P.C., Kitchen, N.R. 2011. Use of GIS-based site-specific nitrogen management for improving energy efficiency. In: Clay, D.E., Shanahan, J.F., editors. GIS Applications in Agriculture, Volume Two, Nutrient Management for Energy Efficiency. Boca Raton, FL:CRC Press. p. 359-384.
Interpretive Summary: To our knowledge, no efforts have been made to employ GIS-based site-specific N management (SSNM) to improve energy costs and efficiency. We will now examine recent SSNM case studies for corn in Missouri and cotton in Texas. Specifically we will address the energy returns (including the outputs fuel and feed) to N fertilizer, particularly SSNM compared to blanket N fertilizer recommendations. These SSNM approaches tested included grid soil sampling, management zone strategies, aerial photography, and canopy reflectance. In irrigated cotton, positive energy returns to N fertilizer and to SSNM were achieved in high yielding drip-irrigation cotton, but not in lower yielding center pivot cotton. In the three corn case studies in Missouri, SSNM yielded more energy than conventional N management in several instances
Technical Abstract: To our knowledge, geographical information system (GIS)-based site-specific nitrogen management (SSNM) techniques have not been used to assess agricultural energy costs and efficiency. This chapter uses SSNM case studies for corn (Zea mays L.) grown in Missouri and cotton (Gossypium hirsutum L.) grown in Texass. In five case studies, the impact of SSNM will be compared with blanket N fertilizer recommendations. The five case studies are investigating (1) the impact N on energy produced in cotton production, (2) the impact of variable-rate N for cotton production based on soil nitrate and crop reflectance, (3) the feasibility of variable-rate N based on corn crop reflectance, (4) the use of corn management zones and crop reflectance for improving N recommendations and energy efficiency, and (5) the ability of using aerial photographs to improve N recommendations in corn.