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dc.contributor.authorMuturi, Jamleck
dc.contributor.authorKristin, Piikki
dc.contributor.authorMats, Söderström
dc.contributor.authorEriksson, Jan
dc.contributor.authorMuthee, Patrick I.
dc.contributor.authorWetterlind, Johanna
dc.contributor.authorLund, Eric
dc.date.accessioned2016-11-24T06:12:58Z
dc.date.available2016-11-24T06:12:58Z
dc.date.issued2016
dc.identifier.citationSensors 2016, 16, 1950en_US
dc.identifier.urihttp://hdl.handle.net/123456789/1261
dc.descriptiondoi:10.3390/s16111950en_US
dc.description.abstractFour proximal soil sensors were tested at four smallholder farms in Embu County, Kenya: a portable X-ray fluorescence sensor (PXRF), a mobile phone application for soil color determination by photography, a dual-depth electromagnetic induction (EMI) sensor, and a LED-based soil optical reflectance sensor. Measurements were made at 32–43 locations at each site. Topsoil samples were analyzed for plant-available nutrients (N, P, K, Mg, Ca, S, B, Mn, Zn, Cu, and Fe), pH, total nitrogen (TN) and total carbon (TC), soil texture, cation exchange capacity (CEC), and exchangeable aluminum (Al). Multivariate prediction models of each of the lab-analyzed soil properties were parameterized for 576 sensor-variable combinations. Prediction models for K, N, Ca and S, B, Zn, Mn, Fe, TC, Al, and CEC met the setup criteria for functional, robust, and accurate models. The PXRF sensor was the sensor most often included in successful models. We concluded that the combination of a PXRF and a portable soil reflectance sensor is a promising combination of handheld soil sensors for the development of in situ soil assessments as a field-based alternative or complement to laboratory measurements.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.subjectEast Africaen_US
dc.subjectproximal sensoren_US
dc.subjectsoil assessmenten_US
dc.subjectsubsistence farmingen_US
dc.titlePerformance Evaluation of Proximal Sensors for Soil Assessment in Smallholder Farms in Embu County, Kenyaen_US
dc.typeArticleen_US


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