Visual soil evaluation in relation to measured soil physical properties in a survey of grassland soil compaction in England and Wales

Visual soil evaluation methods can provide a quick and easy, semi-quantitative approach to assessing the overall soil structural condition of a block of soil in three dimensions. To express this amount of information through other measures of soil physical condition (e.g. penetration resistance, bulk density or shear strength) requires a number of measurements at various depths and can be costly and time consuming. There is therefore a need to develop simple field methods to assess and monitor soil quality. urvey of grassland soil compaction in England and Wales, soil visual evaluation methods were used alongside more widely accepted physical measurements of soil compaction (e.g. bulk density – BD and penetration resistance). Soil structural condition was investigated in 300 fields located on 150 farms, with one ‘mainly grazed’ field and one ‘mainly cut’ field selected on each farm. The visual soil evaluation methods were the visual soil assessment (VSA) method from New Zealand and the Peerlkamp (soil structure – ‘St’) method. on the Landcare VSA ranking score, 8% of the grassland fields were in poor condition (95% confidence interval = ±3), 54% (±6) in moderate condition and 38% (±6) were in good condition. Based on the Peerlkamp ‘St’ score, 12% (±4) of fields were in poor condition (‘St’ score < 4.0), 63% (±6) in moderate condition (‘St’ score 4.0–7.0) and 25% (±5) in good condition (‘St’ score > 7.0). Notably, the soil visual evaluations using the VSA ranking score and ‘St’ score were well related (P < 0.001; r2 = 66%). field sites selected for more detailed investigation, there was an inverse relationship between ‘St’ scores and mid topsoil BD (P < 0.01; r2 = 25%), indicating that the measurement of BD in the middle of the topsoil provided an indication of soil structural condition, as determined by visual soil evaluation. Also, for the 300 grassland fields, there was a positive relationship (P < 0.001) between maximum penetration resistance (MPR) in the top 200 mm and both the ‘St’ score (r2 = 26%) and VSA score (r2 = 19%). The visual evaluation scores increased with increasing penetration resistance, indicating that better soil structure (as assessed visually) was associated with greater penetration resistance. This was contrary to the expectation that soils with better structure would be less dense than poorly structured soils and therefore would have lower penetration resistance values. e of multiple predictor models showed that the two most important factors (P = 0.02) influencing the VSA ranking score were (in order of importance): (i) soil organic matter content (positive relationship); (ii) soil sand content (positive relationship).