Machine learning optimization through randomized autonomous crop planting
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United States of America
Stats
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Mar 18, 2025
Grant Date -
Feb 23, 2023
app pub date -
Aug 21, 2021
filing date -
Aug 21, 2021
priority date (Note) -
In Force
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Abstract
Systems and methods automate the design and execution of randomized experiments. Portions of a field are planted using an agricultural vehicle configured to randomly vary planting parameters when planting a portion of the field. A resulting crop outcome across each portion or sub-portion of the field is observed. A training set of data is generated that includes the varied planting parameters and the associated crop outcomes for each portion of the field. A machine-learned model is trained using the training set of data and is configured to predict a crop outcome for a portion of the field based on historical and forecast conditions and a set of planting parameters applied to a portion of the field. For subsequent iterations, for a target portion of the field, the machine-learned model can be applied to identify a set of planting parameters for planting the target portion of the field to optimize a desired crop outcome.

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Patent Owner(s)
Patent Owner | Address | |
---|---|---|
DEERE & COMPANY | ONE JOHN DEERE PLACE MOLINE IL 61265 |
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Inventor(s)
Inventor Name | Address | # of filed Patents | Total Citations |
---|---|---|---|
Bowman, Angela L | Waukee, US | 1 | 3 |
Stellpflug, Michael D | Cary, US | 1 | 3 |
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