Sensitivity of soil electromagnetic induction measurements to salinity, water content, clay, organic matter and bulk density
Autor: | Fernando Visconti, José Miguel de Paz |
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Rok vydání: | 2021 |
Předmět: |
Salinity
N01 Agricultural engineering P34 Soil biology 0211 other engineering and technologies Soil science 02 engineering and technology Electrical resistivity and conductivity Linear regression Organic matter Texture Sensitivity (control systems) P33 Soil chemistry and physics Water content 021101 geological & geomatics engineering chemistry.chemical_classification 04 agricultural and veterinary sciences Bulk density Electromagnetic induction chemistry 040103 agronomy & agriculture P10 Water resources and management P30 Soil science and management 0401 agriculture forestry and fisheries Environmental science Precision agriculture Sensitivity analysis General Agricultural and Biological Sciences |
Zdroj: | electronico ReDivia. Repositorio Digital del Instituto Valenciano de Investigaciones Agrarias Universidad de Alicante (UA) ReDivia: Repositorio Digital del Instituto Valenciano de Investigaciones Agrarias Instituto Valenciano de Investigaciones Agrarias (IVIA) |
ISSN: | 1573-1618 1385-2256 |
Popis: | Observed variations in the ground electrical conductivity (σb*) measurements obtained with EMI instruments depend on several soil proxies that infuence crop growth and development such as salinity (σe), contents of water (θw), clay (wc) and organic matter (wom) and bulk density (ρb). However, the relative contributions of all these to σb* are unknown. This knowledge is needed to improve the planning and interpretation of σb* data for precision agriculture applications. Recently, a semi-empirical model has been developed to relate σb* measurements taken with an EM38 device to σe, θw, wc, wom and ρb and also soil temperature (t). In this work this model was subjected to a global sensitivity analysis (GSA) based on the soil data obtained during two surveys carried out, one in summer and the other in autumn, in an ample irrigated area in SE Spain. On the basis of the multiple linear regression meta-models developed for the σb* measurements, these were found to linearly respond to the soil properties (R2 between 0.92 and 0.96) and thus, the GSA could be based on their standardised regression coefcients. According to these, the soil characteristics explain the following percentages of variance in σb* (PV): 30–34 (σe), 8–20 (θw), 32–47 (wc), 0.6–2.6 (wom), 5.7–7.5 (ρb) and 0.3–0.4 (t) with changes from the summer to the autumn season of − 4, − 12 and+15 in the PV explained by the most infuential properties, respectively, σe, θw and wc. The results of the GSA will help the planning and interpretation of σb* measurements for improving crop management. |
Databáze: | OpenAIRE |
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