Datasets

date: 2019

Total is 119 Results
Environmental Covariate Data for Spatial Prediction of Soil Properties for the Busia Area, Kenya

10.4231/7F9R-4W74

Darrell Schulze, 0000-0001-9278-2457, Joshua Minai

11/18/2019

Environmental covariates were carefully selected to represent factors of soil formation: climate, relief, organisms, and time.

Agronomy Busia Area Environmental Covariates Kenya Landsat Terrain Attributes WorldClim

Environmental Covariate Data for the Disaggregation of the Reconnaissance Soil Map of the Busia Area, Kenya

10.4231/4DBT-2W68

Darrell Schulze, 0000-0001-9278-2457, Joshua Minai

11/18/2019

Enviromental covariate data used to develop a digital model that represents the landscape and environmental conditions of the Busia landscape.

Agronomy Busia Area Digital Soil Mapping Disaggregate Geographic Information Systems (GIS) Kenya Soil Land Rule-Based Approach

Busia Fuzzy Soil Class Map

10.4231/TDN8-PM14

Darrell Schulze, 0000-0001-9278-2457, Joshua Minai

11/18/2019

Map based on the concept that soil classes can be spatially inferred from soil-related environmental conditions.

Agronomy Busia Area Digital Soil Mapping Fuzzy Membership Values Geographic Information Systems (GIS) Kenya SoLIM

Busia Land Quality Maps

10.4231/KYJ5-S732

Darrell Schulze, 0000-0001-9278-2457, Joshua Minai

11/18/2019

Independent diagnostic criteria reflecting limitations for land use.

Agronomy Busia Area Decision Matrix Kenya Land Evaluation Key Map Unit

Soil Property Data for Spatial Prediction of Soil Properties for the Busia Area, Kenya

10.4231/00R1-HM25

Darrell Schulze, 0000-0001-9278-2457, Joshua Minai

11/18/2019

Soil property data mined from the Reconnaissance Soil Survey of the Busia Area (quarter degree sheet No. 101) for digital soil mapping.

Agronomy Busia Area Digital Soil Mapping Equal Area Quadratic Smoothing Spline Function Kenya R ithir Package RStudio

Survey on Crop Residues for Cattle Feeding in Niger

10.4231/GE83-HA69

Ousmane Seyni Diakite

10/18/2019

The specific objectives were to identify farmers’ and stover traders’ preferences on sorghum stover varieties. A Participatory Rural Appraisal (PRA) consisting of focus group discussions followed by semi-structured interviews, was conducted.

Cattle Farmer Survey Forage Preference Livestock National Agricultural Research Institute of Niger (INRAN) Niger Sorghum Sorghum Trait Development Pipeline West Africa

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Results 51 - 60 of 119