Aarhus University Seal / Aarhus Universitets segl

Mogens Humlekrog Greve

The Relation between Soil Water Repellency and Water Content can be Predicted by Vis–NIR Spectroscopy

Publikation: KonferencebidragKonferenceabstrakt til konferenceForskning

Standard

The Relation between Soil Water Repellency and Water Content can be Predicted by Vis–NIR Spectroscopy. / Hermansen, Cecilie; Møldrup, Per; Müller, Karin; Knadel, Maria; Greve, Mogens Humlekrog; de Jonge, Lis Wollesen.

2019. Abstract fra 2018 - 2019 SSSA International Soils Meeting , San Diego, USA.

Publikation: KonferencebidragKonferenceabstrakt til konferenceForskning

Harvard

Hermansen, C, Møldrup, P, Müller, K, Knadel, M, Greve, MH & de Jonge, LW 2019, 'The Relation between Soil Water Repellency and Water Content can be Predicted by Vis–NIR Spectroscopy', 2018 - 2019 SSSA International Soils Meeting , San Diego, USA, 06/01/2019 - 09/01/2019.

APA

Hermansen, C., Møldrup, P., Müller, K., Knadel, M., Greve, M. H., & de Jonge, L. W. (2019). The Relation between Soil Water Repellency and Water Content can be Predicted by Vis–NIR Spectroscopy. Abstract fra 2018 - 2019 SSSA International Soils Meeting , San Diego, USA.

CBE

Hermansen C, Møldrup P, Müller K, Knadel M, Greve MH, de Jonge LW. 2019. The Relation between Soil Water Repellency and Water Content can be Predicted by Vis–NIR Spectroscopy. Abstract fra 2018 - 2019 SSSA International Soils Meeting , San Diego, USA.

MLA

Hermansen, Cecilie o.a.. The Relation between Soil Water Repellency and Water Content can be Predicted by Vis–NIR Spectroscopy. 2018 - 2019 SSSA International Soils Meeting , 06 jan. 2019, San Diego, USA, Konferenceabstrakt til konference, 2019.

Vancouver

Hermansen C, Møldrup P, Müller K, Knadel M, Greve MH, de Jonge LW. The Relation between Soil Water Repellency and Water Content can be Predicted by Vis–NIR Spectroscopy. 2019. Abstract fra 2018 - 2019 SSSA International Soils Meeting , San Diego, USA.

Author

Bibtex

@conference{3906b8deadc54698897ccc58f671752b,
title = "The Relation between Soil Water Repellency and Water Content can be Predicted by Vis–NIR Spectroscopy",
abstract = "Soils can be water repellent, when covered by hydrophobic organic matter. There are severalconsequences of soil water repellency (SWR), such as decreased crop yield, erosion and increasedrisk of ground watercontamination. The severity of SWR varies non-linearly with water content (w),and it is extremely laborious to obtain complete SWR-w curves. We combined a three-parametermoisture-dependent SWR (MD-SWR) model with visible near-infrared (vis–NIR) spectroscopy as afast and novel method to estimate the SWR-wcurve. The method was applied to a data set of 71 soilsamples, representing five dominant soil orders of the South Island of New Zealand (OC: 0.021 –0.147 kg kg-1, clay: 0.000 – 0.520 kg kg-1). The degree of SWR was measured at air-dry conditions(SWRAD), and at several water contents above air-dried conditions, obtained by adding water in smallincrements until the water content at which the soils became wettable (wNON) was reached. The threeparameterMD-SWR model was fitted to the measured SWR-w curves between the water content atair-dry conditions (wAD) and wNON. Then, the total SWR was derived as the trapezoidal integratedarea underneath the SWR-w curves (SWRAREA). Air-dried soil samples were scanned with a vis–NIRspectrometer (DS2500 spectrometer, Foss, Denmark) in the 400 – 2500 nm range. Each of the threeMD-SWR model parameters was correlated to vis–NIR spectra with partial least squares regressionand ten-fold cross validation (R2 between 0.56 and 0.71). Next, the predicted model parameter valueswere used to obtain vis–NIR predicted SWR-w curves between wAD and wNON, and SWRAREA wasderived from these curves. Results show that vis–NIR can predict the shape of the SWR-w curves aswell as SWRAREA (R2 = 0.56) across a highly variable dataset from a single vis–NIR scanning andone SWR measurement at air-dried conditions.",
author = "Cecilie Hermansen and Per M{\o}ldrup and Karin M{\"u}ller and Maria Knadel and Greve, {Mogens Humlekrog} and {de Jonge}, {Lis Wollesen}",
year = "2019",
language = "English",
note = "2018 - 2019 SSSA International Soils Meeting : SOILS ACROSS LATITUDES, SSSA2019 ; Conference date: 06-01-2019 Through 09-01-2019",
url = "https://www.sacmeetings.org/",

}

RIS

TY - ABST

T1 - The Relation between Soil Water Repellency and Water Content can be Predicted by Vis–NIR Spectroscopy

AU - Hermansen, Cecilie

AU - Møldrup, Per

AU - Müller, Karin

AU - Knadel, Maria

AU - Greve, Mogens Humlekrog

AU - de Jonge, Lis Wollesen

PY - 2019

Y1 - 2019

N2 - Soils can be water repellent, when covered by hydrophobic organic matter. There are severalconsequences of soil water repellency (SWR), such as decreased crop yield, erosion and increasedrisk of ground watercontamination. The severity of SWR varies non-linearly with water content (w),and it is extremely laborious to obtain complete SWR-w curves. We combined a three-parametermoisture-dependent SWR (MD-SWR) model with visible near-infrared (vis–NIR) spectroscopy as afast and novel method to estimate the SWR-wcurve. The method was applied to a data set of 71 soilsamples, representing five dominant soil orders of the South Island of New Zealand (OC: 0.021 –0.147 kg kg-1, clay: 0.000 – 0.520 kg kg-1). The degree of SWR was measured at air-dry conditions(SWRAD), and at several water contents above air-dried conditions, obtained by adding water in smallincrements until the water content at which the soils became wettable (wNON) was reached. The threeparameterMD-SWR model was fitted to the measured SWR-w curves between the water content atair-dry conditions (wAD) and wNON. Then, the total SWR was derived as the trapezoidal integratedarea underneath the SWR-w curves (SWRAREA). Air-dried soil samples were scanned with a vis–NIRspectrometer (DS2500 spectrometer, Foss, Denmark) in the 400 – 2500 nm range. Each of the threeMD-SWR model parameters was correlated to vis–NIR spectra with partial least squares regressionand ten-fold cross validation (R2 between 0.56 and 0.71). Next, the predicted model parameter valueswere used to obtain vis–NIR predicted SWR-w curves between wAD and wNON, and SWRAREA wasderived from these curves. Results show that vis–NIR can predict the shape of the SWR-w curves aswell as SWRAREA (R2 = 0.56) across a highly variable dataset from a single vis–NIR scanning andone SWR measurement at air-dried conditions.

AB - Soils can be water repellent, when covered by hydrophobic organic matter. There are severalconsequences of soil water repellency (SWR), such as decreased crop yield, erosion and increasedrisk of ground watercontamination. The severity of SWR varies non-linearly with water content (w),and it is extremely laborious to obtain complete SWR-w curves. We combined a three-parametermoisture-dependent SWR (MD-SWR) model with visible near-infrared (vis–NIR) spectroscopy as afast and novel method to estimate the SWR-wcurve. The method was applied to a data set of 71 soilsamples, representing five dominant soil orders of the South Island of New Zealand (OC: 0.021 –0.147 kg kg-1, clay: 0.000 – 0.520 kg kg-1). The degree of SWR was measured at air-dry conditions(SWRAD), and at several water contents above air-dried conditions, obtained by adding water in smallincrements until the water content at which the soils became wettable (wNON) was reached. The threeparameterMD-SWR model was fitted to the measured SWR-w curves between the water content atair-dry conditions (wAD) and wNON. Then, the total SWR was derived as the trapezoidal integratedarea underneath the SWR-w curves (SWRAREA). Air-dried soil samples were scanned with a vis–NIRspectrometer (DS2500 spectrometer, Foss, Denmark) in the 400 – 2500 nm range. Each of the threeMD-SWR model parameters was correlated to vis–NIR spectra with partial least squares regressionand ten-fold cross validation (R2 between 0.56 and 0.71). Next, the predicted model parameter valueswere used to obtain vis–NIR predicted SWR-w curves between wAD and wNON, and SWRAREA wasderived from these curves. Results show that vis–NIR can predict the shape of the SWR-w curves aswell as SWRAREA (R2 = 0.56) across a highly variable dataset from a single vis–NIR scanning andone SWR measurement at air-dried conditions.

M3 - Conference abstract for conference

T2 - 2018 - 2019 SSSA International Soils Meeting

Y2 - 6 January 2019 through 9 January 2019

ER -