Journal
BIOSYSTEMS ENGINEERING
Volume 177, Issue -, Pages 90-100Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.biosystemseng.2018.06.008
Keywords
PLS regression analysis; Sand; Clay; Vis-NIR spectroscopy
Funding
- ICT-AGRI (The European Commission's ERA-NET scheme under the 7th Framework Programme) [62-FARMFUSE]
- TUBITAK (The Scientific and Technological Research Council of Turkey) [1120471]
- UK Department of Environment, Food and Rural Affairs [IF0208]
- FWO [G0F9216N]
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The aim of this research was to examine the potential of visible and near infrared (Vis-NIR) spectroscopy for the prediction and mapping of sand and clay fractions of soils in one irrigated field having clay texture in Karacabey district of Bursa Province, Turkey. Eighty six soil samples, collected from the study area, were divided into calibration (80%) and validation (20%) sets. A partial least squares regression (PLSR) with leave-one-out cross-validation analysis was carried out using the calibration set, and the resulting model prediction ability was tested using the prediction set. Models developed were used to predict sand and clay content using laboratory spectra and spectra collected on-line from the field. Results showed an excellent laboratory prediction performance for both sand (regression coefficient (R-2) = 0.90, root mean square error of prediction (RMSEP) = 2.91% and ratio of prediction deviation (RPD) = 3.25 in cross-validation; R-2 = 0.81, RMSEP = 3.84% and RPD = 2.33 in the prediction set) and clay (R-2 = 0.91, RMSEP = 2.67% and RPD = 3.51 in cross validation; R-2 = 0.85, RMSEP = 3.40% and RPD = 2.66 in the prediction set). On-line predictions were less accurate than the laboratory results, although the online predictions were still very good (RPD = 2.25-2.31). Kappa statistics showed reasonable similarities between measured and predicted maps, particularly for those obtained with laboratory scanning. This study demonstrated that soil sand and clay can be successfully measured and mapped using Vis-NIR spectroscopy under both laboratory and on-line scanning conditions. (C) 2018 IAgrE. Published by Elsevier Ltd. All rights reserved.
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