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Visual examination of changes in soil structural quality due to land use

Authors :
Wim Cornelis
Donald Gabriëls
Mansonia Alejandra Pulido Moncada
Luís Carlos Timm
Letiane Helwig Penning
Source :
Soil and Tillage Research. 173:83-91
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

This study aims to assess how responsive visual examination methods are to the effect of land use on soil structural quality (SSQ), and whether they are sensitive enough to detect significant changes on SSQ over a given sampling interval. The visual soil assessment (VSA), the visual evaluation of soil structure (VESS), the visual assessment of aggregate stability (VAAS) and the visual type of aggregates index (Tyagg) were used to evaluate the SSQ of a sandy loam and a silt loam soil. The land uses comprised cropland (CP) and grassland (PP). The survey was conducted twice in an agricultural cycle (in August and November). Results showed that VESS and Tyagg were in agreement with soil physical parameters when evaluating structural quality of a sandy loam, in contrast to VSA and VAAS. In the silt loam, all methods were responsive to land use effects on soil quality and sensitive in detecting changes in SSQ between evaluation times. We further showed that soils under PP resulted in the best SSQ compared to CP after harvesting, whereas SSQ of CP was better during cereal flowering than after harvesting. Despite the majority of the visual examination methods used in this survey were responsive in evaluating the effect of land use on SSQ and capable of representing structural dynamics (related to soil management) in an agricultural cycle, the lack of agreement between visual examinations and their interrelationships with the soil physical properties evaluated, however, highlight the need to conduct further work for exploring: a) method limitations, b) key factors such as soil moisture content and minimum number of samples for visual examination according to soil texture and spatial variability, and c) a judicious selection of a minimum data set of SSQ indicators omitting redundant material.

Details

ISSN :
01671987
Volume :
173
Database :
OpenAIRE
Journal :
Soil and Tillage Research
Accession number :
edsair.doi...........d76ef88cd1ea2cc2f23d99c4bec95c77