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Row crop farmers have traditionally managed fertility issues by applying fertilizer and other soil amendments uniformly cross a field. However, within a single field an agricultural producer may encounter a variety of soil types. Uniform treatement of an entire field may result in over or under application of nutrients and inefficient allocation of resources. New geospatial technologies are making it easier for farmers to pinpoint nutrient requirements and AAES researchers are helping to make that technology more useful to Alabama farmers. Precision
farming, also known as site-specific or prescription farming, is of growing
interest among producers. Precision
farming allows growers to optimize inputs, including lime, phosphorus,
nitrogen, and potassium, on a site-specific basis.
Soils are naturally heterogeneous. By identifying areas with similar
properties in a field, farmers can create management zones and treat these
areas based on their specific needs. Crop
management zones are established using remote sensing and aerial photographs,
soil mapping and landscape characterization, farmer knowledge, yield maps,
and conventional soil testing. Once
established, zones are managed according to their unique properties and
inputs are optimized to meet production potential. Site-specific farming in Alabama is expected to increase as
farmers recognize its potential to increase profits. Geospatial
technologies such as global positioning systems (GPS), geographic information
systems (GIS), and remote sensing (RS) are used to implement site-specific
farming programs. Yield monitors
that collect geo-referenced yield data and variable rate fertilizer applicators
that apply different rates of fertilizer to specific areas are examples
of geospatial technologies used in precision agriculture. GPS also is used for soil sampling using
either zone management or grid sampling methods. Grid soil sampling is a sampling method
in which fields are divided into square sections 1 to 2.5 acres in size
and samples are collected within each grid.
Soil samples are analyzed and results allow for the identification
of fertilizer needs within a field.
AAES researchers are presently investigating optimum soil sampling
methods for precision agriculture.
Once
soil test results are analyzed using a GIS, variable rate applications
result in efficient nutrient applications.
Grower revenues increase as inputs are targeted to specific areas
to maximize crop yields. Site-specific
fertilizer applications also promote environmental stewardship by reducing
the potential for nutrient pollution of waterways. By matching fertilizer applications to
crop needs, risk of off-site leaching of nutrients is reduced. In
rain-fed farming, water is often the limiting production factor. However, nutrients and other intrinsic
and extrinsic factors also can control productivity. AAES researchers are using geospatial technologies to study
crop-soil nutrient relationships at the field scale for precision farming
applications. Spatial correlation
of nutrients can be beneficial for understanding field scale relationships
with crop response. Associating
crop yield with soil test results can help identify a cause-effect relationship
between nutrients and crop yield.
This identification allows farmers to pinpoint areas that may benefit
from site-specific applications of fertilizers. For
the past five years, AAES researchers have been working in Lawrence County
with Glenn Acres Farms, the 1999 Alabama Farm of Distinction. This farm is in the Tennessee Valley region
where soils are predominantly formed from limestone, are fine textured,
and are relatively productive. For
this study, five corn fields were chosen.
These fields are non-irrigated and are in conservation management
systems that utilize reduced tillage.
Fields were divided into one-acre grids using GPS technology. Twenty soil samples from each grid were
collected and composited, and extractable nutrients were evaluated using
Auburn’s standard soil testing procedures. Yield monitors collected geo-referenced corn yield data. Soil test nutrient levels and yield were
analyzed using conventional correlation and geostatistics analyses. Yield
maps (figures
1 and 2)
produced using a GIS, and statistics (see
the table) showed substantial
yield variability existed in these fields. This variability can result from many
factors. For example, figures
3 and 4 are maps developed from grid sampling of pH (Figure
3) and soil test P (Figure
4) for field 5. Analyses
suggest portions of this field would respond to liming where pH is below
5.8, and P applications where soil test P is in the medium range. Correlation of nutrients to yield can
help explain some of the yield variability. Cation exchange capacity (CEC) (r = 0.24) and pH (r = 0.12) were
weakly correlated with yields in dry years (average of less than one inch
of rain per week). However,
in years with adequate rainfall, soil test P (r = 0.33), pH (r = 0.40),
and K (r = 0.38) values were more highly correlated with yield. In
order to create zones of similar nutrient levels, the nutrients must have
a “systematic” variability.
Geostatistics are an approach used to analyze the spatial structure
for geo-referenced variables, such as soil test values.
The range of correlation is the distance over which correlated
values occur. The nugget semivariance is an estimate
of the strength of the correlation.
The data in the table for pH, P, and K, indicate these nutrients
exhibited a fairly high degree of spatial correlation over fairly large
distances for most fields. These
data indicate zones based on soil test values can be reliably created
for these fields. Relationships
between soil nutrients and crop yield demonstrate variable rate fertilizer
applications can enable growers to manage field scale variability. Data suggests establishment of management
zones can improve crop production in the Tennessee Valley Region.
This study indicates geospatial technology will help Alabama producers
to maximize production potential and increase competitiveness. |
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