Soil Factors and their Influence on Within-Field Crop Variability, I: Field Observation of Soil Variation - Earl, R.; Taylor, John C.; Wood, G. A.; Bradley, I.; James, Iain T.; Waine, Toby W.; Welsh, J. P.; Godwin, R. J.; Knight, S. M. (Elsevier, 2003)
A fundamental component of adopting the concept of precision farming in practice is the ability to measure spatial variation in soil factors and assess the influence of this on crop variability in order to apply appropriate management strategies. The aim of this study was to appraise potential methods for measuring spatial variability in soil type, nutrient status and physical properties in practical farming situations. Five fields that are representative of more than 30% of soils used for arable production in England and Wales were selected for use as case studies. Maps of soil type were generated from a conventional hand auger survey on a 100 m grid and the excavation of targeted soil profile pits. These were compared with those refined using a mechanised soil coring device and scans of electromagnetic inductance (EMI) carried out while the soil could reasonably be considered to be at, or near, field capacity moisture content. In addition, soil sampling for nutrient analyses was conducted on a 50 m grid to examine the spatial variation in nutrient status. Conventional methods for sampling soil were found to be appropriate for identifying soil types at specific locations within the field sites, however, they were time- consuming to perform which placed an economic and therefore a practical limitation on the sampling density possible. The resulting data were considered to be too sparse for demarcating soil type boundaries for use in the context of precision farming. The location of soil boundaries were refined by using the mechanised soil corer, however, the limitation of this was found to be the time required to analyse the soil cores produced. Maps of soil variation generated from EMI scans conducted at field capacity appear to reflect the underlying variation in soil type observed in maps generated using the mechanised soil corer. and, therefore, this approach has potential as a cost-effective, data- rich, surrogate for measures of soil variability. Results from analyses of soil samples for measurement of nutrient status indicated that whilst there was considerable variation in macro- and micro-nutrient levels in each field, with the exception of pH, these levels were above commonly accepted agronomic limits. Results did however demonstrate the potential for addressing variation in critical factors such as pH at specific locations, however, there is a need to develop protocols for targeting sampling in order to reduce costs.