4.7 Article

Spatial variability of soil attributes by an electromagnetic induction sensor: A framework of multiple fields assessment under Brazilian soils

Journal

BIOSYSTEMS ENGINEERING
Volume 216, Issue -, Pages 229-240

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.biosystemseng.2022.02.017

Keywords

Soil apparent electrical conductivity; Proximal soil sensing; Precision farming; Site-specific management

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The study demonstrates the use of soil apparent electrical conductivity (ECa) as a valuable tool for mapping soil attributes and characterizing soil spatial variability. The results show a significant correlation between ECa and selected soil properties, indicating its potential for managing soil fertility in multiple fields.
Soil apparent electrical conductivity (ECa) to survey soil has been demonstrated to be a valuable tool for mapping the soil attributes. Whereas the correlation between ECa and soil attributes is well documented, the practical usage of ECa data to characterise soil properties on individual fields or across many fields is still not recognised in Brazil. Including ECa data from several fields could increase the capacity to characterise soil properties compared to a within-field approach. The objective of this study was to deliver a framework to allow the characterisation of soil spatial variability using ECa data from multiple fields. The ability of ECa to map the content and variability of soil attributes was assessed in six fields, totalling 412 ha and 2000 soil samples. The results indicate a significant correlation between ECa and selected soil properties. ECa data is useful to predict and characterise the content and variability of soil attributes according to ECa classes. Sites with relatively low ECa values presented greater spatial variability of those attributes, which requires more intensive sampling for proper spatial characterization. The amplitude of variation of ECa was directly correlated to clay content (R-2 = 0.95), SOM (R-2 = 0.65) and CEC (R-2 = 0.76) ranges, where 1.0 mS m(-1) corresponded to 1.5 g kg(-1), 0.12 g dm(-3) and 0.25 mmolc dm(-3), respectively. The spatial variability of those attributes remained stable over different sampling times. The significant correlation of ECa readings to soil attributes indicates a potential framework to manage soil fertility in multiple fields.(c) 2022 IAgrE. Published by Elsevier Ltd. All rights reserved.

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