Articles | Volume 6, issue 1
https://doi.org/10.5194/soil-6-35-2020
https://doi.org/10.5194/soil-6-35-2020
Review article
 | Highlight paper
 | 
06 Feb 2020
Review article | Highlight paper |  | 06 Feb 2020

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

José Padarian, Budiman Minasny, and Alex B. McBratney

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

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)
AR by José Padarian on behalf of the Authors (14 Jan 2020)
Download
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.