Citation:
R. Earl, J. C. Taylor, G. A. Wood, I. Bradley, I. T. James, T. Waine, J. P. Welsh, R. J. Godwin and S. M. Knight, Soil factors and their influence on within-field crop variability, Part I: Field observation of soil variation, Biosystems Engineering, Volume 84, Issue 4, April 2003, Pages 425-440.
Abstract:
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.