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dc.contributor.authorShisanya, C.A.
dc.contributor.authorOkeyo, J.M.
dc.contributor.authorShepherd, K. D.
dc.contributor.authorWamicha, W. N.
dc.date.accessioned2014-07-01T08:23:03Z
dc.date.available2014-07-01T08:23:03Z
dc.date.issued2006
dc.identifier.citationAfrican Crop Science Journal, Vol. 14, No. 1, 2006, pp. 27-36en_US
dc.identifier.issn1021-9730
dc.identifier.other2072-6589
dc.identifier.urihttp://www.bioline.org.br/request?cs06003
dc.identifier.urihttp://ir-library.ku.ac.ke/handle/123456789/10237
dc.description.abstractIn 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.en_US
dc.language.isoenen_US
dc.subjectMixed effectsen_US
dc.subjectmodelingen_US
dc.subjectsemivarianceen_US
dc.titleSpatial Variation in Soil Organic Carbon within Smallholder Farms in Western Kenya: A geospatial Approachen_US
dc.typeArticleen_US


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