Methods and systems for determining agricultural revenue

Patent metadata

Field	Value
Publication number	US-11847708-B2
Application number	US-202117376608-A
Country	US
Kind code	B2
Filing date	Jul 15, 2021
Priority date	Sep 12, 2014
Publication date	Dec 19, 2023
Grant date	Dec 19, 2023

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:
retrieving, from a database over a communications interface, a plurality of input data from a plurality of data networks;
calculating, with the processor, an expected yield for a field region of a plurality of field regions, based on field definition data associated with the field region and a subset of the plurality of input data;
wherein the calculated expected yield comprises a high yield for the field region and a low yield for the field region;
collecting, by the agricultural intelligence computer system over the communications interface, 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 user-entered expected yield is not within a range defined by the high yield and the low yield of the expected yield:
collecting, by the agricultural intelligence computer system, additional input data from the plurality of data networks;
automatically calculating, with the processor, an updated expected yield based on the calculated expected yield, the field definition data, and the additional input data, wherein calculating the updated expected yield includes changing the calculated expected yield by a particular percentage value or moving the range until the calculated expected yield includes the user-entered expected yield; and
transmitting, over the communications interface, the updated expected yield to one or more user devices, so that each user device, of the one or more user devices, displays the updated expected yield 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 the one or more user devices.

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 , wherein retrieving the plurality of input data includes retrieving the plurality of input data from the plurality of data networks on a daily basis; and
wherein calculating the expected yield, the crop growth stage, and the at least one profit projection on a daily basis includes the expected yield, the crop growth stage, and the at least one profit projection daily.

5. The method of claim 2 , further comprising:
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 the 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 the 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, to the one or more user devices, the first crop growth stage and the second crop growth stage for the field region.

6. The method of claim 1 , further comprising:
determining a plurality of field regions based on the field definition data; and
identifying a subset of the plurality of input data associated with each field region of the plurality of field regions; and
wherein calculating the expected yield includes calculating the 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 the one or more user devices.

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 configured to be in communication with the processor, the processor configured to:
retrieve, from a database over a communications interface, a plurality of input data from a plurality of data networks;
calculate an expected yield for a field region of a plurality of field regions, based on field definition data associated with the field region and a subset of the plurality of input data;
wherein the calculated expected yield comprises a high yield for the field region and a low yield for the field region;
collect, by the agricultural intelligence computer system over the communications interface, 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 user-entered expected yield is not within a range defined by the high yield and the low yield of the expected yield:
collect, by the agricultural intelligence computer system, additional input data from the plurality of data networks;
automatically calculate an updated expected yield based on the calculated expected yield, the field definition data, and the additional input data, wherein the updated expected yield is further based on the calculated-expected yield being changed by a particular percentage value or the range being moved until the calculated expected yield includes the user-entered expected yield; and
transmit, over the communications interface, the updated expected yield to one or more user devices, so that each user device, of the one or more user devices, displays the updated expected yield 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 the one or more user devices.

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 configured to:
retrieve the plurality of input data from the plurality of data networks on a daily basis; and
calculate the expected yield, the crop growth stage, and the at least one profit projection daily.

12. The networked agricultural intelligence system in accordance with claim 9 wherein the processor is further configured to:
receive a selection of at least one local crop price source from the user device;
determine at least one national crop price from the plurality of input data;
retrieve at l

Assignees

• Climate Llc

Inventors

• Ethington James
• Wimbush Alex

Classifications

• G06Q50/02 Primary

  Agriculture; Fishing; Forestry; Mining · 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

• A01B79/005

  Precision agriculture · CPC title