Soybean Variable Rate Planting Simulator

dc.contributor.author McArtor, Brett
dc.contributor.department Agronomy
dc.contributor.majorProfessor Petro Kyveryga
dc.contributor.majorProfessor Allen Knapp
dc.date 2021-01-07T21:58:30.000
dc.date.accessioned 2021-02-25T00:03:53Z
dc.date.available 2021-02-25T00:03:53Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2020
dc.date.embargo 2020-11-05
dc.date.issued 2020-01-01
dc.description.abstract <p>Soybean seed costs have increased considerably over the past 15 years, causing a growing interest in variable rate planting (VRP) to optimize seeding rates within soybean fields. The publicly available online Soybean Variable Rate Planting Simulator (<a href="http://analytics.iasoybeans.com/cool-apps/SoybeanVRPsimulator/">http://analytics.iasoybeans.com/cool-apps/SoybeanVRPsimulator/</a>) was built to help farmers, agronomists, and other agriculturalists to understand the essential prerequisite agronomic or economic conditions necessary for profitable VRP implementation. The simulator uses three years of soybean yield history to identify relative high, medium and low sub-field yield environments. The user then applies one of three yield classification methods (yield distribution percentiles, predefined yield levels and yield stability zones) to define a low, medium, or high yield environment for each raster. Then defines a simulation scenario by entering a common uniform seeding rate (CUSR), a seeding rate increase within the define yield zone, associated yield increase, and additional input costs due to VRP. Once the scenario is defined, the simulator will calculate the cost and return from the seeding rate change and conduct a break-even economic analysis.</p> <p>This simulator utilizes various peer-reviewed studies to help guide the user to understand realistic expectations from VRP. Simulation-based decisions can help farmers and advising agronomists to build their knowledge and skills while not exposing their customers, farm, or crop to unnecessary risks. Simulation-based training techniques, tools, and strategies are also applied in designing learning modules and used as a measurement tool to establish realistic economic and agronomic objectives and outcomes from new practices or technologies.</p>
dc.format.mimetype PDF
dc.identifier archive/lib.dr.iastate.edu/creativecomponents/662/
dc.identifier.articleid 1688
dc.identifier.contextkey 20091195
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath creativecomponents/662
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/93782
dc.source.bitstream archive/lib.dr.iastate.edu/creativecomponents/662/McArtor_B_CC.pdf|||Sat Jan 15 01:26:03 UTC 2022
dc.subject.disciplines Agronomy and Crop Sciences
dc.subject.disciplines Life Sciences
dc.subject.keywords Simulation
dc.subject.keywords Soybean
dc.subject.keywords Population
dc.subject.keywords Precision Ag
dc.subject.keywords Variable Rate Planting
dc.title Soybean Variable Rate Planting Simulator
dc.type article
dc.type.genre creativecomponent
dspace.entity.type Publication
relation.isOrgUnitOfPublication fdd5c06c-bdbe-469c-a38e-51e664fece7a
thesis.degree.discipline Agronomy
thesis.degree.level creativecomponent
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