Articles | Volume 6, issue 1
SOIL, 6, 35–52, 2020
https://doi.org/10.5194/soil-6-35-2020
SOIL, 6, 35–52, 2020
https://doi.org/10.5194/soil-6-35-2020

Review article 06 Feb 2020

Review article | 06 Feb 2020

Machine learning and soil sciences: a review aided by machine learning tools

José Padarian et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (review by editor) (30 Nov 2019) by Olivier Evrard
AR by José Padarian on behalf of the Authors (07 Dec 2019)  Author's response    Manuscript
ED: Publish as is (06 Jan 2020) by Olivier Evrard
ED: Publish as is (07 Jan 2020) by John Quinton(Executive Editor)
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Short summary
The application of machine learning (ML) has shown an accelerated adoption in soil sciences. It is a difficult task to manually review all papers on the application of ML. This paper aims to provide a review of the application of ML aided by topic modelling in order to find patterns in a large collection of publications. The objective is to gain insight into the applications and to discuss research gaps. We found 12 main topics and that ML methods usually perform better than traditional ones.