Granted Patent B2

US 12,207,585 · App. 15/986,785 · Granted Jan 28, 2025

Inventors: Craig Eugene Rupp (Ames, IA); A. Corbett S. Kull (Palantine, IL); Steve Richard Pitstick (Maple Park, IL); Patrick Lee Dumstorff (Chicago, IL)

Assignee: CLIMATE LLC

A01B79/005G06N7/06

Abstract

Claims (40)

1. A method for execution by one or more processing modules of one or more computing devices affiliated with agriculture equipment, the method comprises:

receiving a request to optimize selection of a crop type for a first geographic region;

selecting, by a computing device, a super-region including a plurality of geographic regions including the first geographic region and multiple geographic regions adjacent to the first geographic region;

accessing, by the computing device, data records and historical summaries for each of the plurality of geographic regions of the super-region;

analyzing, by the computing device, the data records and the historical summaries to produce multiple super-region analysis maps of the super-region;

wherein each of the multiple super-region analysis maps illustrates common results of an agricultural lifecycle for a different permutation of one of a first type of crop and a second type of crop as a function of one of a first dry weather agricultural condition and a second wet weather agricultural condition, and wherein the first type of crop is corn and the second type of crop is beans, and wherein the first dry weather agricultural condition is different than the second wet weather agricultural condition;

based on an estimated weather agricultural condition for a current year, generating a super-region analysis summary map from the multiple super-region analysis maps, the super-region analysis summary map including a first segment of the super-region defined by a first of the common results, having the first type of crop, and a second segment of the super-region defined by a second of the common results, having the second type of crop;

generating an agriculture prescription for the first geographic region based on the super-region analysis summary map, the agricultural prescription including the first type of crop in the first segment of the super region included within the first geographic region and the second type of crop in the second segment of the super-region included within the first geographic region; and

executing, by the agriculture equipment, the agriculture prescription in at least a portion of the first geographic region.

2. The method of claim 1 , wherein analyzing the data records and the historical summaries to produce the multiple super-region analysis maps includes weighing each of the data records and historical summaries based on one or more of age of the data records and historical summaries, a data collection accuracy estimate, a data owner identifier, an indication of differences between previous predictions and measured results, and a distance between the first geographic region and each of the plurality of geographic regions.

3. The method of claim 1 , wherein analyzing the data records and the historical summaries to produce the multiple super-region analysis maps includes comparing the super-region analysis to one or more additional super-region analyses to produce a super-region analysis summary, the super-region analysis summary including a comparison of return on investment for the first type of crop and the second type of crop for the first geographic region.

4. The method of claim 3 , wherein the common results of the agricultural lifecycle include at least one of: an absolute crop yield level, a normalized crop yield rate, and/or a return on investment; and wherein the first weather agricultural condition includes a wet weather condition and the second weather agricultural condition includes a dry weather condition.

5. The method of claim 1 , wherein the agriculture prescription includes at least one of a seed pattern, a crop orientation pattern, and/or a crop distribution pattern for the first geographic region.

6. A non-transitory computer readable storage medium comprising:

at least one memory section configured to store operational instructions that, when executed by one or more processing modules of one or more computing devices affiliated with agriculture equipment, cause the one or more computing devices to:

receive a request to optimize selection of a crop type for a first geographic region;

select a super-region including a plurality of geographic regions including the first geographic region and multiple geographic regions adjacent to the first geographic region;

access data records and historical summaries for each of the plurality of geographic regions of the super-region;

analyze the data records and the historical summaries to produce multiple super-region analysis maps of the super-region;

wherein each of the multiple super-region analysis maps illustrates common results of an agricultural lifecycle for a different permutation of one of a first type of crop and a second type of crop as a function of one of a first dry weather agricultural condition and a second wet weather agricultural condition, and wherein the first type of crop is corn and the second type of crop is beans, and wherein the first dry weather agricultural condition is different than the second wet weather agricultural condition;

based on an estimated weather agricultural condition for a current year, generate a super-region analysis summary map from the multiple super-region analysis maps, the super-region analysis summary map including a first segment of the super-region defined by a first of the common results, having the first type of crop, and a second segment of the super-region defined by a second of the common results, having the second type of crop;

generate an agriculture prescription for the first geographic region based on the super-region analysis summary map, the agricultural prescription including the first type of crop in the first segment of the super region included within the first geographic region and the second type of crop in the second segment of the super-region included within the first geographic region; and

execute, by the agriculture equipment, the agriculture prescription in at least a portion of the first geographic region.

7. The non-transitory computer readable storage medium of claim 6 , wherein analyzing the data records and the historical summaries to produce the multiple super-region analysis maps includes weighing each of the data records and historical summaries based on one or more of age of the data records and historical summaries, a data collection accuracy estimate, a data owner identifier, an indication of differences between previous predictions and measured results, and a distance between the first geographic region and each of the plurality of geographic regions.

8. The non-transitory computer readable storage medium of claim 6 , wherein analyzing the data records and the historical summaries to produce the multiple super-region analysis maps includes comparing the super-region analysis to one or more additional super-region analyses to produce a super-region analysis summary, the super-region analysis summary including a comparison of return on investment for at least two crops for the first geographic region.

9. The non-transitory computer readable storage medium of claim 8 , wherein the common results of the agricultural lifecycle include at least one of: an absolute crop yield level, a normalized crop yield rate, and/or a return on investment.

10. A non-transitory computer readable storage medium of claim 6 , wherein the agriculture prescription includes at least one of a seed pattern, a crop orientation pattern, and/or a crop distribution pattern for the first geographic region.

11. A computer system comprising:

one or more processors;

one or more non-transitory computer-readable media storing operational instructions that, when executed by one or more processing modules of one or more computing devices affiliated with agriculture equipment of a computing system, cause the one or more computing devices to:

receive a request to optimize selection of a crop type for a first geographic region;

select a super-region including a plurality of geographic regions including the first geographic region and multiple geographic regions adjacent to the first geographic region;

access data records and historical summaries for each of the plurality of geographic regions of the super-region;

analyze the data records and the historical summaries to produce multiple super-region analysis maps of the super-region;

wherein each of the multiple super-region analysis maps illustrates common results of an agricultural lifecycle for a different permutation of one of a first type of crop and a second type of crop as a function of one of a first dry weather agricultural condition and a second wet weather agricultural condition, and wherein the first type of crop is corn and the second type of crop is beans, and wherein the first dry weather agricultural condition is different than the second wet weather agricultural condition;

based on an estimated weather agricultural condition for a current year, generate a super-region analysis summary map from the multiple super-region analysis maps, the super-region analysis summary map including a first segment of the super-region defined by a first of the common results, having the first type of crop, and a second segment of the super-region defined by a second of the common results, having the second type of crop;

generate an agriculture prescription for the first geographic region based on the super-region analysis summary map, the agricultural prescription including the first type of crop in the first segment of super region included within the first geographic region and the second type of crop in the second segment of the super-region included within the first geographic region; and

execute, by the agriculture equipment, the agriculture prescription in at least a portion of the first geographic region.

12. The computer system of claim 11 , wherein analyzing the data records and the historical summaries to produce the super-region analysis includes comparing the multiple super-region analysis maps to one or more additional super-region analyses to produce a super-region analysis summary, the super-region analysis summary including a comparison of return on investment for at least two crops for the first geographic region.

13. The computer system of claim 11 , wherein the common results of the agricultural prescription include at least one of: a seed pattern, a crop orientation pattern, a return on investment, and/or a crop distribution pattern for the first geographic region.

Assignments (4)

Continuity (3)

References Cited (32)