Article
Performance Evaluation of Proximal Sensors for Soil
Assessment in Smallholder Farms in Embu
County, Kenya
Kristin Piikki
1,2,
*, Mats Söderström
1,2
, Jan Eriksson
3
, Jamleck Muturi John
4
,
Patrick Ireri Muthee
5
, Johanna Wetterlind
2
and Eric Lund
6
1
Regional Office for Africa, International Center for Tropical Agriculture (CIAT), Kasarani Rd.,
ICIPE Complex, P.O. Box 823-00621, Nairobi, Kenya; mats.soderstrom@slu.se
2
Department of Soil and Environment, Precision Agriculture and Pedometrics, Swedish University of
Agricultural Sciences (SLU), Box 234, SE-53223 Skara, Sweden; johanna.wetterlind@slu.se
3
Department of Soil and Environment, Biogeochemistry, Swedish University of Agricultural Sciences (SLU),
Box 7014, SE-75007 Uppsala, Sweden; jan.o.eriksson@slu.se
4
School of Agriculture, University of Embu (UoEm), P.O. Box 6-60100, Embu, Kenya; jjamkenya@yahoo.com
5
Ministry of Agriculture, Embu, Kenya; patrickireri66@gmail.com
6
Veris Technologies Inc., 1925 Clay Ridge Ct., Salina, KS 67401, USA; lunde@veristech.com
* Correspondence: kristin.piikki@slu.se; Tel.: +46-511-67-222
Academic Editor: Gonzalo Pajares Martinsanz
Received: 29 August 2016; Accepted: 8 November 2016; Published: 19 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.
Keywords: East Africa; proximal sensor; soil assessment; subsistence farming
1. Background
1.1. Soil Testing Is Important
Agriculture is the backbone and livelihood of a majority of the population in East Africa. Economic
and efficient farm production is highly determined by soil conditions. Soil testing is an important
procedure to undertake, since it determines the fertility status, i.e., the physical and chemical properties
that affect a soil’s suitability for growing plants. Soil health determines how well the soil can
function [
1
]. Different methods of soil assessment have been adopted over the years. An alternative
or complement to laboratory soil analyses could be to test the soil directly in the field, e.g., by using
handheld instruments. Knowledge of the local soil properties is crucial to farmers as it enables them to
determine best management practices. The main bottlenecks for soil testing among smallholders in
Sensors 2016, 16, 1950; doi:10.3390/s16111950 www.mdpi.com/journal/sensors
