{"type": "FeatureCollection", "features": [{"id": "10.7910/DVN/GVNJAB", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:24:31Z", "type": "Dataset", "created": "2019-06-24", "title": "Physical topsoil  properties in Murugusi, Western Kenya", "description": "Open Access<b>General:</b> Lab determined topsoil bulk density, contents of sand, clay and organic carbon in Murugusi, W. Kenya, together with spatial coordinates of where the soil samples were taken (rounded to the closest center point of a 250 m \u00d7 250 m raster). All lab analyses were carried out at the ILRI/CIAT lab in Nairob, Kenya.  <br>  <b>Soil sampling:</b> At each sample location, one composite topsoil sample was taken; three cores of 7 cm in diameter taken within an area of one square meter. The soil was taken from 0-0.2 m depth below any organic (O) horizon.   <br>  <b>Determination of soil properties:</b> The bulk density of the soil was determined by taking two undisturbed soil samples (0-10 cm and 10-20 cm depth) of known volume (100 cm2) and weighting them after air drying. Soil fractions of clay (<0.002 mm) and sand (0.05-2 mm) were determined by the hydrometer method (Estefan et al., 2014), using 10% sodium hexametaphosphate as the dispersing agent. Soil pH was determined potentiometrically on a soil suspension of 1:2 (soil: water). Total carbon was measured after dry combustion using an elemental analyser (Elementar Vario max cube; ISO 10694, first edition 1995-03-01)  <br>  <b>Reference: </b>Estefan G., Sommer R., Ryan J. (2014) Analytical Methods for Soil-Plant and Water in Dry Areas. 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Verified: October 9, 2018.  <br>  <b>Acknowledgements: </b> We are deeply thankful for the good services provided by John Mukulama (soil sampling), John Yumbya Mutua (soil sampling) and Francis Mungthu Njenga (lab analyses) The project was carried out within the CGIAR Research Program on Water, Land and Ecosystems (WLE).", "keywords": ["Soil organic matter", "Agricultural Sciences", "Soil organic carbon", "sand", "Kenya", "Carbon", "Latin America and the Caribbean", "soil", "Soil", "Soil bulk density", "Sand", "soil organic matter", "Earth and Environmental Sciences", "Soil texture", "Murugusi", "Africa", "Clay", "Texture", "Western Kenya", "Agroecosystems and Sustainable Landscapes - ASL"], "contacts": [{"organization": "Piikki, Kristin, S\u00f6derstr\u00f6m, Mats, Sommer, Rolf, Da Silva, Mayesse,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/GVNJAB"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/GVNJAB", "name": "item", "description": "10.7910/DVN/GVNJAB", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/GVNJAB"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/ZJMJ7K", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:24:32Z", "type": "Dataset", "created": "2018-01-01", "title": "Predicted soil organic carbon (SOC) content (g/kg) and SOC stock (t/ha) in the Eastern Plains of Colombia", "description": "Open AccessMaps allocated in this repository were predicted using a digital soil mapping (DSM) approach (McBratney et al, 2003) based on random forest (Breiman, 2001). 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Suitable areas for commercial fish farming were derived from the combined suitability of five land-quality factors important for fish farming development and operation; net annual water loss from ponds through evaporation and seepage; soil and terrain suitability for ponds; potential for agriculture by-products and fertiliser inputs; potential for farm gate sales; and potential market demand. Yield estimations for carp were based on water temperature which in turn were predicted from air temperature. Mean maximum and minimum monthly air temperatures grids were provide by FAO's Agrometeorology group. In order to explore a range of commercial aquaculture possibilities by the use of the growth model, simulations were conducted for carp, assuming two different feeding levels and two harvesting weights (600 and 1,000 g). 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Suitable areas for commercial fish farming were derived from the combined suitability of five land-quality factors important for fish farming development and operation; net annual water loss from ponds through evaporation and seepage; soil and terrain suitability for ponds; potential for agriculture by-products and fertiliser inputs; potential for farm gate sales; and potential market demand. Yield estimations for Nile tilapia were based on water temperature which in turn were predicted from air temperature. Mean maximum and minimum monthly air temperatures grids were provide by FAO's Agrometeorology group. In order to explore a range of commercial aquaculture possibilities by the use of the growth model, simulations were conducted for Nile tilapia, assuming two different feeding levels and two harvesting weights (600 and 1,000 g). 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