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RESEARCH ARTICLE

Effects of soil composition and preparation on the prediction of particle size distribution using mid-infrared spectroscopy and partial least-squares regression

Leslie J. Janik A B C , José M. Soriano-Disla A B , Sean T. Forrester A and Michael J. McLaughlin A B
+ Author Affiliations
- Author Affiliations

A CSIRO Environmental Contaminant Mitigation and Technologies Program, CSIRO Land and Water, Waite Campus, Waite Road, Urrbrae, SA 5064, Australia.

B School of Agriculture, Food and Wine, University of Adelaide, Waite Campus, Waite Road, Urrbrae, SA 5064, Australia.

C Corresponding author. Email: les.janik@csiro.au

Soil Research 54(8) 889-904 https://doi.org/10.1071/SR16011
Submitted: 11 January 2016  Accepted: 25 July 2016   Published: 26 September 2016

Abstract

Soil composition and preparation can affect prediction accuracy using diffuse reflectance mid-infrared Fourier transform spectroscopy (DRIFTS). In the present study, we evaluated the effect of soil composition, preparation and carbonate content on the accuracy of particle size distribution (PSD) predictions in four contrasting sets of soils, including calcareous soils, using partial least-squares regression (PLSR). The soils were scanned as <2- and <0.1-mm fine-ground samples. Regression calibrations were derived for individual soil sets, as well as a composite of the four sets. Predictions for clay and sand for the <2-mm composite calibration resulted in good accuracy (coefficient of determination R2 = 0.78; ratio of the standard deviation of reference values to the prediction error (RPD) = 2.2), but were less accurate for clay in the calcareous soils (R2 = 0.70–0.78; RPD = 1.8–1.1) and similarly accurate for sand (R2 = 0.68–0.80; RPD = 1.7–2.2). Predictions for silt were poor. Accuracies improved by fine grinding (R2 = 0.88, RPD = 2.9 for clay; R2 = 0.84, RPD = 2.9 for sand). It was concluded that single, large and highly variable sets rather than site-specific calibrations could be used for the PSD predictions of specific soil sets. Changes in the PLSR loading weights, resulting from grinding, could be linked to an improved access of the infrared beam to the soil matrix by removal or dilution of surface coatings, resulting in a reduction of inter- and intraparticulate heterogeneity.

Additional keywords: calcareous soil, clay, multivariate methods, particle size analysis.


References

Arroyo LJ, Li H, Teppen BJ, Boyd SA (2005) A simple method for partial purification of reference clays. Clays and Clay Minerals 53, 511–519.
A simple method for partial purification of reference clays.CrossRef | 1:CAS:528:DC%2BD2MXhtFyht7vF&md5=9b24f55677603f1fc6a065ffe35c3e69CAS |

Ben Dor E, Irons JR, Epema JF (1999) Soil reflectance. In ‘Manual of remote sensing: remote sensing for the earth sciences. Vol. 3’. pp. 111–188. (John Wiley & Sons, New York, NY)

Boivin P, Garnier P, Tessier D (2004) Relationship between clay content, clay type, and shrinkage properties of soil samples. Soil Science Society of America Journal 68, 1145–1153.
Relationship between clay content, clay type, and shrinkage properties of soil samples.CrossRef | 1:CAS:528:DC%2BD2cXlvVKis7s%3D&md5=64081d2e6095955325c4fa9514f1210fCAS |

Bowman G, Hutka J (2002) Particle size analysis. In ‘Soil physical measurement and interpretation for land evaluation’. (Eds N McKenzie, K Coughlan, H Cresswell) pp. 224–239. (CSIRO Publishing: Melbourne, Vic.)

Bricklemyer RS, Brown DJ (2010) On-the-go VisNIR: Potential and limitations for mapping soil clay and organic carbon. Computers and Electronics in Agriculture 70, 209–216.
On-the-go VisNIR: Potential and limitations for mapping soil clay and organic carbon.CrossRef |

Guerrero C, Zornoza R, Gómez I, Mataix-Beneyto J (2010) Spiking of NIR regional models using samples from target sites: Effect of model size on prediction accuracy. Geoderma 158, 66–77.

Isbell R (2002) ‘The Australian soil classification.’ (CSIRO Publishing: Melbourne, Vic.)

Janik LJ, Merry RH, Skjemstad JO (1998) Can mid infrared diffuse reflectance analysis replace soil extractions? Australian Journal of Experimental Agriculture 38, 681–696.
Can mid infrared diffuse reflectance analysis replace soil extractions?CrossRef |

Janik LJ, Merry RH, Forrester ST, Lanyon DM, Rawson A (2007) Rapid prediction of soil water retention using mid infrared spectroscopy. Soil Science Society of America Journal 71, 507–514.
Rapid prediction of soil water retention using mid infrared spectroscopy.CrossRef | 1:CAS:528:DC%2BD2sXjsVSqs7Y%3D&md5=2d890714a912890eae36e24ee18e6d06CAS |

Janik LJ, Forrester ST, Rawson A (2009) The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks (PLS-NN) analysis. Chemometrics and Intelligent Laboratory Systems 97, 179–188.
The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks (PLS-NN) analysis.CrossRef | 1:CAS:528:DC%2BD1MXmtlWmtLY%3D&md5=9b1e30f7a3a7114743383744741e1742CAS |

Kennard RW, Stone LA (1969) Computer aided design of experiments. Technometrics 11, 137–148.
Computer aided design of experiments.CrossRef |

Kunze GW, Dixon JB (1986) Pretreatment for mineralogical analysis. In ‘Methods of soil analysis, part 1. Physical and mineralogical methods’. 2nd edn. (Ed. A Klute) pp. 91–100. (American Society of Agronomy, Inc. and the Soil Science Society of America, Inc.: Madison, WI)

McKenzie N, Coughlan K, Cresswell H (2002) Particle size analysis. In ‘Soil physical measurement and interpretation for land evaluations’. pp. 224–239. (CSIRO Publishing: Melbourne)

Nguyen TT, Janik LJ, Raupach M (1991) Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy in soil studies. Australian Journal of Soil Research 29, 49–67.
Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy in soil studies.CrossRef | 1:CAS:528:DyaK3MXhvV2nsbk%3D&md5=74c03fbfad1ac80c49c0ca2f2a7c6895CAS |

Nocita M, Stevens A, van Wesemael B, Aitkenhead M, Bernard B, Barthès M, Ben Dor E, Brown DJ, Clairotte M, Csorba A, Dardenne P, Demattê JAM, Genot V, Guerrero C, Knadel M, Montanarella L, Noon C, Ramirez-Lopez L, Robertson J, Sakai H (2015) Soil spectroscopy: an alternative to wet chemistry for soil monitoring. Advances in Agronomy 132, 139–159.
Soil spectroscopy: an alternative to wet chemistry for soil monitoring.CrossRef |

Reeves JB (2010) Near-versus mid-infrared diffusive reflectance spectroscopy for soil analysis emphasizing carbon and laboratory versus on-site analysis: where are we and what needs to be done? Geoderma 158, 3–14.
Near-versus mid-infrared diffusive reflectance spectroscopy for soil analysis emphasizing carbon and laboratory versus on-site analysis: where are we and what needs to be done?CrossRef | 1:CAS:528:DC%2BC3cXnvFWhsr0%3D&md5=f47e0e7d5abea4031f1816e97123b01eCAS |

Sherrod LA, Dunn G, Peterson GA, Kolberg RL (2002) Inorganic carbon analysis by modified pressure calcimeter method. Soil Science Society of America Journal 66, 299–305.
Inorganic carbon analysis by modified pressure calcimeter method.CrossRef | 1:CAS:528:DC%2BD38XlslOquro%3D&md5=197d934812385a7d9aab826d7d3c4780CAS |

Soriano-Disla JM, Janik L, Viscarra Rossel RA, McDonald LM, McLaughlin MJ (2014) The performance of visible, near and mid-infrared spectroscopy for prediction of soil physical, chemical and biological properties. Applied Spectroscopy Reviews 49, 139–186.
The performance of visible, near and mid-infrared spectroscopy for prediction of soil physical, chemical and biological properties.CrossRef | 1:CAS:528:DC%2BC3sXhtVCrtLfF&md5=5ffce62d4cf9e24cb39bdfa6cd34e085CAS |

Stenberg B, Viscarra-Rossel RA, Mouazen AM, Wetterling J (2010) Visible and near-infrared spectroscopy in soil science. Advances in Agronomy 107, 163–215.
Visible and near-infrared spectroscopy in soil science.CrossRef | 1:CAS:528:DC%2BC3cXht1yht7bE&md5=90cd822a8ac5aeee81175c4b196fa4f4CAS |

Stumpe B, Weihermüller L, Marschner B (2011) Sample preparation and selection for qualitative and quantitative analyses of soil organic carbon with mid-infrared reflectance spectroscopy. European Journal of Soil Science 62, 849–862.
Sample preparation and selection for qualitative and quantitative analyses of soil organic carbon with mid-infrared reflectance spectroscopy.CrossRef | 1:CAS:528:DC%2BC38Xmt1answ%3D%3D&md5=1edc3544d3f2f8b45339a0fb2f5cd7f6CAS |

Sudduth KA, Hummel JW (1996) Geographic operating range evaluation of a NIR soil sensor. Transactions of the American Society of Agricultural Engineers 39, 1599–1604.
Geographic operating range evaluation of a NIR soil sensor.CrossRef |

Tisdall JM, Oades JM (1982) Organic matter and water-stable aggregates in soils. Journal of Soil Science 33, 141–163.
Organic matter and water-stable aggregates in soils.CrossRef | 1:CAS:528:DyaL38XlsVels7w%3D&md5=177f36ec03e780b29b6204cb7a6e6294CAS |

USDA Natural Resources Conservation Service, National Soil Survey Center (1996) Particle-size analysis. In ‘Soil survey laboratory methods manual’. Soil Survey Investigation Report No. 42, Version 3.0. (USDA: Washington DC)

Viscarra Rossel RA, Webster R (2012) Predicting soil properties from the Australian soil visible-near infrared spectroscopic database. European Journal of Soil Science 63, 848–860.
Predicting soil properties from the Australian soil visible-near infrared spectroscopic database.CrossRef |

Viscarra Rossel RA, Cattle SR, Ortega A, Fouad Y (2009) In situ measurements of soil colour, mineral composition and clay content by vis-NIR spectroscopy. Geoderma 150, 253–266.
In situ measurements of soil colour, mineral composition and clay content by vis-NIR spectroscopy.CrossRef | 1:CAS:528:DC%2BD1MXkslOkt7k%3D&md5=4452fb0fbb4c85467b556d60cc5aaa8bCAS |

Waiser TH, Morgan CLS, Brown DJ, Hallmark CT (2007) In situ characterization of soil clay content with visible near-infrared diffuse reflectance spectroscopy. Soil Science Society of America Journal 71, 389–396.
In situ characterization of soil clay content with visible near-infrared diffuse reflectance spectroscopy.CrossRef | 1:CAS:528:DC%2BD2sXjsVSru70%3D&md5=69e259e65127fd5d56e8adf76553b604CAS |

Williams PC (1987) Variables affecting near-infrared reflectance spectroscopy. In ‘Near-infrared technology in the agricultural and food industries’. (Eds PC Williams, KH Norris) pp. 143–167. (American Association of Cereal Chemists Inc.: St Paul, MN)



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