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Author (up) Erktan, A.; Legout, C.; De Danieli, S.; Daumergue, N.; Cecillon, L. openurl 
  Title Comparison of infrared spectroscopy and laser granulometry as alternative methods to estimate soil aggregate stability in Mediterranean badlands Type Journal Article
  Year 2016 Publication Geoderma Abbreviated Journal  
  Volume 271 Issue Pages 225-233  
  Abstract Soil aggregate stability is a key indicator of soil resistance to erosion, but its measurement remains fastidious for large scale uses. Alternative time and cost-effective methods are thus needed. Our objective was to assess and compare the efficiency of laser granulometry (LG) and soil mid- and near-infrared spectroscopy (MIR/NIR) as alternative methods to assess soil aggregate stability in Mediterranean badland soils. A collection of 75 badland soil samples was used, showing wide variations in soil aggregate stability. Three different categories of measurements were performed: (i) the aggregate breakdown kinetics of the [<1 mm] size fraction under stirring and sonication, tracked by repeated particle size distribution measurements, using LG, (ii) mid-(diffuse-MIR-DR and attenuate transmitted reflectance MIR-ATR) and near-(NIR-DR) infrared spectra of the fine soil fraction [<2 mm] and (iii) the soil aggregate [3-5 mm] stability, using the standardized method (ISO/FDIS 10930, 2012). Partial least squares regression models were used to predict soil aggregate stability using LG data and infrared spectra. Results showed that NIR-DR and MIR-ATR data provided the best prediction model for soil aggregate stability values (RPD = 2.61 & 2.74; R-2 = 0.85 & 810.87), followed by MIR-DR data (RPD = 2.24; R-2 = 0.89) and finally LG data (RPD = 2.12; R-2 = 0.80). For a quantitative use of the models to assign soil samples to standardized soil aggregate stability classes (ISO/FDIS 10930, 2012), infrared spectra also provided the best accuracy, with a misclassification rate below 30% for NIR-DR and MIR-ATR models, while it reached 43% with the LG-based model. The combination of IR and LG data did not yield a better prediction model for soil aggregate stability values and classes, Infrared-based method also provided best results in terms of time-saving strategy, reducing the measurement time to 8 min only. To conclude, infrared spectra (NIR-DR and MIR-ATR) outperformed LG-data to predict soil aggregate stability. Further development of this technique would require calibrating a set of soil-type specific prediction models for a wide range of soil types. (C) 2016 Elsevier B.V. All rights reserved.  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0016-7061 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000373541800024 HYDRIMZ Approved no  
  Call Number IGE @ juliette.blanchet @ Serial 4117  
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