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Sensors 2016, 16(11), 1950; doi:10.3390/s16111950

Performance Evaluation of Proximal Sensors for Soil Assessment in Smallholder Farms in Embu County, Kenya

1
Regional Office for Africa, International Center for Tropical Agriculture (CIAT), Kasarani Rd., ICIPE Complex, P.O. Box 823-00621, Nairobi, Kenya
2
Department of Soil and Environment, Precision Agriculture and Pedometrics, Swedish University of Agricultural Sciences (SLU), Box 234, SE-53223 Skara, Sweden
3
Department of Soil and Environment, Biogeochemistry, Swedish University of Agricultural Sciences (SLU), Box 7014, SE-75007 Uppsala, Sweden
4
School of Agriculture, University of Embu (UoEm), P.O. Box 6-60100, Embu, Kenya
5
Ministry of Agriculture, Embu, Kenya
6
Veris Technologies Inc., 1925 Clay Ridge Ct., Salina, KS 67401, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
Received: 29 August 2016 / Revised: 1 November 2016 / Accepted: 8 November 2016 / Published: 19 November 2016
(This article belongs to the Collection Sensors in Agriculture and Forestry)
View Full-Text   |   Download PDF [9242 KB, uploaded 21 November 2016]   |  

Abstract

Four 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. View Full-Text
Keywords: East Africa; proximal sensor; soil assessment; subsistence farming East Africa; proximal sensor; soil assessment; subsistence farming
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MDPI and ACS Style

Piikki, K.; Söderström, M.; Eriksson, J.; Muturi John, J.; Ireri Muthee, P.; Wetterlind, J.; Lund, E. Performance Evaluation of Proximal Sensors for Soil Assessment in Smallholder Farms in Embu County, Kenya. Sensors 2016, 16, 1950.

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