Soil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: recent advances - a review

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dc.contributor.authorBarra, Issam
dc.contributor.authorHaefele, Stephan M.
dc.contributor.authorSakrabani, Ruben
dc.contributor.authorKebede, Fassil
dc.date.accessioned2021-01-20T09:39:51Z
dc.date.available2021-01-20T09:39:51Z
dc.date.issued2020-12-30
dc.description.abstractOver the past two decades soil spectroscopy, particularly, in the infrared range, is becoming a powerful technique to simplify analysis relative to the traditional chemical methods. It is known as a rapid, cost-effective, quantitative and eco-friendly technique, which can provide hyperspectral data with narrow and numerous wavebands, both in the laboratory and in the field. In this context, the present article reviews the recent developments in mid and near infrared techniques coupled with chemometrics and machine learning tools in addition to the preprocessing transformations and variable selection strategies to diagnose soil physical and chemical properties. Both spectral techniques demonstrated a good ability to provide accurate predictions of specific properties. Moreover, the MIR spectroscopy outperformed NIR for the estimation of most indicators used for fertilizers recommendation. Herein, a detailed overview on the opportunities and challenges that soil spectroscopy offers as efficient diagnostic tool in soil science was provided.en_UK
dc.identifier.citationBarra I, Haefele SM, Sakrabani R, Kebede F. (2021) Soil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: recent advances - a review, Trends in Analytical Chemistry, Volume 135, February 2021, Article number 116166en_UK
dc.identifier.issn0165-9936
dc.identifier.urihttps://doi.org/10.1016/j.trac.2020.116166
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/16207
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectData preprocessingen_UK
dc.subjectMachine learningen_UK
dc.subjectChemometricsen_UK
dc.subjectInfrared spectroscopyen_UK
dc.subjectSoil diagnosisen_UK
dc.titleSoil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: recent advances - a reviewen_UK
dc.typeArticleen_UK

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