Economics of site-specific nitrogen management for protein content in wheat

被引:19
作者
Bongiovanni, R. G. [1 ]
Robledo, C. W.
Lambert, D. M.
机构
[1] Inst Nacl Tecnol Agropecuaria, Estacion Expt Agropecuaria Manfredi, La Plata, Argentina
[2] Univ Empresarial Siglo 21, Dept Econ, Cordoba, Argentina
[3] Univ Tennessee, Dept Agr Econ, Knoxville, TN USA
关键词
wheat; yield monitor; protein; economically optimal nitrogen rates; spatial econometrics;
D O I
10.1016/j.compag.2007.01.018
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Wheat fields in the semiarid region of Argentina are spatially variable in soil nitrogen (N) fertility and crop productivity. By accounting for spatial variation in soil N levels, variable-rate fertilizer application may improve crop yield, protein content, and N use efficiency within fields. Therefore, there is interest in applying variable rates of N fertilizer across the landscape. The general objectives of this research are to determine relationships among yield, protein and N rates, using spatial regression analysis of yield monitor data; and to optimize variable-rate application (VRA) of nitrogen fertilizer for wheat. The data were drawn from an on-farm N trial of 10.2 ha. within a 44 ha field conducted in Manfredi, Cordoba, Argentina, in 2003. The experimental design was a complete block strip trial that included two different types of soils in terms of landscape (Hilltop and Lowland) and two different antecessor crops (Corn and Soybeans). The fertilized strips were wider than the combine platform width, with zero N application as the control, and five other rates of elemental N (12, 37, 62, 88 and 112 kg ha(-1)). Yield data were obtained with a combine grain monitor, and grain samples for quality analysis were manually collected from the grain flow of a combine harvester, analyzed for quality in the laboratory and converted into a geographical information system (GIS) layer, together with the yield monitor data. Yield and grain quality variability was observed across the field, and among treatments. The combination of yield maps, soil moisture and protein content can help to determine management zones in order to maximize economic benefit. This approach offers opportunities to optimize grain protein on a site-specific basis by accounting for spatial variability of N fertility within individual fields. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:13 / 24
页数:12
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