Relating apparent electrical conductivity to soil properties across the north-central USA

被引:266
|
作者
Sudduth, KA
Kitchen, NR
Wiebold, WJ
Batchelor, WD
Bollero, GA
Bullock, DG
Clay, DE
Palm, HL
Pierce, FJ
Schuler, RT
Thelen, KD
机构
[1] Univ Missouri, USDA ARS, Cropping Syst & Water Qual Res Unit, Columbia, MO 65211 USA
[2] Univ Missouri, Dept Agron, Columbia, MO 65211 USA
[3] Iowa State Univ, Dept Agr & Biosyst Engn, Ames, IA 50011 USA
[4] Univ Illinois, Dept Crop Sci, Urbana, IL 61801 USA
[5] S Dakota State Univ, Dept Plant Sci, Brookings, SD 57007 USA
[6] Washington State Univ, Ctr Precis Agr Syst, Prosser, WA 99350 USA
[7] Univ Wisconsin, Dept Biol Syst Engn, Madison, WI 53706 USA
[8] Michigan State Univ, Dept Crop & Soil Sci, E Lansing, MI 48824 USA
关键词
soil electrical conductivity; precision agriculture; sensors; EM38; Veris; 3100;
D O I
10.1016/j.compag.2004.11.010
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Apparent electrical conductivity (ECa) of the soil profile can be used as an indirect indicator of a number of soil physical and chemical properties. Commercially available ECa sensors can efficiently and inexpensively develop the spatially dense datasets desirable for describing within-field spatial soil variability in precision agriculture. The objective of this research was to relate ECa data to measured soil properties across a wide range of soil types, management practices, and climatic conditions. Data were collected with a non-contact, electromagnetic induction-based ECa sensor (Geonics EM38) and a coulter-based sensor (Veris 3100) on 12 fields in 6 states of the north-central United States. At 12-20 sampling sites in each field, 120-cm deep soil cores were obtained and used for soil property determination. Within individual fields, EM38 data collected in the vertical dipole orientation (0-150 cm depth) and Veris 3100 deep (0-100cm depth) data were most highly correlated. Differences between ECa sensors were more pronounced on more layered soils, such as the claypan soils of the Missouri fields, due to differences in depth-weighted sensor response curves. Correlations of ECa with clay content and cation exchange capacity (CEC) were generally highest and most persistent across all fields and ECa data types. Other soil properties (soil moisture, silt, sand, organic C, and paste EC) were strongly related to ECa in some study fields but not in others. Regressions estimating clay and CEC as a function of ECa, across all study fields were reasonably accurate (r(2) >= 0.55). Thus, it may be feasible to develop relationships between ECa and clay and CEC that are applicable across a wide range of soil and climatic conditions. (c) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:263 / 283
页数:21
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