<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"><identifier identifierType="DOI">10.7910/DVN/KLPHCG</identifier><creators><creator><creatorName nameType="Organizational">International Center for Tropical Agriculture (CIAT)</creatorName></creator><creator><creatorName nameType="Organizational">Selian Agricultural Research Institute (SARI)</creatorName></creator></creators><titles><title>Soil Survey to Characterize 2 Sentinel Sites (CIAT)</title></titles><publisher>Harvard Dataverse</publisher><publicationYear>2017</publicationYear><subjects><subject>Agricultural Sciences</subject><subject>Social Sciences</subject><subject schemeURI="http://aims.fao.org/aos/agrovoc/c_7198" subjectScheme="AGROVOC">soil analysis</subject><subject schemeURI="http://aims.fao.org/aos/agrovoc/c_7608" subjectScheme="AGROVOC">TANZANIA</subject><subject schemeURI="http://aims.fao.org/aos/agrovoc/c_2442" subjectScheme="AGROVOC">EAST AFRICA</subject><subject schemeURI="http://aims.fao.org/aos/agrovoc/c_166" subjectScheme="AGROVOC">AFRICA SOUTH OF SAHARA</subject><subject schemeURI="http://aims.fao.org/aos/agrovoc/c_165" subjectScheme="AGROVOC">AFRICA</subject><subject schemeURI="http://aims.fao.org/aos/agrovoc/c_8679" subjectScheme="AGROVOC">Agricultural research</subject></subjects><contributors><contributor contributorType="ContactPerson"><contributorName nameType="Personal">Kihara, Job</contributorName><givenName>Job</givenName><familyName>Kihara</familyName><affiliation>International Center for Tropical Agriculture (CIAT)</affiliation></contributor><contributor contributorType="Producer"><contributorName nameType="Organizational">International Center for Tropical Agriculture (CIAT)</contributorName></contributor><contributor contributorType="Producer"><contributorName nameType="Organizational">Selian Agricultural Research Institute (SARI)</contributorName></contributor><contributor contributorType="ProjectLeader"><contributorName nameType="Organizational">Kihara, Job (International Center for Tropical Agriculture (CIAT))</contributorName></contributor><contributor contributorType="Researcher"><contributorName nameType="Personal">Winowiecki, Leigh (World Agroforestry Center (ICRAF))</contributorName><givenName>Leigh (World Agroforestry Center (ICRAF))</givenName><familyName>Winowiecki</familyName></contributor><contributor contributorType="Researcher"><contributorName nameType="Organizational">Masawe, P. (Selian Agricultural Research Institute (SARI))</contributorName></contributor><contributor contributorType="Distributor"><contributorName nameType="Organizational">International Food Policy Research Institute (IFPRI)</contributorName></contributor></contributors><dates><date dateType="Issued">2015-12-07</date><date dateType="Created">2015-07-12</date><date dateType="Submitted">2017-08-01</date><date dateType="Updated">2019-04-10</date><date dateType="Collected">2014-03-01/2014-06-30</date></dates><resourceType resourceTypeGeneral="Dataset">Agronomy data</resourceType><sizes><size>535552</size></sizes><formats><format>application/vnd.ms-excel</format></formats><version>1.1</version><rightsList><rights rightsURI="info:eu-repo/semantics/closedAccess"/><rights/></rightsList><descriptions><description descriptionType="Abstract">&lt;p>The Land Degradation Surveillance Framework (LDSF) used by AfSIS was employed to conduct a systematic biophysical assessment of various ecological and soil health metrics. The LDSF was based on a hierarchical spatially stratified, random sampling approach consisting of 100 km2 sentinel landscapes, which were statistically representative of the variability in climate, topography, and vegetation of the study area under consideration. To predict soil properties for areas where samples were not collected, relatively large number of samples from representative locations were taken. To overcome the huge cost of analyzing large soil samples using conventional laboratory techniques, near and mid-infrared spectroscopy approaches were used. &lt;/p>&#xd;
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&lt;p>&lt;h4>About the project &lt;/h4>&lt;/p>&#xd;
&lt;p>&lt;b>Project title: Identification of the Key Biophysical Production Constraints to Crops and Livestock at Farm and Landscape Levels&lt;/b>&lt;/p>&#xd;
&lt;p>&lt;b> Project abstract &lt;/b>&lt;/p>&#xd;
&lt;p>The project undertakes soil survey to characterize 2 sentinel sites (Long and Matufa); and agronomic survey to estimate farmers' actual yield.&lt;/p>&#xd;
&lt;p>&lt;b>Project website&lt;/b>:  &lt;http://africa-rising.net/&lt;/a>&lt;/p>&#xd;
&lt;p> &lt;b>Project start date&lt;/b>: 01/11/2012 &lt;/p>&#xd;
&lt;p>&lt;b> Project end date &lt;/b>: 01/10/2013 &lt;/p</description><description descriptionType="TechnicalInfo">Microsoft Excel, 2016</description></descriptions><geoLocations/><fundingReferences><fundingReference><funderName>United States Agency for International Development (USAID)</funderName></fundingReference><fundingReference><funderName>United States Agency for International Development (USAID)</funderName></fundingReference></fundingReferences></resource>