Machine learning methods and systems for variety profile index crop characterization
AssigneeAdvanced Agrilytics Holdings, LLC
InventorsWilliam Kess Berg, Jon J. Fridgen, Jonathan Michael Bokmeyer, Andrew James Woodyard
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Abstract
A system includes one or more processors; and one or more non-transitory, computer-readable media including instructions that, when executed by the one or more processors, cause the computing system to: receive a machine data set; process the machine data set with a trained deep learning model to generate predicted variety profile index values; and cause a visualization to be displayed.
Claims20
A computing system, comprising:
- one or more processors;
- and
- one or more non-transitory, computer-readable media having stored thereon instructions that, when executed by the one or more processors, cause the computing system to:
- receive a machine data set corresponding to an agricultural field, wherein the agricultural field includes a plurality of crop plants;
- process the machine data set using an artificial neural network to generate one or more predicted variety profile index values corresponding to the agricultural field;
- and
- generate an executable electronic agricultural prescription file for the agricultural field by processing the one or more predicted variety profile index values.
A computer-implemented method for performing variety selection and placement based on variety profile index values, comprising:
- receiving, via one or more processors, a machine data set corresponding to an agricultural field, wherein the agricultural field includes a plurality of crop plants;
- processing, via one or more processors, the machine data set using an artificial neural network to generate one or more predicted variety profile index values corresponding to the agricultural field;
- and
- generating, via one or more processors, an executable electronic agricultural prescription file for the agricultural field by processing the one or more predicted variety profile index values.
A non-transitory computer-readable medium having stored thereon computer-executable instructions that, when executed by one or more processors, cause a computer to:
- receive a machine data set corresponding to an agricultural field, wherein the agricultural field includes a plurality of crop plants;
- process the machine data set using an artificial neural network to generate one or more predicted variety profile index values corresponding to the agricultural field;
- and
- generate an executable electronic agricultural prescription file for the agricultural field by processing the one or more predicted variety profile index values.
Dependencies are inferred from the claim text.