Note: Descriptions are shown in the official language in which they were submitted.
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TITLE: VARIABLE ZONE CROP-SPECIFIC INPUTS PRESCRIPTION METHOD
AND SYSTEMS THEREFOR
FIELD OF THE INVENTION
This invention relates to methods for managing agricultural crop production in
large
fields. More particularly, the invention relates to methods and systems for
prescribing options for
variable fertility and pest management inputs for optimizing crop production
in selected
agricultural fields.
BACKGROUND OF THE INVENTION
Increasing demands for increased efficiencies in crop production have resulted
in the
development of new agricultural production management tools, methods, and
systems. Adoption
of these tools has enabled significant improvements in crop yields harvested
on a per-acre basis.
However, the efforts required for maximizing crop yields are difficult, time
consuming, and
costly because the characteristics of farmlands vary from acre to acre. This
variance is due to a
variety of factors including among others physico-chemical factors such as
soil topography, soil
nutrient availability, and environmental factors related to weather conditions
particularly
precipitation and temperature. Agricultural farmland productivity is also
affected by the types of
crops produced, their fertility requirements and their optimal environmental
growing
requirements. A constant challenge in all crop production management
strategies is timely pest
detection and control.
Current agronomic production strategies are focused on intensive fertilization
to achieve
maximized crop yields on individual fields. Such strategies require
understanding of various
physico-chemical characteristics of individual fields that could significantly
affect crop yields.
Agricultural lands are typically comprised of several different soil types,
each of which may be
categorized according to differences in soil texture, soil profile
characteristics, soil chemistry,
and organic matter content. Some fields contain one dominant soil type that
covers the majority
of the field area with the remaining area made up of other different soil
types. These other soil
type areas are distributed around the field in various locations and have
irregularly shaped
boundaries, which often, but not necessarily, correspond to low or high spots.
Often, a field
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contains a plurality of irregularly distributed interfacing soil types.
Although any given plot of
land or field may include many different soil types, its potential
productivity and related
fertilization requirements are additionally affected by post-production-cycle
residual nutrient
levels remaining in the soil matrix profiles throughout and about the fields.
Residual soil nutrient
levels can vary considerably within a single field. For example, residual
nitrate nitrogen levels
can vary from about 0 to 200 lbs/acre or higher. According, it would be
unusual if a field did not
include at least two substantially different soils having substantially
different fertilization
requirements. Present methods generally determine nutrient requirements by
taking soil samples
from different areas of the field in a grid configuration in reference to
yield data or multispectral
satellite imagery. Characteristics such as soil composition and type
comprising each soil sample
are quantified and summarized. The depth and thickness of soil horizons and
their properties can
vary immensely within a landscape, and even within a given field. If a
critical soil property, such
as nutrient and water holding capacity or carbon content, is to be assessed
within a given field or
area, then it is critical that the vertical and horizontal distribution of
such properties be
determined accurately. When a soil core is collected, the number of sections
analyzed in the
sample limits the vertical resolution of the soil property assessment at that
location. This is due
primarily to the high cost and time expenditure associated with soil sample
collection,
preparation, analysis, and recording procedures. For example, if one producer
managing
farmland on the order of several thousand acres would require the collection
and analyses of
hundreds of soil samples from throughout their fields for the purpose of
determining the
pluralities of soil characteristics for which nutrient input requirements must
be determined.
Extracting and analyzing this multitude of soil samples is cost prohibitive
and does not provide a
viable method for maximizing agricultural output. Typically, only a few
locations across a
landscape are chosen for core sampling, and only a few sample sections are
removed from each
core for analysis. This limited vertical soil information results in errors
when attempting to
model the spatial distribution and volume of soil properties across a
landscape. Furthermore, the
grid method may unintentionally allow a varied number of soil types and
elevations to be
included within a single area due to the irregularity in shape of the
different areas of the field.
This is also problematic.
The type of the crop to be grown in a field will also significantly affect the
fertilization
requirements for maximal production of the crop. For example, protein and test
weight for wheat
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can range 2.5 percent in a single 40-acre field. The yield can vary as well.
Typically, yields range
from 50 percent less than the mean to 50 percent greater than the mean. Most
applied nutrient
amounts are determined by the expected yield of the crop. Therefore, it is
important to determine
yield potentials prior to application of fertilizers. Ideally, each of the
individual areas of different
soil should be treated independently for the purpose of applying seed,
fertilizer, or other items to
the field. Current practices are to prescribe items, such as seed and
fertilizer, to the entire plot of
land or section of the land, if using the grid method, according to the needs
of the most deficient
soil, or according to the averaged requirements of the different soils. Such
practices commonly
employ satellite imagery in combination with GIS software (i.e., geographic
information system)
or alternatively GPS software (i.e., global positioning system) for detecting
and mapping
selected fields, and for determining various attributes such as topography,
estimations of soil
moisture levels based on the brightness of the soil in high-resolution aerial
satellite imagery, and
estimations of a` normalized difference vegetable indeg'(i.e., NVDI) based on
biomass
extrapolations derived from multispectral satellite imagery. Such practices
typically integrate the
results of soil sample analyses with data derived and extrapolated from
satellite images for
preparation of soil fertility input recommendations that provide specific
fertilizer input
suggestions for each management zone within the field, based on field-
averaging approaches for
maximizing a crop yield.
Other problems encountered with the current agricultural production management
tools,
methods, and systems used for maximizing crop yields relate to recommendations
prepared in
reference to optimal growing conditions. Unexpected weather patterns occurring
during the crop
production cycle often reduce the beneficial effects of fertility inputs on
subsequent crop growth
and development. Crop plants are typically stressed significantly during
extended periods of
drought or alternatively excessive moisture, and during extended periods of
unusually cold
temperatures or alternatively high temperatures. Such stresses generally
reduce plant metabolic
rates and may have long-term debilitative effects of their physiological
performance, thereby
reducing the amounts of the applied fertilizers that are taken up by the
plants. Consequently, in
such stressed growing conditions, significant amounts of anionic macronutrient
salts are leached
away from the soil profiles while the cationic forms tend to accumulate in the
upper soil
horizons. Atypical weather conditions are commonly accompanied by pest
infestations of the
stressed crops that further reduce crop yields and add to the growers'
production costs.
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SUMMARY OF THE INVENTION:
The exemplary embodiments of the present invention relate to methods and
systems for
providing variable zone-based crop inputs prescriptions for optimized
production of selected
crops in selected agricultural fields wherein each field comprises a plurality
of soil management
zones. The crop inputs prescriptions may include one or more of fertility
inputs prescriptions,
pest management inputs prescriptions, and prescriptions comprising
combinations of fertility
inputs and pest management inputs. The methods and systems are suitable for no-
till field crop
production practices and also, for crop production where soils are tilled
prior to seeding. The
methods are adaptable for integration of real-time weather forecasting data to
enable adjustments
in deliveries of selected inputs during a prescribed growing cycle.
An exemplary method according to one embodiment of the present invention
relates to
the acquisition of a plurality of selected input data sets pertaining to a
contemplated production
of a selected agricultural crop. Suitable input data sets include at least
among others, satellite
imagery and/or aerial photographs, encompassing one or more selected
agricultural fields,
topographical maps, physico-chemical data generated from analyses of
pluralities of soil samples
collected within and about the selected agricultural field(s), historical crop
yield data, and
reference agronomic data pertaining to optimized production of a selected crop
species. The
satellite imagery is processed to determine and delineate a plurality of plant
production zones
based on detected and calculated differences in ranges of plant biomass
densities about the
agricultural field. The plant production zones are grouped into soil
management zones based on
the similarities of their soil physico-chemical profiles. For each of a set of
selected crop inputs, a
suitable quantity of a crop input to be applied to each of the soil management
zones is calculated
as follows. First, the residual level of a selected crop input in a selected
soil management zone is
determined from the previously produced physico-chemical profile for that soil
management
zone. The residual level of the selected crop input is then compared to a
suitable reference data
set pertaining to agronomic recommendations for optimal production of the
selected crop. The
difference between the reference data set and the residual level of the crop
input in the plurality
of soil samples collected from the soil management zone is the amount to be
prescribed. An
exemplary crop inputs prescription thus prepared may include prescriptions for
one or more
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selected macronutrients and nutrients for each soil management zone comprising
the agricultural
field.
According to one aspect, historical production and yield data collected from
the
agricultural field comprise suitable input data sets for comparisons with the
suitable agronomic
reference data sets for the purposes of adjusting, tailoring and optimizing
the crop inputs
prescription. The historical data may comprise records from a single growing
season, or
alternatively, records from a plurality of growing seasons. It is suitable for
the data records from
a single growing season to be used as a single data set. However, it is
optional if so desired to
prepare an averaged set of historical production data from a plurality of
production seasons.
According to another aspect, historical weather data sets pertaining to the
historical
production and yield data collected from the agricultural field comprise
suitable data sets for
incorporating into the processing, comparisons and correlations with other
input data sets. For
example, it is useful to identify and correlate production data sets from
growing seasons wherein
certain environmental stresses such as drought, moisture, and temperature
significantly affected
crop productivity and yields, and then correlating the yields of such stress-
affected crops to the
reference agronomic data set, as part of the prescription development
processing steps.
Some exemplary embodiments of the present invention relate to variable zone-
based crop
inputs prescriptions for optimized production of each of a plurality of
selected crops in a selected
field that comprises a plurality of soil management zones for use in assisting
crop production
management decision-making regarding selection of a crop for production in the
agricultural
field.
Another exemplary embodiment relates to methods and systems for providing
targeted
zone-based crop inputs prescriptions for delivery of pest management
strategies and products to
the crop during the production cycle. Such methods generally comprise
additional steps of
inputting data sets pertaining to optimal environmental conditions suitable
for field application of
selected chemical pesticides and biological pesticides relevant to the
production of the selected
crop, and also, to inputting data sets pertaining to sub-optimal environmental
conditions for the
application of these pesticide products and the effects on pesticide
performance. Additional input
steps may include inputting of real-time weather conditions and forecasts, and
optionally, the
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severity of pest incidence and distribution throughout the agricultural field.
The processing steps
will select a suitable pesticide product for application and provide
information outputs pertaining
to weather forecast-based time windows suitable for application of the
selected pesticide product.
Other exemplary embodiments of the present invention relate to methods and
systems for
storing inputs data sets, processing modules and output sets in suitable
protected databases that
are accessible, and optionally manipulable, by qualified users. Certain
aspects relate to wireless
transmission of the inputs data sets and outputs sets to a user for reception
by suitable devices
exemplified by laptop computers, hand-held data transmission and receiving PDA
devices (i.e.,
personal digital assistants). Other aspects relate to correlation of the
outputs sets pertaining to
prescriptions for crop inputs to be applied to specific soil management zones
within the
agricultural field, with GPS positioning coordinates to facilitate computer-
controlled applications
of the crop inputs by suitably equipped field equipment.
BRIEF DESCRIPTION OF THE DRAWINGS
The present invention will be described in conjunction with reference to the
following
drawings in which:
Fig. 1 is a schematic block diagram summarizing exemplary inputs, processing
modules
and outputs according to an embodiment of the present invention;
Fig. 2 is a schematic flow chart outlining an exemplary method and related
system of the
present invention;
Fig. 3 is a schematic flow chart outlining another exemplary method and
related system
of the present invention;
Fig. 4 is an exemplary high-resolution aerial satellite imagery encompassing
an
agricultural field;
Fig. 5 is an exemplary multispectral satellite imagery of the agricultural
field from Fig. 4;
Fig. 6 is an exemplary soil sampling design template superimposed on the
multispectral
satellite imagery from Fig. 5;
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Fig. 7 is an exemplary high-resolution aerial satellite imagery encompassing
another
agricultural field;
Fig. 8 is an exemplary multispectral satellite imagery of the agricultural
field from Fig. 7;
and
Fig. 9 is an exemplary soil sampling design template superimposed on the
multispectral
satellite imagery from Fig. 8.
DETAILED DESCRIPTION OF THE INVENTION
The methods and systems of the present invention for providing variable zone-
based crop
inputs prescriptions for optimized production of selected crops on selected
agricultural fields,
generally relate to collection of selected input data sets, processing and
correlating the data sets,
and producing from the correlated data sets, output sets of information
relevant for assisting
agricultural crop production management decisions for selecting individual
fertility and/or pest
management inputs for optimizing crop production and for the timing of the
applications of the
selected inputs. The methods and systems of the present invention are
generally referred to
herein as variable zone-based crop inputs prescriptions, The variable zone-
based crop inputs
prescriptions are suitable for no-till agricultural crop production and for
crop production systems
wherein soils are tilled prior to sowing.
As shown in Fig. 1, some embodiments of the present invention generally relate
to the
collecting and inputting of a series of data sets pertaining to a service
provider, a user, to selected
sets of information and/or data relating to a selected agricultural field, and
to selected reference
data sets. Suitable input data sets pertaining to a selected agriculture field
generally comprise at
least some selected information exemplified by imagery, physico-chemical data
for the soil
zones comprising field, historical crop production and yield data for the
agricultural field,
agronomic recommendations for production of one or more selected field crops,
and historical
weather data.
Suitable imagery data is exemplified by and/or derived from high-resolution
aerial
imagery, panchromatic satellite imagery, multispectral satellite imagery,
hyperspectral satellite
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imagery, light detection and ranging (LIDAR) data, digital elevation model
(DEM) data,
topographical data, the like, and combinations thereof
Suitable physico-chemical data sets should include at least some of. residual
soil nutrient
levels exemplified by macronutrients and micronutrients, pH, EC (i.e.,
electroconductivity),
soluble salts as a measure of EC, soil texture, mineral composition, moisture,
organic matter
content, and the like. Exemplary soil macronutrients include nitrogen,
phosphorus, potassium,
sulfur, calcium and magnesium. Exemplary soil micronutrients include boron,
chlorine, cobalt,
copper, iron, magnesium, manganese, molybdenum, nickel and zinc.
Reference data sets of agronomic recommendations may include suitable
fertilization
practices for optimal yields of the selected crop, wherein suitable
fertilization practices may
include information exemplified by options for fertilizer formulations and
recommended rates of
application of each type of fertilizer formulation. It is within the scope of
the present invention to
provide reference data sets of agronomic recommendation for a number of
different crops
suitable for production in the agricultural field. The reference data sets may
also include lists of
common plant pests, microbial pests, insect pests and other relevant
biological pests of the
selected crop, as well as lists of chemical pesticides and biological
pesticides registered by the
appropriate agencies for use to eradicate the target pests. Other suitable
reference data sets are
exemplified by historical weather data from previous crop production cycles.
Each set of input data is separately processed, analyzed, summarized, and
identified for
storage and retrieval in a suitable electronic database as exemplified by
enterprise resource
planning software-driven databases. The individual processing module
components are each
provided with one or more suitable algorithms for processing, sorting,
analyzing, summarizing
and preparing suitable reports for each of the input data sets. Some
processing modules are
suitably configured for comparing and correlating selected different types of
input data sets.
Input data sets may also comprise service provider information, user/client
information. The
related systems of the present invention may be integrated with and cooperate
with the methods
to enable multiple user/clients to access a service providers database via
online access or
alternatively, via a VPN-based (virtual private network) web portal wherein
each users access
and interaction with the service providers database and processing modules, is
secure.
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An exemplary method and related system S for providing variable zone-based
crop-
specific fertilization prescriptions for a selected agricultural field is
shown in Fig. 2. After a
farmer selects an agricultural field 10 for which he wishes input
prescriptions for selected crops
to facilitate their crop selection and production management decisions,
suitable high-resolution
geo-referenced aerial imagery is obtained to determine and acquire the field's
shape, dimensions,
and boundaries. The fields boundaries can be saved as geo-referenced (e.g.,
GPS) shape file or
polygon that is accessible by GIS-based programs. The fields topography can be
integrated into
one or more selected polygons from which a site-specific geo-referenced field
shape file 20 is
produced. It is optional to incorporate a site-specific topography map into
the field shape file 20
if so desired. One of a site-related multispectral satellite imagery, and
hyperspectral satellite
imagery collected in previous years, is obtained and clipped onto the field
shape file 20 to
produce a site-specific vegetation sitemap 30. It is suitable if so desired to
obtain, process and
correlate several site related satellite imagery to produce an averaged
satellite imagery to clip
onto the field shape file 20. The near-infrared bands and red bands of
multispectral imagery are
vectored to a vectorized polygon grid, after which a normalized difference
vegetation index
(NDVI) pertaining to the distribution of ranges of biomass densities within
and throughout the
field, can be calculated 40. The NDVI values are then classified and grouped
into several classes
wherein each class has similar ranges of biomass density distribution. The
classes are
interpolated using suitable geostatistical techniques exemplified by kriging,
nearest-neighbor,
inverse distance, Delauney triangulation, minimum curvature, polynomial
regression, radial basis
function, Shepards method, the like, and combinations thereof, into about 4 to
8 zones that
comprise the agricultural field. The NVDI classes may be created by methods of
classification
exemplified by natural breaks, equal area, equal intervals, the like, and
combinations thereof.
The zones are then mapped onto one or more field map templates, and the number
of acres
within each zone is calculated 50. It is suitable to refer to these zones as`
soil management zones'
or`integrated management zones' It is suitable to use NDVI data from a single
growing season to
identify and locate the soil management zones comprising the agricultural
field. However, it is
preferable to combine NDVI data from two or more growing seasons for more
precise
delineation of the soil management zones within and about the agricultural
field. Alternatively,
the soil management zones may be more precisely delineated by correlating the
NDVI data with
one or more of a topographical map, soil moisture distribution throughout the
field, crop yield
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data using algorithms exemplified by fuzzy k-means clustering and by the
minimum-volume
embedding algorithm.
After the soil management zones have been delineated for the agricultural
field, a pattern
of soil sampling suitable numbers of sites within each soil management zone
throughout the
agricultural field is derived 60. Soil samples are then collected and analyzed
for selected
macronutrients and micronutrients, and at least some of soil pH, soil EC,
soluble salts, texture,
mineral composition and organic matter content 70. The soil analysis results
provide a physico-
chemical profile for each of the soil management zones. The physico-chemical
profiles are then
compared to reference data sets pertaining agronomic fertility inputs for
optimal production of a
selected crop, and the differences are then reported for each soil management
zone 80. Using
information provided by the farmer regarding the list of crops he is
considering growing during
the upcoming production season 100, agronomic recommendations for each of the
selected crops
e.g., 111, 112, 113, are input, and a set of equations 120 then calculates a
set of fertilizer
application rates (i.e., prescriptions) for selected macronutrients and
micronutrients for each of
the soil management zones for each of the selected crops 131, 132, 133.
Weather conditions and crop development occurring during a growing season
often
proceed outside of predictions and calculated projections that were made prior
to crop sowing.
For example, unusually high ambient temperatures for extended periods of time
coupled with
ideal precipitation and soil moisture conditions can produce un-anticipated
rapid rates of crop
growth and development that may result in depletion of soil nutrient levels
that were previously
adjusted according to prescriptions. Alternatively, excessive precipitation
coupled with unusually
cool ambient temperatures could result in depletion of the anionic components
of applied
fertilizers through leaching (e.g., nitrates) or precipitation (e.g.,
phosphates) that may result in
the occurrence of crop nutrient stresses. Accordingly, it is within the scope
of the present
invention to adapt the method and systems exemplified in Fig. 2 to provide one
or more variable
zone-based crop-specific inputs prescriptions during the course of a crop
production cycle on a
selected agricultural field, to augment crop inputs prescriptions provided
prior to the
commencement of growing season. It is known that different and varying
concentrations of
macronutrients and micronutrients in soils will cause changes in the
reflectance of crops growing
in those soils. Such changes in crop reflectance are detectable with
hyperspectral imagery. In
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addition to acquiring one or more selected satellite imagery during the
production of the selected
crop in the agricultural field for determination of real-time NDVI indices and
NDVI zones across
the field, other suitable real-time crop production parameter inputs are
exemplified by crop
seeding date, crop development stage exemplified by tillering, leaf-stage data
and the like, the
results of supplementary analyses performed on soil samples collected at one
or more selected
post-seeding time periods. Inputting data sets comprising hyperspectral
information, in
combination with other selected crop production parameter data, enables early
detection of the
potential occurrence and severity of macronutrient and/or micronutrient
deficiencies associated
with the unusual weather conditions occurring during the early stages of crop
production.
Accordingly, the processing module then calculates using appropriately adapted
algorithms, a set
of in-season fertilization prescriptions for each of the soil management zones
across the field to
ameliorate the potential nutrient deficiencies thereby enabling mid-season
optimization of crop
production.
Several pest events invariably occur during the course of a crop production
cycle.
Various types of pests exemplified by weeds, insects and microbial diseases
are commonly
associated with certain geographies, agronomic practices and/or crop types.
The severity of
damage caused to the crop can be ameliorated by prophylactic applications of
certain chemical
pesticides, alternatively by early detection of pest appearance and immediate
application of one
or more suitable chemical or biological pesticides. Quite often, the severity
of pest infestation is
exacerbated by weather conditions. Accordingly, certain aspects of the present
invention relate to
use and analyses of data collected by several different pest monitoring and
detection systems
exemplified by crop scouting and satellite images, for early detection of
localized pest
appearance in one or more soil management zones comprising the agricultural
field. An
exemplary method and related system 200 for providing pest management
prescriptions during a
crop production cycle is shown in Fig. 3. In response to a farmer's request
for one or more pest
management prescriptions for a selected field for which a geo-referenced field
shape file
template 20 has been previously produced, real-time spectral imagery is
obtained for the crop
being produced to enable preparation for a real-time vegetation sitemap 210.
The real-time
NDVI index 220 is determined across the vegetation site map, after which the
related biomass
distribution values are calculated, then classified and grouped into about 4
to 8 soil management
zones that comprise the agricultural field 230. Collected pest scouting data
pertaining to the
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appearance of pest types and their distribution 240 across the NDVI zones
delineating the
agricultural field are input. Historical weather data from previous production
cycles 250 and
current weather forecast projections 260 are input. Also input are suitable
agronomic
recommendations pertaining to recommended pest control products and management
practices
for each of the identified pests 270. The processing module 280 processes,
calculates and
correlates the pest scouting data sets with the NDVI zones across the
agricultural field, the
historical weather data, and with the current weather forecasts, after which
the periods of highest
risk for development of significant diseases, insect and weed pests are
calculated, projected and
reported. Concomitantly, the processing module 280 correlates the disease risk
projections to
reference data sets of chemical pesticides and biological pesticides and to
the agronomic
recommendations for pest management and provides prescription options ,e.g.,
291, 292, 293, for
selection of suitable pest control products, related recommended application
rates for each of the
soil management zones, and timing of applications.
Weed control products represent a significant cost for agricultural producers.
Current
management strategies to control these costs are focused on booking volume
quantities of
selected herbicides in advance of the growing season in anticipation that
certain weed pests will
appear and will need to be controlled. It is within the scope of the present
invention to adapt the
exemplary method and system shown in Fig. 3 for providing weed control
prescriptions
pertaining to one or more selected crops, type of crop rotation employed on
the agricultural
field, historical data pertaining to crop production and yield during the
previous year and related
data sets pertaining to weed infestation and herbicide applications,
historical weed infestation
problems and herbicide usage, and to correlate the processed data with
probability analyses of
potential weed infestation spectra with the selected crop during the planned
growing season, with
reference data pertaining to forecast weather conditions throughout the
growing seasons, and to
lists of suitable herbicides. The output data sets will provide
recommendations for one or two
suitable herbicides, forecasts of likely required application rates on a soil
management zone basis
and related timing of application, and the volumes of each herbicide required.
It is within the scope of the present invention to adapt the methods and
systems of the
present invention to input one or more set(s) of historical annual crop
production records for a
selected agricultural field, to enable refinement of crop prescriptions for an
upcoming production
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cycle. Each annual historical record set could include the type of crop grown,
sowing and
harvesting dates, fertility and pest management product inputs before and
during crop
production, soil physico-chemical data produced from soil samples collected
throughout the field
prior to the crop production, weather data, survey data noting crop health,
vigor, and pest
occurrence during the production period, crop yields, and the like. It is a
common agricultural
practice to rotate the type of crop grown on an agricultural field from year
to year. Accordingly,
providing the methods and systems of the present invention with a plurality of
historical annual
record inputs for an agricultural field whereon multiple crops have been
produced over several
production cycles, will enable averaging of historical production data for
each crop. Such
historical annual record inputs will facilitate the preparation of
prescriptions for several crop
options for an upcoming production cycle and will enable comparison of
projected production
costs for each crop option, and related projections of returns on investment.
Accordingly,
incorporation of historical annual production records into the methods and
systems of the present
invention can be used to facilitate crop selection and production planning for
an upcoming
production cycle.
The methods and systems therefor of the present invention for providing
variable zone-
based crop inputs prescriptions for optimized production of selected crops in
selected agricultural
fields wherein each field comprises a plurality of soil management zones, are
described in more
detail in the following examples which are intended to be exemplary of the
invention and are not
intended to be limiting.
Example 1:
The following example relates to the exemplary method shown in Fig. 2 for
providing
crop-specific zone-variable fertilization prescriptions for a selected
agricultural field. Fig. 4
shows a high-resolution aerial imagery 300 of three agricultural fields in
south eastern Alberta
having the legal land description of N 28 28 24 W4; 08. The middle field 310
with perimeter
boundaries illustrated with the dashed line 30, was chosen as the subject
agricultural field. The
middle field 320 encompassed 158.97 acres (rounded up to 159 ac for this
example).
Subsequently, a shape file template was prepared for the middle field 20. A
service provider
would purchase such suitable imagery when a user/client identifies such fields
for prescription of
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crop inputs. Fig. 5 shows a spectral satellite imagery clipped to the middle
field template, and an
analysis and classification were performed on the related NDVI values
pertaining to biomass
density distributions, resulting in the identification of 7 soil management
zones. Fig. 6 shows the
distribution and locations of individual soil sampling sites throughout the
soil management zones
and about the agricultural field. Based on the soil testing results, the
recommendations for
application of urea fertilizer to the field ranged from 1 (soil management
zone 1) to 128 lbs/ac
(soil management zone 7) with a total urea fertilizer recommendation of
13,693.4 lbs (Table 1).
Table 1:
Soil
management Number of acres Recommended application rate Total fertilizer
for urea fertilizer (lb/ac) applied (lb)
zone
1 25.0 0 0
2 1.4 0 0
3 10.8 49 556.8
4 18.3 91 1,619.8
5 8.9 98 5,752.6
6 59.8 102 887.4
7 39.2 128 4,876.8
Total 159 13,693.4
Example 2:
Fig. 7 shows a high-resolution aerial imagery of another agricultural fields
in south
eastern Alberta having the legal land description of SW 34 28 24 W4; 08, with
perimeter
boundaries illustrated with the dashed line. This field encompassed 157.05
acres. Subsequently, a
polygon outlining the field boundary was prepared for the middle field 20. A
service provider
would purchase such suitable imagery when a user/client identifies such fields
for prescription of
crop inputs. Fig. 8 shows a NDVI map created from a multispectral image and
clipped to the
polygon outlining the middle field boundary, and an analysis and
classification were performed
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on the related NDVI values pertaining to biomass density distributions,
resulting in the
identification of 7 soil management zones. Fig. 9 shows the distribution and
locations of
individual soil sampling sites throughout the soil management zones and about
the agricultural
field. Based on the soil testing results, the recommendations for application
of urea fertilizer to
the field ranged from 54 lbs/ac (soil management zone 1) to 100 lbs/ac (soil
management zone 7)
with a total urea fertilizer recommendation of 12,598.8 lbs (Table 1).
Table 2:
Soil
management Number of acres Recommended application rate Total fertilizer
for urea fertilizer (lb/ac) applied (lb)
zone
1 0.5 54 27.0
2 1.7 54 91.8
3 4.9 72 352.8
4 19.9 72 1,432.8
5 38.3 76 2,910.8
6 58.6 76 4,453.6
7 33.3 100 3,330.0
Total 157.1 12,598.8
Example 3:
Following is a prophetic example illustrating an exemplary embodiment of the
present
invention relating to a client alert method and system for a prescribed
application of a pest
control product according to previously submitted prescription request. The
assumption is that a
client is producing a barley crop on a selected field that was previously
mapped, analysed, and
characterized, and wishes to apply a herbicide product for prophylactic
control of weed pests.
The preferred herbicide product may have the following use
instructions/restrictions: the product
should not be applied if the weather forecasts that within the 12-hour period
after application, the
ambient temperature may drop below +5 C or go above +32 C, and if the soil
moisture is
below a specified level. Additionally, the herbicide product should be applied
to barley between
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the 1-leaf-5-leaf stages and with 2 tillers. Based on data inputs that would
include at least
sowing date, collected post-seeding growing-degree data, barley leaf-stage
data, barley tiller
data, zone-based soil moisture data,`Yeal-time'NDVI data, and current weather
forecast
information, the method and systems are configured to send one or more daily
wireless alerts to
the client indicating whether the herbicide should or should not be applied.
If the real-time data
processing and correlations result in prescribing several days of `do not
apply' recommendations,
then it is suitable to further adapt the method and systems to select an
alternative and more
appropriate herbicide product for application.
While this invention has been described with respect to the exemplary
embodiments,
those skilled in these arts will understand how to modify and adapt the
methods and systems
providing variable zone-based crop inputs prescriptions for optimized
production of selected
crops. For example, it is suitable to provide input data sets pertaining to
real-time futures pricing
for the crop commodity being grown on the selected agricultural field and to
adapt the
processing module for processing and correlating the futures pricing with the
pre-season and in-
season crop inputs prescriptions, thereby enabling deliveries of real-time
profit/loss projection
outputs for facilitating in-season crop inputs management decision-making.
