Soil organic carbon prediction with terrain derivatives using geostatistics and sequential Gaussian simulation

Autor: Kingsley John, Isong Isong Abraham, Ndiye Michael Kebonye, Prince Chapman Agyeman, Esther Okon Ayito, Ahado Samuel Kudjo
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Journal of the Saudi Society of Agricultural Sciences, Vol 20, Iss 6, Pp 379-389 (2021)
Druh dokumentu: article
ISSN: 1658-077X
DOI: 10.1016/j.jssas.2021.04.005
Popis: This current study investigated the relationship between soil organic carbon (SOC) and terrain derivatives on soil developed on dissimilar lithology while comparing the best modelling approach. Sixty (n = 60) bulk soil samples were taken from the depth of 0–30 cm according to five identified basement complex materials and analyzed for SOC. The models considered are ordinary kriging (OK), principal components kriging (PCA_OK) and regression kriging (RK). For the prediction's accuracy, 2-fold, and leave one out (LOOCV) cross-validation was carried out. The study indicated SOC in soil developed on granite gneiss (2.12%) and Biottite hornblende gneiss (2.05%) to be significantly (p
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