Densidade Amostral, identificação da variabilidade espacial de atributos químicas e susceptibilidade magnética do solo no Cerrado Piauiense
DOI:
https://doi.org/10.26848/rbgf.v18.4.p2657-2676Keywords:
Magnetização, Manejo, Preservação, SoloAbstract
The floristic and soil composition of the Cerrado is varied, indicating that the soil requires specific preparations to facilitate sustainable agricultural management and environmental preservation. In this context, non-destructive techniques, such as magnetic susceptibility, can identify the diversity and characteristics of the soil with a smaller number of samples. This study verified the magnetic susceptibility and chemical attributes of the soil through different sampling densities in the MATOPIBA region. The work was conducted in the municipality of Barreiras do Piauí. The area under study was delimited and georeferenced, in 1 hectare (100 x 100 m), three sampling densities were applied (10 x 10, 20 x 20 and 30 x 30 m), with collections at 0.0-0.20 and 0.20-0.40 m, totaling 242 samples. pH, organic matter, P, Ca, K, Mg, H+Al, Al, SB, CTC and V%. Magnetic susceptibility was analyzed using a scale, and the data was analyzed using univariate, descriptive, multivariate and geostatistical statistics. The densities and depths, but the 30 x 30 m density showed defined variability with fewer samples. The correlation between chemical attributes and magnetic susceptibility was insignificant, except for CTC and organic matter at density 10 x 10 m at 0-0.20 m. The kriging maps revealed areas with lower nutrient concentrations, allowing management according to local needs. A multivariate analysis indicated that the 10 x 10 and 30 x 30 m grids are the most suitable for spatial variability studies.
Keywords: preservation, soil, management, magnetization.
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Agegnehu, G., Amede, T., Desta, G., Erkossa, T., Legesse, G., Gashaw, T., Rooyen, A. V., Harawa, R., Degefu, T., Mekonnen, K., Schulz, S. (2023). Improving fertilizer response of crop yield through liming and targeting to landscape positions in tropical agricultural soils. Heliyon 9,e17421.https://doi.org/10.1016/j.heliyon.2023.e17421
Ayoubi, S., Jabbari, M., Khademi, H. (2018). Multiple linear modeling between soil properties, magnetic susceptibility and heavy metals in various land uses. Modeling Earth Systems and Environment 4, 579-589. https://doi.org/10.1007/s40808-018-0442-0
Barros, B. A. A., Matias, S.S.R., Nogueira, M. S., Lins, R. C., Oliveira, F. F., Tavares Filho, G. S. (2022). Spatialization of chemical attributes, penetration resistance and magnetic susceptibility of the soil in a Cerrado área. Revista Brasileira de Ciências Agrárias 17, e2186.https://doi.org/10.5039/agraria.v17i4a2186.
Cambardella, C. A., Moorman, T. B., Novak, J. M., Parkin, T. B., Karlen, D. L., Turco, R. F., Konopka, A. E. (1994). Field‐scale variability of soil properties in central Iowa soils. Soil science society of America journal 58, 1501-1511. https://doi.org/10.2136/sssaj1994.03615995005800050033x
Cardoso, K. D. V., Amorim, J. D. (2024). Matopiba: A fronteira agrícola sob o olhar de estudantes da educação básica. Revista Eixo 13, 4 -19. https://doi.org/10.19123/REixo.v13n2.1
Figueiredo Filho, D. B., Silva Júnior, J. A. (2009). Desvendando os Mistérios do Coeficiente de Correlação de Pearson (r). Revista Política Hoje 18, 115-146.
Hair, J. F., Anderson, R. E., Tatham, R. L., BLACK, W., 2005. Análise multivariada de dados. Porto Alegre: Bookman, 593 p.
Jalane, O. I., Mafalacusser, J. M., da Siva, E. V., Mabjaia, A. S. A. (2023). Geoestatística e SIG como Técnica de Mapeamentos das Propriedades Químicas do Solo. RAC: Revista Angolana de Ciências 5, e050208. https://doi.org/10.54580/R0502.08
Kamimura, K. M., Santos, G. R. D., Oliveira, M. S. D., Dias Junior, M. D. S., Guimarães, P. T. G. (2013). Variabilidade espacial de atributos físicos de um Latossolo Vermelho-Amarelo, sob lavoura cafeeira. Revista Brasileira de Ciência do Solo 37, 877-888. https://doi.org/10.1590/S010006832013000400006
Kruglov, O., Menshov, O., Horoshkova, L., Kruhlov, B., 2023. Magnetic susceptibility of inclined soils and its relationship with some agronomic indicators. Plant & Soil Science 14, 39-50. https://doi.org/10.31548/plant1.2023.39
Lemos Filho, L. C. A., de Oliveira, E. L., de Faria, M. A., de Bastos Andrade, L. A. (2008). Variação espacial da densidade do solo e matéria orgânica em área cultivada com cana-de-açúcar (Saccharum officinarum L.). Revista ciência agronômica 39, 193-202.
Ma, G., Cheng, S., He, W., Dong, Y., Qi, S., Tu, N., Tao, W. (2023). Effects of organic and inorganic fertilizers on soil nutrient conditions in rice fields with varying soil fertility. Land 12, 1026. https://doi.org/10.3390/land12051026
Matias, S. S. R., Baptistel, A. C., Nobrega, J. C. A., Andrade, F. R., da Silva, J. B. L. (2015). Variabilidade espacial dos atributos do solo em duas áreas de manejo convencional no Cerrado piauiense. Revista de Ciências Agrárias Amazonian Journal of Agricultural and Environmental Sciences 58, 217-227. http://dx.doi.org/10.4322/rca.1687
Matos, A. P. D., Matias, S. S. R., Nunes, R. K. L., Morais, E. M., Tavares Filho, G. S. (2023). Soil management of limed areas cultivated with banana identified by magnetic susceptibility. Revista Ceres 70, 17-24. https://doi.org/10.1590/0034737X202370040004
Matos, A. P., Matias, S. S. R., Landim, J. S. P., Nunes, T. P. M. (2024). Variabilidade espacial dos micronutrientes, granulometria e susceptibilidade magnética do solo em área de bananeira com e sem incorporação de calcário. Revista Brasileira de Geografia Física, v.17, n.05, p.3700-3714. https://doi.org/10.26848/rbgf.v17.5.p3700-3714.
Minitab, 2000. Release Making Data analysis Easier: version 13.1. CD Rom
Monteiro, H. O., Matias, S. S. R., Vogado, R. F., Nogueira, M. S., Silva, D. N., Landim, J. S. P. (2024). Espacialização dos atributos do solo e suscetibilidade magnética em ambiente de inundação sazonal no Nordeste do Brasil. Revista Brasileira de Geografia Física, v.17, n.4, p.2795-2807. https://doi.org/10.26848/rbgf.v17.4.p2795-2807
Moreira, E. V., Tavares Filho, G. S., de Oliveira, F. F., Júnior, F. A. P., de Sousa Araújo, C. A., Matias, S. S. R. (2020). Espacialidade dos atributos químicos de águas subterrâneas do município de Granito, PE. Research, Society and Development 9, e10091210779-e10091210779. https://doi.org/10.33448/rsd-v9i12.10779
Oliveira Filho, F. X. D., Miranda, N. D. O., Medeiros, J. F. D., Silva, P. C. D., Mesquita, F. O., Costa, T. K. (2015). Zona de manejo para preparo do solo na cultura da cana-de-açúcar. Revista Brasileira de Engenharia Agrícola e Ambiental, 19, p.186-193. https://doi.org/10.1590/18071929/agriambi.v19n2p186-193
Oliveira, B. A., Campos, L. P., Matias, S. S. R., Silva, T. S. D., Gualberto, A. V. S. (2021). Spatiality of soil chemical attributes in a banana cultivation area in west Bahia. Revista Caatinga, 34, p.177-188. https://doi.org/10.1590/1983-21252021v34n118rc
Pereira, P., Bogunovic, I., Inacio, M., Zhao, W., Barcelo, D. (2023). Agriculture intensification impacts on soil and water ecosystem services. In EGU General Assembly Conference Abstracts (pp.EGU-1423). https://doi.org/ 10.5194/egusphere-egu23-1423
R Core Team R. (2022). A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Robertson, G.P. GS+. (2008). Geostatistics for the environmental sciences (version 9 for windows). Gamma Design Software. 179p.
Rousse, S., Llubes, M., Ghorbel, M., Soubrand, M., Joussein, E., Munoz, M. (2023). Multi-devices field magnetic susceptibility:‘3D’spatialization of metallic contamination in soils and reverse correlation in carbonated context (Jebel Ressas, Tunisia). Environmental Earth Sciences 82, 457. https://doi.org/10.1007/s12665-023-11104-w
Siqueira, D. S., Marques Jr, J., Matias, S. S. R., Barrón, V., Torrent, J., Baffa, O., Oliveira, L. D. (2010). Correlation of properties of Brazilian Haplustalfs with magnetic susceptibility measurements. Soil Use and Management, 26, p.425-431. https://doi.org/10.1111/j.1475-2743.2010.00294.x
Sneath, P. H., Sokal, R. R. (1973). Numerical taxonomy: the principles and practice of numerical classification. San Francisco: W. H. Freeman; 573p.
Sohrabian, B. (2021). Geostatistical prediction through convex combination of Archimedean copulas. Spatial Statistics 41, 100488. https://doi.org/10.1016/j.spasta.2020.100488
Sokal, R. R., Rohlf, F. J. (1962). The comparison of dendrograms by objeticve methods. Taxon 11, 30-40p. https://doi.org/10.2307/1217208
Souza, Z. M. D., Souza, G. S. D., Marques Júnior, J., Pereira, G. T. (2014). Número de amostras na análise geoestatística e na krigagem de mapas de atributos do solo. Ciência Rural, 44, 261-268p. https://doi.org/10.1590/S010384782014000200011
Sun, X. L., Lai, Y. Q., Ding, X., Wu, Y. J., Wang, H. L., Wu, C. (2022). Variability of soil mapping accuracy with sample sizes, modelling methods and landform types in a regional case study. Catena 213, 106217. https://doi.org/10.1016/j.catena.2022.106217
Surfer for windows. Realese 7.0. (1999). Contouring and 3D surface mapping for scientist’s engineers. User’s guide. New York:Golden software, 619p.
Taghdis, S., Farpoor, M. H., Mahmoodabadi, M., Fekri, M. (2021). Monitoring magnetic susceptibility and spatial distribution of soil attributes in different land uses: a case study in an arid and semi-arid region, southern Iran. Arabian Journal of Geosciences 14, 970. https://doi.org/10.1007/s12517-021-07303-z
Teixeira, P. C. Donagemma, G. K.; Fontana, A.; Teixeira, W. G. (2017). Manual de métodos de análise de solo. 3. ed. Rio de Janeiro: Embrapa Solos, 573p.
Vogado, R. F., Souza, H. A., Matias, S. S.R.., Gualberto, A. V. S., da Cunha, J. R., Leite, L. F. C. (2020). Spatial variability of carbon and nitrogen stocks in integrated management systems and pasture in a cerrado region. Research, Society and Development 9, e67291110220. http://dx.doi.org/10.33448/rsd-v9i11.10220
Warrick, A. W., Nielsen, D. R. (1980). Spatial variability of soil physical properties in the field. In: HILLEL, D. (Ed.). Applications of soil physics. New York: Academic Press, cap. 2, p. 319-344.
Zhou, Y., Zhang, Z., Rao, J., Chen, B., 2022. Predicting and mapping soil magnetic susceptibility in an agro-pastoral transitional zone: Influencing factors and implications. Soil and Tillage Research 219, 105352. https://doi.org/10.1016/j.still.2022.10535
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Copyright (c) 2025 Sammy Sidney Rocha Matias, Ana Alice Salmito Nolêto de Campos Ferreira, Ariane da Silva Lopes Rocha Ascenso, Maria de Fátima Marques Pires, Priscila Alves Barroso
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