Using machine learning to predict soil bulk density on the basis of visual parameters: Tools for in-field and post-field evaluation-Reference-Cited by-同舟云学术

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Using machine learning to predict soil bulk density on the basis of visual parameters: Tools for in-field and post-field evaluation

Published:2018-05 Issue: Volume:318 Page:137-147
ISSN:0016-7061
Container-title:Geoderma
language:en
Short-container-title:Geoderma

Author:

Bondi Giulia,Creamer Rachel^ORCID,Ferrari Alessio^ORCID,Fenton Owen,Wall David

Funder

Irish Department of Agriculture

Publisher

Elsevier BV

Subject

Soil Science

Reference54 articles.

1. An exact analytical relation among recall, precision, and classification accuracy in information retrieval;Alvarez,2002

2. Impact of mechanized logging on compaction status of sandy forest soils;Ampoorter;For. Ecol. Manag.,2007

3. Physical soil structure evaluation based on hydraulic energy functions;Armindo;Soil Sci. Soc. Am. J.,2016

4. Effect of clay content and silt-clay fabric on stability of artificial aggregates;Attou;Eur. J. Soil Sci.,1998

5. Visual Soil Evaluation: Realizing Potential Crop Production With Minimum Environmental Impact;Ball,2015

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