Journal ArticleDOI
Proximal soil sensing of soil texture and organic matter with a prototype portable mid-infrared spectrometer
Nandkishor M. Dhawale,Viacheslav I. Adamchuk,Shiv O. Prasher,R. A. Viscarra Rossel,Ashraf A. Ismail,J. Kaur +5 more
TLDR
In this article, a prototype portable mid-IR spectrometer was used for direct measurements of soil reflectance and to model the spectra to predict sand, clay and soil organic matter (SOM) contents under a range of field soil water conditions.Abstract:
Summary
Recent advances in semiconductor technologies have given rise to the development of mid-infrared (mid-IR) spectrometers that are compact, relatively inexpensive, robust and suitable for in situ proximal soil sensing. The objectives of this research were to evaluate a prototype portable mid-IR spectrometer for direct measurements of soil reflectance and to model the spectra to predict sand, clay and soil organic matter (SOM) contents under a range of field soil water conditions. Soil samples were collected from 23 locations at different depths in four agricultural fields to represent a range of soil textures, from sands to clay loams. The particle size distribution and SOM content of 48 soil samples were measured in the laboratory by conventional analytical methods. In addition to air-dry soil, each sample was wetted with two different amounts of water before the spectroscopic measurements were made. The prototype spectrometer was used to measure reflectance (R) in the range between 1811 and 898 cm−1 (approximately 5522 to 11 136 nm). The spectroscopic measurements were recorded randomly and in triplicate, resulting in a total of 432 reflectance spectra (48 samples × three soil water contents × three replicates). The spectra were transformed to log10 (1/R) and mean centred for the multivariate statistical analyses. The 48 samples were split randomly into a calibration set (70%) and a validation set (30%). A partial least squares regression (PLSR) was used to develop spectroscopic calibrations to predict sand, clay and SOM contents. Results show that the portable spectrometer can be used with PLSR to predict clay and sand contents of either wet or dry soil samples with a root mean square error (RMSE) of around 10%. Predictions of SOM content resulted in RMSE values that ranged between 0.76 and 2.24%.read more
Citations
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Journal ArticleDOI
Climate-smart soils
Keith Paustian,Johannes Lehmann,Stephen M. Ogle,David S. Reay,G. Philip Robertson,Pete Smith +5 more
TL;DR: ‘state of the art’ soil greenhouse gas research is highlighted, mitigation practices and potentials are summarized, gaps in data and understanding are identified and ways to close such gaps are suggested through new research, technology and collaboration.
Journal ArticleDOI
How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal.
Pete Smith,Jean-François Soussana,Denis A. Angers,Louis A. Schipper,Claire Chenu,Daniel P. Rasse,Niels H. Batjes,Fenny van Egmond,Stephen McNeill,Matthias Kuhnert,Cristina Arias-Navarro,Jørgen E. Olesen,Ngonidzashe Chirinda,Dario A. Fornara,Eva K. Wollenberg,Jorge Álvaro-Fuentes,Alberto Sanz-Cobena,Katja Klumpp +17 more
TL;DR: A new vision for a global framework for MRV of SOC change is described, to support national and international initiatives seeking to effect change in the way the authors manage their soils.
Journal ArticleDOI
In situ and laboratory soil spectroscopy with portable visible-to-near-infrared and mid-infrared instruments for the assessment of organic carbon in soils
TL;DR: In this article, the potential of handheld MIR spectroscopy for soil organic carbon (SOC) estimation with field spectral data against parallel VIS-NIR measurements was evaluated.
Journal ArticleDOI
Assessment of soil properties in situ using a prototype portable MIR spectrometer in two agricultural fields
Wenjun Ji,Viacheslav I. Adamchuk,Asim Biswas,Nandkishor M. Dhawale,Bharath Sudarsan,Yakun Zhang,Raphael A. Viscarra Rossel,Zhou Shi +7 more
TL;DR: In this paper, a small portable prototype MIR (898-1811 cm −1 ) spectrometer was used to collect soil spectra from two agricultural fields (predominantly organic and mineral soils).
Journal ArticleDOI
Evaluation of the performance of portable visible-infrared instruments for the prediction of soil properties
José M. Soriano-Disla,José M. Soriano-Disla,L. Janik,L. Janik,Danielle J. Allen,Mike J. McLaughlin,Mike J. McLaughlin +6 more
TL;DR: In this article, the performance of portable/miniaturized mid-infrared (MIR) and VIS-NIR spectrometers was compared for the prediction of soil properties across a range of soils.
References
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Journal ArticleDOI
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TL;DR: PLS-regression (PLSR) as mentioned in this paper is the PLS approach in its simplest, and in chemistry and technology, most used form (two-block predictive PLS) is a method for relating two data matrices, X and Y, by a linear multivariate model.
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Journal ArticleDOI
Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties
TL;DR: In this article, partial least squares regression (PLSR) was used to construct calibration models which were independently validated for the prediction of various soil properties from the soil spectra, including soil pHCa,p H w, lime requirement (LR), organic carbon (OC), clay, silt, sand, cation exchange capacity, exchangeable calcium (Ca), exchangeable aluminium (Al), nitrate-nitrogen (NO3-N), available phosphorus (PCol), exchangeability potassium (K) and electrical conductivity (EC).
Journal ArticleDOI
Can mid infrared diffuse reflectance analysis replace soil extractions
TL;DR: It is described how mid infrared diffuse reflectance analysis can provide results comparable in accuracy with many traditional extractive and digestion laboratory methods in soil studies, with the possibility of either replacing or enhancing them.
Journal ArticleDOI
In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy
TL;DR: In this paper, the authors compared field spectra collected in situ to those collected in the laboratory at different depths, in triplicate, using principal component analysis and by using wavelength specific t-tests.