Environmental Management Zone Modeling And Analysis

• US 20150242970A1
• Filed: 02/25/2015
• Published: 08/27/2015
• Est. Priority Date: 02/25/2014
• Status: Active Grant

• Current Assignee: Pioneer Hi-Bred International (Corteva, Inc.)
• Original Assignee: Pioneer Hi-Bred International (Corteva, Inc.)
• Inventors: Avey, Donald P., Wei, Jun, Winkler, Chris, Gunzenhauser, Robert Alan, Hanson, Joe, Walker, Bruce J., Warnick, Sean
• Granted Patent: US 10,387,977 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A01C 21/007 Determining fertilization requirements
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 50/02 Agriculture; Fishing; Forestry; Mining
• CPC Class Codes: G06Q 50/163 Real estate management

Abstract

Methods and systems for crop management are disclosed. An example method can comprise receiving first information associated with an environmental management zone. The first information can relate to one or more of a land characteristic and a management practice. The first information can comprise a soil type of the environmental management zone. An example method can comprise, receiving historical weather data relating to the environmental management zone. An example method can comprise receiving real-time weather data relating to the environmental management zone. An example method can comprise executing a growth model to predict a nitrogen range for the environmental management zone based on one or more of the first information, the historical weather data, and the real-time weather data. The nitrogen range can comprise probabilities for one or more of a current time period and a future time period in the growing season.

Claims

1. A method comprising:

receiving, by a computing device, first information associated with an environmental management zone, wherein the first information relates to one or more of a land characteristic and a management practice, and wherein the first information comprises a soil type of the environmental management zone;

receiving, by the computing device, historical weather data relating to the environmental management zone;

receiving, by the computing device, real-time weather data relating to the environmental management zone; and

executing a growth model to predict a nitrogen range for the environmental management zone based on one or more of the first information, the historical weather data, and the real-time weather data, wherein the nitrogen range comprises probabilities for one or more of a current time period and a future time period in a growing season.

2. The method of claim 1, wherein the growth model predicts the nitrogen range for the environmental management zone based on second information comprising one or more of a seed planting date, a seed planting density, and seed variety attributes.

3. The method of claim 2, wherein the second information relates to maize seed.

4. The method of claim 1, wherein the growth model is a Crop Environment Resource Synthesis (CERES) maize crop growth and development model.

5. The method of claim 1, wherein the growth model is used to calculate an optimum point of a nitrogen response curve based on the probabilities.

6. The method of claim 5, wherein the optimum point of the nitrogen response curve is determined based upon a maximum yield per nitrogen.

7. The method of claim 5, wherein the optimum point of the nitrogen response curve is determined based upon a maximum yield per nitrogen adjusted for an economic cost of one or more sources of nitrogen.

8. The method of claim 5, wherein the optimum point of the nitrogen response curve is determined based upon a maximum yield per nitrogen adjusted to minimize runoff of excess nitrogen from the environmental management zone.

9. The method of claim 5, wherein the growth model further calculates a difference between the optimum point of the nitrogen response curve and one or more of an actual current soil rate of nitrogen and a predicted current soil rate of nitrogen.

10. The method of claim 5, further comprising storing the optimum point in an electronic data file and using the optimum point to control application of a nitrogen source.

11. The method of claim 1, wherein the growth model comprises a plant growth model.

12. The method of claim 1, wherein executing the growth model to predict the nitrogen range for the environmental management zone comprises forecasting future weather conditions based on at least one of the real-time weather data and the historical weather data.

21. The method of claim 24, wherein the nitrogen outcome probability is generated based on a growth model configured to calculate a difference between the optimum point of the nitrogen response curve and one or more of an actual current soil rate of nitrogen and a predicted current soil rate of nitrogen.

23. The method of claim 1, wherein the nitrogen range is expressed as a visually distinct area adjacent to a line indicating a predicted nitrogen level.

24. The method of claim 23, wherein the visually distinct area is a shaded area.

13. A method comprising:

receiving, by a computing device, first information associated with an environmental management zone, wherein the first information relates to one or more of a land characteristic and a management practice, and wherein the first information comprises a soil type of the environmental management zone;

receiving, by the computing device, historical weather data relating to the environmental management zone;

receiving, by the computing device, real-time weather data relating to the environmental management zone;

generating a nitrogen outcome probability for the environmental management zone based on one or more of the first information, the historical weather data, and the real-time weather data for a particular time period;

receiving, by the computing device, second information associated with the environmental management zone, wherein the second information comprises a change to the first information; and

updating the nitrogen outcome probability based on the second information.

14. The method of claim 13, wherein the first information comprises one or more of seed planting date, seed planting density, and seed variety attributes.

15. The method of claim 13, wherein the first information relates to maize seed.

16. The method of claim 13, wherein the nitrogen outcome probability is generated using a Crop Environment Resource Synthesis (CERES) maize crop growth and development model.

17. The method of claim 13, wherein the nitrogen outcome probability comprises a nitrogen response curve, and further comprising calculating an optimum point of the nitrogen response curve.

18. The method of claim 17, wherein the optimum point of the nitrogen response curve is determined based upon a maximum yield per nitrogen.

19. The method of claim 17, wherein the optimum point of the nitrogen response curve is determined based upon a maximum yield per nitrogen adjusted for an economic cost of one or more sources of nitrogen.

20. The method of claim 17, wherein the optimum point of the nitrogen response curve is determined based upon a maximum yield per nitrogen adjusted to minimize runoff of excess nitrogen from the environmental management zone.

22. The method of claim 17, wherein generating the nitrogen outcome probability for the environmental management zone comprises forecasting future weather conditions based on at least one of the real-time weather data and the historical weather data.

25. The method of claim 13, wherein the nitrogen outcome probability is expressed as a visually distinct area adjacent to a line indicating a predicted nitrogen level.

26. The method of claim 25, wherein the visually distinct area is a shaded area.

27. A method of graphically representing a nitrogen range comprising probabilities for a future time period, wherein the probability of said outcomes are graphically represented as a visually distinct area adjacent to a line indicating a predicted nitrogen level.

28. The method of claim 27, wherein the visually distinct area is a shaded area.