Maximum benefit of a precise nitrogen application system for wheat

Maximum benefit of a precise nitrogen application system for wheat Research is ongoing to develop sensor-based systems to determine crop nitrogen needs. To be economic and to achieve wide adoption, a sensor-based site-specific application system must be sufficiently efficient to overcome both the cost disadvantage of dry and liquid sources of nitrogen relative to applications before planting of anhydrous ammonia and possible losses if weather prevents applications during the growing season. The objective of this study is to determine the expected maximum benefit of a precision N application system for winter wheat that senses and applies N to the growing crop in the spring relative to a uniform system that applies N before planting. An estimate of the maximum benefit would be useful to provide researchers with an upper bound on the cost of delivering an economically viable precision technology. Sixty five site-years of data from two dryland winter wheat nitrogen fertility experiments at experimental stations in the Southern Plains of the U.S.A. were used to estimate the expected returns from both a conventional uniform rate anhydrous ammonia (NH3) application system before planting and a precise topdressing system to determine the value of the latter. For prices of $0.55 and $0.33 kg−1 N for urea-ammonium nitrate (UAN) and NH3, respectively, the maximum net value of a system of precise sensor-based nitrogen application for winter wheat was about $22–$31 ha−1 depending upon location and assumptions regarding the existence of a plateau. However, for prices of $1.10 and $0.66 kg−1 N for UAN and NH3, respectively, the value was approximately $33 ha−1. The benefit of precise N application is sensitive to both the absolute and relative prices of UAN and NH3. Precision Agriculture Springer Journals

Maximum benefit of a precise nitrogen application system for wheat

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Springer US
Copyright © 2006 by Springer Science+Business Media, LLC
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
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