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Application of the Random Forest Model to Predict the Plasticity State of Vertisols

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Vertisol plasticity is related to moisture content, and it requires an in-depth physicochemical characterization. This information allows us to use the land under the most adequate conditions and avoid soil physical degradation, especially its compaction. The objective of this study was to characterize the Vertisol in the Moroccan region of Doukkala-Abda and to predict soil plasticity based on the physicochemical parameters of soil, such as texture, electrical conductivity, Soil Organic Matter (SOM) and other chemical parameters for 120 samples. Determination of soil plasticity using Atterberg limits is a challenging and time-consuming method. Thus, this study aimed to develop a new model that can predict soil plasticity using the Random Forest algorithm. The soils presented homogeneity in the majority of physicochemical parameters, except a significant difference observed in the SOM and the electrical conductivity, which in turn influenced the soil plasticity state. The results showed significant and positive correlations between SOM, Soil Clay Content (SCC), Electrical Conductivity (EC), and plasticity in the Vertisol fields of the region. For the training phase, the model gave excellent results with a coefficient of determination of 0.995 and an RMSE of 0.164. Almost the same results were observed in the validation phase with a coefficient of determination of 0.974 and an RMSE of 0.361, which shows that the model succeeded in predicting plasticity in both phases. On the basis of these results, this model can be used for the plasticity prediction using other physicochemical parameters and the Random Forest Model. The prediction of soil plasticity is an important parameter to respect the timing of introducing machines/tools in the fields and avoid Vertisol degradation.
Rocznik
Strony
36--46
Opis fizyczny
Bibliogr. 64 poz., rys., tab.
Twórcy
  • Laboratory of Geosciences and Environment Technics, Chouaib Doukkali University, Faculty of Science, El-Jadida, Morocco
  • Laboratory of Agricultural Engineering, National Institute of Agricultural Research, Settat, 26000, Morocco
  • Laboratory of Geosciences & Environment research, Faculty of Science and Technique, Hassan I University, Settat, Morocco
  • Laboratory of Geosciences and Environment Technics, Chouaib Doukkali University, Faculty of Science, El-Jadida, Morocco
  • Laboratory of Agricultural Engineering, National Institute of Agricultural Research, Settat, 26000, Morocco
  • Laboratory of Geosciences and Environment Technics, Chouaib Doukkali University, Faculty of Science, El-Jadida, Morocco
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Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3b95caec-d62d-434a-91cf-3c1fecf8e293
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