Correlation between the physical and chemical properties of an oxysol and the apparent electrical conductivity
Abstract
Keywords
Full Text:
PDFReferences
Abdallah, A.M., Jat, H.S., Choudhary, M., Abdelaty, E.F., Sharma, P.C. and Jat, M.L., 2021. Conservation Agriculture Effects on Soil Water Holding Capacity and Water-Saving Varied with Management Practices and Agroecological Conditions: A Review. Agronomy, 11(9), pp. 1681. https://doi.org/10.3390/agronomy11091681
Bañón, S., Álvarez, S., Bañón, D., Ortuño, M.F. and Sánchez-Blanco, M.J., 2021. Assessment of soil salinity indexes using electrical conductivity sensors. Scientia Horticulturae, 285, pp. 110171. https://doi.org/10.1016/j.scienta.2021.110171
Becker, S.M., Franz, T.E., Abimbola, O., Steele, D.D., Flores, J.P., Jia, X., Scherer, T.F., Rudnick, D.R. and Neale, C.M.U., 2022. Feasibility assessment on use of proximal geophysical sensors to support precision management. Vadose Zone Journal, 21(6), pp. 20228. https://doi.org/10.1002/vzj2.20228
Bento, C.B., Brandani, C.B., Filoso, S., Martinelli, L.A. and Carmo, J.B.D., 2021. Effects of extensive-to-intensive pasture conversion on soil nitrogen availability and CO2 and N2O fluxes in a Brazilian oxisol. Agriculture, Ecosystems & Environment, 321, pp. 107633. https://doi.org/10.1016/j.agee.2021.107633
Bernal R.J., Peña A., Díaz N. and Obano D., 2013. Condiciones Climáticas de la Altillanura Plana Colombiana en el Contexto de Cambio Climático. In: Amézquita E., Rao I., Rivera M., Corrales I. and J. Bernal, eds. Sistemas Agropastoriles: Un Enfoque Integrado para el Manejo Sostenible de Oxisoles de los Llanos Orientales de Colombia. Cali: International Center for Tropical Agriculture. pp. 28 – 42.
Corwin, D.L. and Scudiero, E., 2020. Field?scale apparent soil electrical conductivity. Soil Science Society of America Journal, 84(5), pp. 1405–1441. https://doi.org/10.1002/saj2.20153
Doolittle, J.A. and Brevik, E.C., 2014. The use of electromagnetic induction techniques in soils studies. Geoderma, 223–225, pp. 33–45. https://doi.org/10.1016/j.geoderma.2014.01.027
Ehosioke, S., Adebayo, M.B., Bailey, V.L., Peixoto, R.B., Emmanuel, E.D., Machado-Silva, F., Regier, P.J., Spanbauer, T., Thomas, S.P., Ward, N.D., Weintraub, M.N. and Doro, K. O., 2024. Geophysical methods reveal the soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie. Journal of Soils and Sediments, 24(6), pp. 2215–2236. https://doi.org/10.1007/s11368-024-03787-w
Estrada-Godoy, F., Cruz-Cárdenas, G., Ochoa-Estrada, S. and Silva, J.T. 2023. Cartografía digital de suelos con regresión-Kriging y datos de sensores remotos. Revista terra latinoamericana, 41. pp. 12. https://doi.org/10.28940/terra.v41i0.1617
Geonics Limited Ontario., 2002. EM38-MK2 ground conductivity meter, operating manual. Ontario: Geonics. pp. 32.
Gómez Chávez, A.F., Feo Mahecha, J.K. and Parra Gonzalez, S.D., 2024. Estimación de analitos del suelo en la altillanura, con teledetección sentinel-2 y modelos de regresión. Revista de Investigación Agraria y Ambiental, 15(2), pp. 269–289. https://doi.org/10.22490/21456453.7003
Grisales, E.F., Darghan, A.E. and Rivera, C.A., 2022. Use of two relative depths of the soil apparent electrical conductivity to define experimental blocks with spatial regression models. Spanish Journal of Agricultural Research, 20(1), pp. 1102. https://doi.org/10.5424/sjar/2022201-18631
He, Y., Li, X. and Jin, M., 2023. Temporal and Spatial Assessment of Soil Salinity Post-Flood Irrigation: A Guide to Optimal Cotton Sowing Timing. Agronomy, 13(9), pp. 2246. https://doi.org/10.3390/agronomy13092246
Heil, K. and Schmidhalter, U., 2015. Comparison of the EM38 and EM38-MK2 electromagnetic induction-based sensors for spatial soil analysis at field scale. Computers and Electronics in Agriculture, 110, pp. 267–280. https://doi.org/10.1016/j.compag.2014.11.014
Henrion, M., Li, Y., Koganti, T., Bechtold, M., Jonard, F., Opfergelt, S., Vanacker, V., Van Oost, K. and Lambot, S., 2024. Mapping and monitoring peatlands in the Belgian Hautes Fagnes: Insights from Ground-penetrating radar and Electromagnetic induction characterization. Geoderma Regional, 37, pp. 795. https://doi.org/10.1016/j.geodrs.2024.e00795
ICONTEC., 2007. NTC 5526:2007 Calidad de suelo. Determinación de disponibles: Cobre, manganeso. Bogotá: Icontec. micronutrientes zinc, hierro y manganeso. Bogotá, Colombia: Icontec. pp. 8.
ICONTEC., 2008. NTC 5595:2008 Calidad de suelo. Determinación del nitrógeno amoniacal y nitrógeno nítrico. Bogotá, Colombia: Icontec. pp. 11.
ICONTEC., 2014. NTC 5268:2014 Calidad de suelo. Determinación de la capacidad de intercambio catiónico. Bogotá, Colombia: Icontec. pp. 5.
ICONTEC., 2016. NTC 5349:2016 Calidad de suelo. Determinación de las bases cambiables: Método del acetato amonio 1m, pH 7,0. Bogotá, Colombia: Icontec. pp. 9.
ICONTEC., 2017. NTC 5263:2017 Calidad del suelo. Determinación de la acidez, aluminio e hidrógeno intercambiables. Bogotá, Colombia: Icontec. pp. 10.
ICONTEC., 2018b. NTC 6299:2018 Calidad del suelo. Determinación de la textura por bouyoucos. Bogotá, Colombia: Icontec. pp. 11.
ICONTEC., 2022a. NTC-ISO 11464:2022 Calidad del suelo. Pretratamiento de muestras para análisis fisicoquímicos. Bogotá, Colombia: Icontec. pp. 14.
ICONTEC., 2022b. NTC 5596:2022 Calidad del suelo. Determinación de la conductividad eléctrica. Bogotá, Colombia: Icontec. pp. 15.
ICONTEC., 2022c. NTC 5403:2021 Calidad del suelo. Determinación del carbono orgánico. Bogotá, Colombia: Icontec. pp. 18.
IGAC. and CIAF., 2018. La altillanura colombiana: aspectos biofísicos. Bogotá, Colombia: Imprenta Nacional de Colombia. pp. 132.
IGAC. 2004. Estudio general de suelos y zonificación de tierras: departamento del Meta. (2da ed.). Bogotá, Colombia: Imprenta Nacional de Colombia. pp. 496.
Karp, F.H.S., Adamchuk, V.I., Melnitchouck, A., Allred, B., Dutilleul, P. and Martinez, L. R., 2023. Validation And Potential Improvement of Soil Survey Maps Using Proximal Soil Sensing. Journal of Environmental and Engineering Geophysics, 28(1), pp. 45–61. https://doi.org/10.32389/JEEG22-018
Lal, R., 2017. Geophysical Methods. In Encyclopedia of Soil Science, CRC Press. https://doi.org/10.1081/E-ESS3-120053754
Loiseau, B., Carrière, S.D., Jougnot, D., Singha, K., Mary, B., Delpierre, N., Guérin, R. and Martin-StPaul, N.K., 2023. The geophysical toolbox applied to forest ecosystems – A review. Science of The Total Environment, 899, 165503. https://doi.org/10.1016/j.scitotenv.2023.165503
Mello, D.C.D., Safanelli, J.L., Poppiel, R.R., Veloso, G.V., Cabrero, D.R.O., Greschuk, L.T., De Oliveira Mello, F.A., Francelino, M.R., Ker, J.C., Leite, E.P., Fernandes-Filho, E.I., Schaefer, C.E.G.R. and Demattê, J.A.M., 2022. Soil apparent electrical conductivity survey in different pedoenvironments by geophysical sensor EM38: a potential tool in pedology and pedometry studies. Geocarto International, 37(26), pp. 13057–13078. https://doi.org/10.1080/10106049.2022.2076913
Oliver, M.A. and Webster, R., 2015. Basic Steps in Geostatistics: The Variogram and Kriging. Springer International Publishing. https://doi.org/10.1007/978-3-319-15865-5
Ondrasek, G. and Rengel, Z., 2021. Environmental salinization processes: Detection, implications & solutions. Science of The Total Environment, 754, pp. 142432. https://doi.org/10.1016/j.scitotenv.2020.142432
Pasaribu, N.P., Wahjunie, E.D. and Tarigan, S.D., 2023. Characteristics of soil physical properties in different soil management of oxisols and inceptisols. Agrovigor: Jurnal Agroekoteknologi, 16(2), pp. 83–90. https://doi.org/10.21107/agrovigor.v16i2.19869
Pathirana, S., Lambot, S., Krishnapillai, M., Cheema, M., Smeaton, C. and Galagedara, L., 2023. Ground-Penetrating Radar and Electromagnetic Induction: Challenges and Opportunities in Agriculture. Remote Sensing, 15(11), pp. 2932. https://doi.org/10.3390/rs15112932
Pento?, K., Pieczarka, K. and Serwata, K., 2021. The Relationship between Soil Electrical Parameters and Compaction of Sandy Clay Loam Soil. Agriculture, 11(2), pp. 114. https://doi.org/10.3390/agriculture11020114
Petsetidi, P.A. and Kargas, G., 2023. Assessment and Mapping of Soil Salinity Using the EM38 and EM38MK2 Sensors: A Focus on the Modeling Approaches. Land, 12(10), pp. 1932. https://doi.org/10.3390/land12101932
Rab, M.A., Chandra, S., Fisher, P.D., Robinson, N.J., Kitching, M., Aumann, C.D. and Imhof, M., 2011. Modelling and prediction of soil water contents at field capacity and permanent wilting point of dryland cropping soils. Soil Research, 49(5), pp. 389–407. https://doi.org/10.1071/SR10160
Rieder, L., Amann, T. and Hartmann, J., 2024. Soil electrical conductivity as a proxy for enhanced weathering in soils. Frontiers in Climate, 5, pp. 1283107. https://doi.org/10.3389/fclim.2023.1283107
Robain, H., Descloitres, M., Ritz, M. and Atangana, Q.Y,. 1996. A multiscale electrical survey of a lateritic soil system in the rain forest of Cameroon. Journal of Applied Geophysics, 34(4), pp. 237–253. https://doi.org/10.1016/0926-9851(95)00023-2
Rodrigues, H.M., Vasques, G.M., Oliveira, R.P., Tavares, S.R.L., Ceddia, M.B. and Hernani, L.C., 2020. Finding Suitable Transect Spacing and Sampling Designs for Accurate Soil ECa Mapping from EM38-MK2. Soil Systems, 4(3), pp. 1-19. https://doi.org/10.3390/soilsystems4030056
Romero?Ruiz, A., Linde, N., Keller, T. and Or, D., 2018. A Review of Geophysical Methods for Soil Structure Characterization. Reviews of Geophysics, 56(4), pp.672–697. https://doi.org/10.1029/2018RG000611
Sanches, G.M., Otto, R., Adamchuk, V. and S.G. Magalhães. P., 2022. Spatial variability of soil attributes by an electromagnetic induction sensor: A framework of multiple fields assessment under Brazilian soils. Biosystems Engineering, 216, pp. 229–240. https://doi.org/10.1016/j.biosystemseng.2022.02.017
Santos, D.P., Santos, G.G., Oliveira, V.Á. de, Silva, G.C. da, Flores, R.A., Azevedo, A.C., Júnior, V.S. de S. and Pereira, M.G., 2024. Chemical and mineralogical constitution of redoximorphic features and mechanism of formation of Plinthosols from the Araguaia River plain, Brazil. Revista Brasileira de Ciência do Solo, 48. https://doi.org/10.36783/18069657rbcs20230115
Silva, C.M.C.A.C., Barbosa, R.S., Nascimento, C.W.A.D., Silva, Y.J.A.B.D. and Silva, Y.J.A.B.D., 2018. Geochemistry and Spatial Variability of Rare Earth Elements in Soils under Different Geological and Climate Patterns of the Brazilian Northeast. Revista Brasileira de Ciência do Solo, 42. pp. 1-17. https://doi.org/10.1590/18069657rbcs20170342
Steenekamp, D., Van-Rensburg, L., Barnard, J. and Du-Preez, C., 2024. Are inorganic nitrogen concentrations in potassium chloride and saturated paste extracts of irrigated soils comparable?. South African Journal of Plant and Soil, pp. 1–9. https://doi.org/10.1080/02571862.2023.2294448
Sun, R. and Han, G., 2024. A comprehensive review of multi-scale mechanisms of soil carbon mineralization: From micro processes to macro ecosystems. Geographical Research Bulletin, 3 pp. 471-498. https://doi.org/10.50908/grb.3.0_471
Tsai, C.C. and Lin, C.H., 2022. Review and Future Perspective of Geophysical Methods Applied in Nearshore Site Characterization. Journal of Marine Science and Engineering, 10(3), pp. 344. https://doi.org/10.3390/jmse10030344
Van-Leeuwen, C., Schmutz, M. and De-Rességuier, L., 2024. The contribution of near surface geophysics to measure soil related terroir factors in viticulture: A review. Geoderma, 449, pp. 116983. https://doi.org/10.1016/j.geoderma.2024.116983
Zajícová, K. and Chuman, T., 2019. Application of ground penetrating radar methods in soil studies: A review. Geoderma, 343, pp. 116–129. https://doi.org/10.1016/j.geoderma.2019.02.024
Zhao, D., Li, N., Zare, E., Wang, J. and Triantafilis, J., 2020. Mapping cation exchange capacity using a quasi-3d joint inversion of EM38 and EM31 data. Soil and Tillage Research, 200, pp. 104618. https://doi.org/10.1016/j.still.2020.104618.
Zhao, W., Hu, W., Zhang, F., Shi, Y., Wang, Y., Zhang, X., Feng, T., Hong, Z., Jiang, J., and Xu, R. 2024. Exchangeable acidity characteristics of farmland black soil in northeast China. Geoderma Regional, 38, pp. 852. https://doi.org/10.1016/j.geodrs.2024.e00852
Zhao, D., Wang, J., Zhao, X. and Triantafilis, J., 2022. Clay content mapping and uncertainty estimation using weighted model averaging. Catena, 209, pp. 105791. https://doi.org/10.1016/j.catena.2021.105791
URN: http://www.revista.ccba.uady.mx/urn:ISSN:1870-0462-tsaes.v28i3.62681
DOI: http://dx.doi.org/10.56369/tsaes.6268
Copyright (c) 2025 Sareth Samantha Ulloa Galeano, Jhon Alexander Carrillo Rozo, Sergio David Parra González

This work is licensed under a Creative Commons Attribution 4.0 International License.