Shisanya, C.A.Okeyo, J.M.Shepherd, K. D.Wamicha, W. N.2014-07-012014-07-012006African Crop Science Journal, Vol. 14, No. 1, 2006, pp. 27-361021-97302072-6589http://www.bioline.org.br/request?cs06003http://ir-library.ku.ac.ke/handle/123456789/10237In many farming landscapes across Sub-Saharan Africa (SSA), soil fertility has been on the decline with significant implications on crop productivity. However, even with such a decline, soil nutrient levels still differ significantly between farms, fields or within the same field. Knowledge of such spatial variability and relationships among soil properties is important in implementation of agricultural land management practices. In this study, the spatial variability of soil organic carbon (SOC) in two districts of western Kenya was modeled using the geostatistical theory of semivariography and mixed effects modeling. Soil organic C was found to be spatially correlated and the spatial structure modeled using experimental semivariograms fitted with spherical, exponential and ratio quadratic models. The nugget/sill ratios for all the three variogram models were between 50-60%, indicating moderate spatial correlation. It is suggested that future soil fertility should target individual fields, as a precision farming approach.enMixed effectsmodelingsemivarianceArticle