Table of Contents
ISRN Soil Science
Volume 2013 (2013), Article ID 720589, 11 pages
Research Article

Prediction of Soil Organic Carbon for Ethiopian Highlands Using Soil Spectroscopy

1Centre for Development and Environment, University of Bern, Hallerstrasse 10, CH-3012 Bern, Switzerland
2Amhara Regional Agricultural Research Institute, P.O. Box 527, Bahir Dar, Ethiopia
3Bahir Dar University, P.O. Box 79, Bahir Dar, Ethiopia

Received 30 April 2013; Accepted 30 May 2013

Academic Editors: M. Bernoux and G. Broll

Copyright © 2013 Tadele Amare et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used. The stability of models was evaluated using coefficient of determination (), root mean square error (RMSE), and the ratio performance deviation (RPD). The (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9), Maybar (84. 0.57, 2.5), Megech (85, 0.15, 2.6), and Wondo Genet (86, 0.52, 2.7) indicating that the models were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.