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US Patent 11776071 Machine learning in agricultural planting, growing, and harvesting contexts

Patent 11776071 was granted and assigned to Indigo (company) on October, 2023 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Indigo
Indigo
Current Assignee
Indigo
Indigo
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11776071
Patent Inventor Names
David Weisman
Jeremy Crane
Casey James Leist
Robert Berendes
Marc-Cedric Joseph Meunier
Steve Abramson
Lauren Moores
Neal Hitesh Rajdev
...
Date of Patent
October 3, 2023
Patent Application Number
17198257
Date Filed
March 11, 2021
Patent Citations
‌
US Patent 8019694 System and method for estimating forward retail commodity price within a geographic boundary
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US Patent 8965812 Evaluating commodity conditions using aerial image data
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US Patent 9113590 Methods, apparatus, and systems for determining in-season crop status in an agricultural crop and alerting users
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US Patent 9381646 Insect and other small object image recognition and instant active response with enhanced application and utility
‌
US Patent 9489576 Crop stand analysis
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US Patent 9519861 Generating digital models of nutrients available to a crop over the course of the crop's development based on weather and soil data
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US Patent 9563945 Object image recognition and instant active response with enhanced application and utility
‌
US Patent 9582002 Robotic platform and method for performing multiple functions in agricultural systems
...
Patent Primary Examiner
‌
Matthew C. Bella
CPC Code
‌
G06Q 10/04
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G06Q 30/06
‌
G06Q 30/02
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G06Q 10/0639
‌
G06Q 30/0278
‌
G06Q 50/02
‌
G06V 10/82
‌
G06V 20/188
...
Patent abstract

A crop prediction system performs various machine learning operations to predict crop production and to identify a set of farming operations that, if performed, optimize crop production. The crop prediction system uses crop prediction models trained using various machine learning operations based on geographic and agronomic information. Responsive to receiving a request from a grower, the crop prediction system can access information representation of a portion of land corresponding to the request, such as the location of the land and corresponding weather conditions and soil composition. The crop prediction system applies one or more crop prediction models to the access information to predict a crop production and identify an optimized set of farming operations for the grower to perform.

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