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Open AccessArticle

Capability of Diffuse Reflectance Spectroscopy to Predict Soil Water Retention and Related Soil Properties in an Irrigated Lowland District of Southern Italy

1
Institute for Mediterranean Agriculture and Forest System, National Research Council (ISAFoM-CNR), via Patacca, 85, 80056 Ercolano (NA), Italy
2
Department of Science and Technology (DST), University of Sannio, via dei Mulini, 82100 Benevento, Italy
3
Water Research Institute, National Research Council (IRSA-CNR), V.le F. De Blasio, 5, 70132 Bari, Italy
4
Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, Campania University Luigi Vanvitelli, via Vivaldi 43, 81100 Caserta, Italy
*
Author to whom correspondence should be addressed.
Water 2019, 11(8), 1712; https://doi.org/10.3390/w11081712
Received: 26 June 2019 / Revised: 9 August 2019 / Accepted: 11 August 2019 / Published: 17 August 2019
(This article belongs to the Special Issue Evapotranspiration and Plant Irrigation Strategies)
In this study, we examined the potential of vis-NIR reflectance spectroscopy, coupled with partial least squares regression (PLSR) analysis, for the evaluation and prediction of soil water retention at field capacity (FC) and permanent wilting point (PWP) and related basic soil properties [organic carbon (OC), sand, silt, and clay contents] in an agricultural irrigated land of southern Italy. Soil properties were determined in the laboratory with reference to the Italian Official Methods for Soil Analysis. Vis-NIR reflectance spectra were measured in the laboratory, using a high-resolution spectroradiometer. All soil variables, with the exception of silt, evidently affected some specific spectral features. Multivariate calibrations were performed to predict the soil properties from reflectance spectra. PLSR was used to calibrate the spectral data using two-thirds of samples for calibration and one-third for validation. Spectroscopic data were pre-processed [multiplicative scatter correction (MSC), standard normal variance (SNV), wavelet detrending (WD), first and second derivative transformation, and filtering] prior to multivariate calibration. The results revealed very good models (2.0 < RPD < 2.5) for the prediction of FC, PWP and sand, and excellent (RPD > 2.5) models for the prediction of clay and OC, whereas a poor (RPD < 1.4) prediction model was obtained for silt. View Full-Text
Keywords: reflectance spectroscopy; soil texture; organic carbon; field capacity; permanent wilting point reflectance spectroscopy; soil texture; organic carbon; field capacity; permanent wilting point
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MDPI and ACS Style

Leone, A.P.; Leone, G.; Leone, N.; Galeone, C.; Grilli, E.; Orefice, N.; Ancona, V. Capability of Diffuse Reflectance Spectroscopy to Predict Soil Water Retention and Related Soil Properties in an Irrigated Lowland District of Southern Italy. Water 2019, 11, 1712.

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