Main authors: Else K. Bünemann, Giulia Bongiorno, Zhanguo Bai, Rachel E. Creamer, Gerlinde De Deyn, Ron de Goede, Luuk Fleskens, Violette Geissen, Thom W. Kuyper, Paul Mäder, Mirjam Pulleman, Wijnand Sukkel, Jan Willem van Groenigen and Lijbert Brussaard
Editor: Jane Brandt
Source document: Bünemann, E. K. et al. (2018) Soil quality - A critical review. Soil Biology and Biochemistry, Volume 120, May 2018, pp 105-125


A plethora of soil quality assessment and monitoring tools have become available since the 1990s. Here, we give an overview of the main developments in different countries, before addressing aspects of soil quality indicators in more depth in »Soil quality indicators.

Table 1: Major soil quality assessment approaches based on analytical indicators according to geographic origin (North America, Europe, China):
Objectives, target group, scale, interpretation approach, website

Country Reference(s) Name (if any) Objectives  Target group (assumed) Spatial scale Interpretation Website (if any)
Canada (Acton and Gregorich, 1995; Wang et al., 1997) National soil quality monitoring program
Assess status of and trends in soil health Not stated (policy) 23 benchmark sites (5-10 ha each) across Canada Mainly trend analysis  
(Macdonald et al., 1998) Assess inherent soil quality and susceptibility to change Not stated (policy) Regional and national Rating procedures with respect to 4 soil functions  
USA  (Andrews et al., 2004; Karlen et al., 2001; Wienhold et al., 2004; Wienhold et al., 2009) Soil management assessment framework (SMAF) Evaluate management practices, educate about soil quality Land managers, advisors, general public Plot scale Scoring curves, additive index
(Idowu et al., 2008; Moebius-Clune et al., 2016) Cornell Soil Health Test Assess soil health, address soil degradation, increase productivity Farmers Plot scale Scoring curves, overall score
Australia (Gonzalez-Quiñones et al., 2015) Soil Quality Website Benchmark sites, soil quality monitoring and education Farmers National and regional Target values; threshold values wherever possible
New Zealand (Lilburne et al., 2004; Schipper and Sparling, 2000; Sparling and Schipper, 2002; Sparling et al., 2004) “500 soils project”, soil indicator assessment (Sindi) Assess soil quality for environmental reporting Government; Sindi: regional council staff, landowners 511 sites across New Zealand, x soil types, 10 land uses Comparative (compared to database) or according to target ranges
France  (Antoni et al., 2007; Arrouays et al., 2002; Arrouays et al., 2003; Martin et al., 1998) Observatoire de la Qualité des Sols (OQS), Réseau des mesures de la qualité des sols (RMQS)  Assess soil quality for environmental protection, food security and sustainable management practices Not stated (policy) 11 sites (OQS) 2000 sites (RMQS) Mainly trend analysis   
UK  (Loveland and Thompson, 2002; Merrington, 2006)   Assess soil function of environmental interaction Policy   National  Trigger values  
Ireland (Bondi et al., 2017) Soil quality assessment research project (SQARE) Assessment of soil functions Farmers Plot (38 farms)
The Netherlands (Wattel-Koekkoek et al., 2012) National Soil Quality Monitoring Network Assess soil quality and land-use effects Not stated (policy) 200 locations Target values  
EU  (Huber et al., 2001) European Soil Monitoring and Assessment framework Provide objective, reliable and comparable information at European level Policy      
(Huber et al., 2008; Kibblewhite et al., 2008b; Stolte et al., 2016) ENVASSO, RECARE Assess soil degradation Policy

Analytical approaches to soil quality

National assessments of soil quality are often based primarily on analytical approaches (Table 1). One of the earliest national programs to assess and monitor soil quality was started in Canada in 1988 (Acton and Gregorich, 1995), using benchmark sites to assess changes in soil quality over time, especially in relation to the soil threats erosion, compaction, organic matter loss, acidification and salinization (Wang et al., 1997). While the Canadian soil quality monitoring program as such was not consistently continued, the data are still partly used in the assessment of agri-environmental indicators that cover soil, water and air quality (Clearwater et al., 2016). At a coarser scale, a GIS-based approach to characterize primarily inherent soil quality was presented by Macdonald et al. (1998).

Two major soil quality assessment approaches focusing at the plot scale were developed in the USA (Table 1). The Soil Management Assessment Framework (SMAF) developed at the Soil Quality Institute (Andrews and Carroll, 2001; Andrews et al., 2004; Karlen et al., 2001; Wienhold et al., 2004; Wienhold et al., 2009) is rather unique in its flexibility in the selection of indicators. Based on a clear definition of the main ecosystem service(s) or management objective(s) to be addressed, a set of indicators is selected out of 81 potential indicators using selection rules. The user can disregard or alter the proposed minimum dataset as desired, although that limits comparability between sites. The interpretation of an indicator value is based on scoring curves and an additive soil quality index can be derived. The Cornell Soil Health Test (Idowu et al., 2008; Moebius-Clune et al., 2016) is much more standardized and targeted directly at land users, offering various soil health testing packages for farmers, landscape managers and others, and supplying them with management advice together with the results.

In New Zealand, a nationwide survey of seven soil quality indicators at 511 sites aimed at establishing benchmark values across all major soil types and land-uses (Lilburne et al., 2004; Lilburne et al., 2002; Sparling and Schipper, 2004; Sparling and Schipper, 2002). Based on these data, an online tool called Sindi (soil indicator assessment) was developed (Lilburne et al., 2002) that allows the comparison of measurements of soil properties in a given soil type with the information in the database.

In Australia, a consortium of public and private partners provides fact sheets and regional, soil type-specific critical threshold values of a range of soil quality indicators for impact on agricultural production, supplemented by land use-specific distributions of measured indicator values (Gonzalez-Quiñones et al., 2015). Hence, individual farmers can compare their own data for every indicator with the range of values known for similar circumstances in the region. Supplementary general information is also provided that can be used to modify management for environmental goals such as carbon sequestration and minimizing nutrient losses to the environment.

In Europe, many national approaches to soil quality assessment were developed. Those focusing on soil biodiversity rather than on general soil quality were reviewed by Pulleman et al. (2012). The French “soil quality observatory” was started in 1986 and included 11 sites (Martin et al., 1998). The more recent soil quality monitoring system (RMQS) program is based on a 16 x 16 km grid of the French territory and feeds into the French Information System on soils (Antoni et al., 2007; Arrouays et al., 2003). In the UK, the first approach to soil quality monitoring (Loveland and Thompson, 2002) had a focus on forestry and semi-natural soils. After further elaboration, a minimum dataset of only seven measurements was proposed (Merrington, 2006). In addition, »Countryside Survey has been monitoring a few soil properties such as pH, soil organic carbon and some aspects of soil biodiversity (Black et al., 2003) since 1978. In Ireland, recent work on the assessment of soil functions at grassland farms combines a full soil profile description and visual soil assessment with determination of a suite of analytical indicators (Bondi et al., 2017). In The Netherlands, a set of indicators for soil ecosystem services developed by RIVM (National Institute for Public Health and the Environment) was used in two five-year measurement cycles in 200 sites of the Dutch soil quality monitoring network (Wattel-Koekkoek et al., 2012). Target values and ranges for agronomic land use are based on median values of the monitoring network and on judgement of a group of soil experts. Also in the Netherlands, a large Public Private Partnership »Sustainable Soil is developing a soil quality assessment system in which a set of soil chemical, physical and biological indicators is related to target values and ranges for integral advice on soil management.

Given the plethora of soil monitoring programs in Europe, a common European soil monitoring framework was proposed (Huber et al., 2001), which was based as much as possible on existing monitoring activities. Subsequently, the EU-FP6 project ENVASSO (ENVironmental ASsessment of Soil for mOnitoring) aimed at defining and documenting a soil monitoring system for implementation in support of a European Soil Framework Directive (Kibblewhite et al., 2008b), focused on the assessment of soil threats, which however never materialized. Nevertheless, three priority indicators for each soil threat (Huber et al., 2008) were identified, and this list was further revised and amended by the EU-FP7 project RECARE (Preventing and Remediating Degradation of Soils in Europe through Land Care) as shown in Supplementary Table 1.

Supplementary Table 1: Key indicators for soil threats identified by the projects ENVASSO and RECARE (table modified from Stolte et al. (2016))

Soil threat ENVASSO (Huber et al., 2008)  RECARE (Stolte et al., 2016) 
Soil erosion

Estimated soil loss by  
Water erosion (rill, inter-rill, and sheet erosion) Area affected by soil erosion (km2); magnitude of soil erosion/deposition or sediment delivery (tons)
Wind erosion Measured soil loss by wind (t ha-1 yr-1); estimates of wind erosion; susceptibility to wind erosion; various proxy indicators
Tillage erosion Not specified.
Decline in soil organic matter Topsoil organic carbon content (measured) Clay/SOC; topsoil organic carbon content
Soil organic carbon stocks (measured) Total carbon stocks to 1 m depth
Peat stocks (calculated or measured) Peat stocks
Soil contamination Heavy metal contents in soils
Critical load exceedance by sulfur and nitrogen
Progress in management of contaminated sites
Soil sealing Sealed area Sealed area
Land take (Corine Land Cover) Transition index (TI)
New settlement area established on previously developed land Sealed to green areas ratio
Soil compaction Density (bulk density, packing density, total porosity) Relative normalized density
Air-filled pore volume at specified suction Air-filled pore volume
Vulnerability to compaction (estimated) Penetration resistance
Soil biodiversity loss Earthworms diversity and fresh biomass
Collembola diversity (enchytraeids diversity if no earthworms)
Microbial respiration
Soil salinization Salt profile (total salt content or electrical conductivity)
Exchangeable sodium percentage
Potential salt sources (groundwater or irrigation water) and vulnerability of soils to salinization/sodification
Landslides Occurrence of landslide activity
Volume/weight of displaced material
Landslide hazard assessment
Flooding Not addressed Seasonality, magnitude, frequency of precipitation/rainfall intensity; extent of inundated area; flood frequency; loss of crops due to inundation of fields
Desertification Land area at risk of desertification
Land area burnt by wildfires
Soil organic carbon content in desertified land

The history of soil quality assessment in China was reviewed for an international readership by Teng et al. (2014). Due to increasing pressure to maintain and improve soil quality in China, the Chinese government in 2008 established the China Soil Quality Standardisation & Technology Committee (SAC/TC 404) that has been responsible for formulating and modifying soil quality standards in China, including terminology, indicators, criteria, soil sampling methods, analytical methods, standards for soil quality assessment, and remediation of contaminated soils (Chen et al., 2011). By 2010, 141 soil quality-related standards had been set up, partly adopted from ISO.

The flexible and context-specific approach to soil quality assessment of the SMAF as described above has inspired several recent studies that apply multivariate statistical methods to select the most relevant indicators, often based on assumed but not assessed connections between indicators and soil functions, and utilize scoring functions to arrive at a soil quality index geared to the specific conditions (Armenise et al., 2013; Askari and Holden, 2015; Congreves et al., 2015; de Paul Obade and Lal, 2016; Lima et al., 2013; Swanepoel et al., 2014; Tesfahunegn, 2014; Velasquez et al., 2007). The drawback of such flexible approaches lies in the limited comparability between studies, even more than between different applications of the SMAF.

The compilation of major soil quality assessment approaches in Table 1 shows the variation in objectives, target groups (though often not explicitly stated) and spatial scales. Most of these approaches remain at the plot/field/site scale. Recently developed sensor-based approaches show promise to expand soil quality assessment to the landscape level (e.g. Vågen et al., 2013). Importantly, explicit evaluation of soil quality with respect to specific soil threats, functions and ecosystem services has rarely been implemented, and few approaches provide clear interpretation schemes of measured indicator values. This limits their adoption by land managers as well as policy.

Visual assessment approaches to soil quality

The above approaches to soil quality assessment typically require analytical laboratory facilities. Approaches targeting farmers and stressing the educational aspect benefit from more empirical, qualitative indicators that can be easily assessed in the field, deliver immediate results, and facilitate communication between farmers and scientists (Beare et al., 1997).

Table 2: Comparison of major visual soil assessment methods (X signifies required material or performed observations)

Country Australia  France  Australia  UK  New Zealand Brazil/UK Germany
Reference McKenzie (2001) Roger-Estrade et al. (2004) McGarry (2006) Ball et al. (2007) Shepherd et al. (2008) Guimaraes et al. (2011) Mueller et al. (2014)
Stated objectives (assessment of …) soil structure, suitability for root growth soil structure land degradation soil structure soil quality soil structure soil properties with respect to yield potential
Method name SOILpak Profil cultural VS-Fast Peerlkamp  VSA  VESS1 M-SQR2
Principle spade trench spade spade spade spade pit
spade X X X X X X X
plastic basin         X    
hard square board X       X    
plastic bag or sheet       X X X  
knife X     X X X X
auger             X
water bottle         X    
tape measure or ruler     X X X X X
Time needed (min) 25-90 60-180 ? 5-15 25 5-15 10-40
General observations              
soil layers, A-horizon     X       X
surface crusting or cover     X   X    
surface ponding         X    
slope             X
soil erosion         X    
Soil physical properties              
soil texture     X   X   X
soil structure X X X X X X X
soil consistency X   X        
aggregate size distrib.     X X X X X
aggregate shape  X            
slaking/dispersion      X        
soil porosity  X     X X X  
soil colour X   X   X    
soil mottles (no., colour)         X    
available water             X
water infiltration     X        
Soil chemical properties              
soil pH      X        
labile organic C      X        
Soil biological properties              
earthworms (no., size)      X   X    
potential rooting depth         X   X
root development X   X X   X  

1 Visual evaluation of soil structure
2 Muencheberg Soil Quality Rating

In the Wisconsin Soil Health Program, for example, a soil health score card was developed that collects farmers’ observations on soil and plants, and includes a few questions on animal health and water quality (Romig et al., 1996). In Europe, the »GROW Observatory was established in 2016, which is developing simple tools to support soil management for farmers and soil stakeholders, such as simple field-based assessments and educational tools. Visual soil assessment (VSA) approaches have been developed in different parts of the world (Table 2). Most of these methods target mainly soil structure, sometimes in relation to productivity (Abdollahi et al., 2015; Mueller et al., 2013). The methods vary in material and time requirements, with spade methods being generally faster to perform than profile methods and thus being more suitable for farmers (Boizard et al., 2005). The method developed by Peerlkamp (1959), which was used in the Netherlands for 40 years, has recently been improved by simplification of the scoring scheme and inclusion of a visual key (Ball et al., 2007; Guimaraes et al., 2011) to further support the use of the method by non-experts of soil science. Straightforward interpretation is certainly an asset of visual soil quality assessment, but visual soil assessment alone cannot evaluate the status of ecosystem services driven by biological and chemical soil processes (Ball et al., 2017). Because visual soil assessment provides different information than laboratory approaches (Emmet-Booth et al., 2016) the combination of both would be advantageous (Pulido Moncada et al., 2014). Ultimately, the increased use of visual soil assessment is considered to be important in yield gap analysis and land management programs (McKenzie et al., 2015).


Note: For full references to papers quoted in this article see

» References

Go To Top