Methods and systems for determining agricultural revenue

Patent metadata

Field	Value
Publication number	US-11069005-B2
Application number	US-201514846454-A
Country	US
Kind code	B2
Filing date	Sep 4, 2015
Priority date	Sep 12, 2014
Publication date	Jul 20, 2021
Grant date	Jul 20, 2021

Abstract

A computer-implemented method for determining agricultural revenue is provided. The method uses an agricultural intelligence computer system in communication with a memory. The method includes receiving a plurality of field definition data, retrieving a plurality of input data from a plurality of data networks, determining a field region based on the field definition data, identifying a subset of the plurality of input data associated with the field region, calculating at least one yield projection for the field region based on the field definition data and the subset of the plurality of input data, and providing the at least one yield projection to a user device.

First claim

What is claimed is:

1. A computer-implemented method for determining agricultural yield estimates implemented using an agricultural intelligence computer system in communication with a processor, a memory and a database, the method comprising:
receiving, from a database over a communications interface, a plurality of field definition data;
retrieving, from the database, a plurality of input data from a plurality of data networks;
determining, by the processor, a field region, of a plurality of field regions, based on the field definition data;
identifying a subset of the plurality of input data associated with the field region;
generating, by the processor, a calculated expected yield for the field region by performing calculations based on the field definition data and the subset of the plurality of input data; wherein the calculated expected yield comprises a high yield for the field region, calculated based on the field definition data and the subset of the plurality of input data, and a calculated low yield for the field region calculated based on the field definition data and the subset of the plurality of input data;
collecting, by the agricultural intelligence computer system, user-entered expected yield;
comparing, by the agricultural intelligence computer system, the calculated expected yield with the user-entered expected yield;
in response to determining that the calculated expected yield does not include the user-entered expected yield within a particular range:
collecting additional input data from the plurality of data networks;
automatically generating, by the processor, an update based on the calculated expected yield, the field definition data and the additional input data, and by automatically adjusting the calculated expected yield by changing the calculated expected yield by a particular percentage value or by moving the particular range until the calculated expected yield includes the user-entered expected yield; and
transmitting the update to one or more user devices, so that each user device, of the one or more user devices, displays the update for the field region of the plurality of field regions.

2. The method of claim 1 , wherein the field definition data includes a crop identifier and the method further comprises:
calculating a crop growth stage based on the crop identifier and the calculated expected yield; and providing the crop growth stage to a user device.

3. The method of claim 2 , further comprising:
receiving cost data for the field region;
calculating at least one profit projection for the field region based on the cost data and the crop growth stage; and providing the at least one profit projection to the user device.

4. The method of claim 3 , further comprising:
retrieving the plurality of input data from the plurality of data networks on a daily basis; and
recalculating the calculated expected yield, the crop growth stage, and the at least one profit projection on a daily basis.

5. The method of claim 2 , wherein receiving crop prices further comprises:
receiving, from the user device, a selection of at least one local crop price source;
determining at least one national crop price from the plurality of input data;
retrieving, from at least one local crop price source, at least one local crop price based on the crop identifier associated with the field region;
calculating a first crop growth stage based on the calculated expected yield and at least one national crop price;
calculating a second crop growth stage based on the calculated expected yield and the at least one local crop price; and
providing the first crop growth stage and the second crop growth stage for the field based on the calculated expected yield and at least one crop price.

6. The method of claim 1 , further comprising:
determining a plurality of field regions based on the field definition data;
identifying a subset of the plurality of input data associated with each field region of the plurality of field regions; and
calculating at calculated expected yield for each field region based on the field definition data.

7. The method of claim 1 , further comprising:
selecting a crop identifier;
determining a plurality of field regions with the selected crop identifier;
aggregating the calculated expected yield for each field region in the plurality of field regions with the selected crop identifier;
determining a national predicted yield estimate for the selected crop identifier based on the aggregation; and
providing the national predicted yield estimate to a user device.

8. A networked agricultural intelligence system for determining agricultural yield estimates comprising:
a plurality of data network computer systems; and
an agricultural intelligence computer system comprising a processor and a memory in communication with said processor, said processor configured to:
receive, from a database over a communications interface, a plurality of field definition data;
retrieve, from the database, a plurality of input data from a plurality of data networks;
determine, by the processor, a field region, of a plurality of field regions, based on the field definition data;
identify a subset of the plurality of input data associated with the field region;
generate, by the processor, a calculated expected yield for the field region by performing calculations based on the field definition data and the subset of the plurality of input data; wherein the calculated expected yield comprises a high yield for the field region, calculated based on the field definition data and the subset of the plurality of input data, and a calculated low yield for the field region calculated based on the field definition data and the subset of the plurality of input data;
collect, by the agricultural intelligence computer system, user-entered expected yield;
compare, by the agricultural intelligence computer system, the calculated expected yield with the user-entered expected yield;
in response to determining that the calculated expected yield does not include the user-entered expected yield within a particular range:
collect additional input data from the plurality of data networks;
automatically generate, by the processor, an update based on the calculated expected yield, the field definition data and the additional input data, and by automatically adjusting the calculated expected yield by changing the calculated expected yield by a particular percentage value or by moving the particular range until the calculated expected yield includes the user-entered expected yield; and
transmit the update to one or more user devices, so that each user device, of the one or more user devices, displays the update for the field region of the plurality of field regions.

9. The networked agricultural intelligence system in accordance with claim 8 wherein the field definition data includes a crop identifier, and the processor is further configured to:
calculate a crop growth stage based on the crop identifier and the calculated expected yield; and
provide the crop growth stage to a user device.

10. The networked agricultural intelligence system in accordance with claim 9 wherein the processor is further configured to:
receive cost data for the field region;
calculate at least one profit projection for the field region based on the cost data and the crop growth stage; and
provide the at least one profit projection to the user device.

11. The networked agricultural intelligence system in accordance with claim 10 wherein the processor is further configured to:
retrieve the plurality of input data from the plurality of data networks on a daily basis; and
recalculate

Assignees

• Climate Corp

Inventors

• Ethington James
• Wimbush Alex

Classifications

• A01B79/005

  Precision agriculture · CPC title

• G06Q10/04

  Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) · CPC title

• G06Q10/06

  Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling · CPC title

• G06Q10/06375

  Prediction of business process outcome or impact based on a proposed change · CPC title

• G06Q50/02 Primary

  Agriculture; Fishing; Forestry; Mining · CPC title