Environmental management zone modeling and analysis
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.
1. A method comprising: receiving, by a computing device, information associated with a management zone, wherein the information comprises the hydrological attributes for the soil type of the management zone; receiving, by the computing device real-time weather data associated with the management zone; generating a nitrogen response curve for the management zone with a crop model or with artificial intelligence utilizing inputs comprising the hydrological attributes for the soil type of the management zone and weather data associated with the management zone; calculating an optimal amount of nitrogen to be applied to the management zone based upon a difference between a predicted optimal amount of nitrogen and a predicted current soil rate of nitrogen; storing the optimal amount of nitrogen to be applied to the management zone in an electronic data file and using the electronic data file to automate application of a nitrogen application source to apply the calculated optimal amount of nitrogen to be applied to the management zone.
2. The method of claim 1 , wherein the optimal amount of nitrogen to be applied to the management zone is based on one or more of a seed planting date, a seed planting density, and seed variety attributes.
3. The method of claim 2 , wherein the one or more of a seed planting date, a seed planting density, and seed variety attributes relate to maize seed.
4. The method of claim 1 , wherein the hydrological attributes for the soil type of the management zone is one or more of the predicted wilting point or saturation point of the soil.
5. The method of claim 1 , wherein the predicted current rate of nitrogen accounts for two or more forms of nitrogen applied to the management zone.
6. The method of claim 1 , wherein the predicted optimal rate of nitrogen prevents or minimizes soluble nitrogen runoff.
7. The method of claim 1 , wherein the weather data comprises both historical and real-time weather data.
8. The method of claim 1 , further comprising a user interface that enables the user to view the predicted amount of nitrogen at different points in time.
9. A method comprising: receiving, by a computing device, information associated with the hydrological attributes for the soil type of the management zone, the amount of irrigation applied to the management zone and weather data associated with the management zone; generating an optimum point of a crop nutrient for the management zone based on a crop model or artificial intelligence techniques that utilize as inputs the hydrological attributes for the soil type of the management zone, the amount of irrigation applied to the management zone and the weather data, calculating the optimum point of the crop nutrient to be applied to the management zone based upon a difference between the amount of the crop nutrient applied to the management zone and a predicted current soil rate of the crop nutrient; storing the optimum point of the crop nutrient to be applied to the management zone in an electronic data file and using the electronic data file to automate application of a crop nutrient application source to apply the optimum point of the crop nutrient to the management zone.
10. The method of claim 9 , wherein the crop nutrient is nitrogen, and the optimal amount of nitrogen to be applied to the management zone is based on one or more of a seed planting date, a seed planting density, and seed variety attributes.
11. The method of claim 10 , wherein the one or more of a seed planting date, a seed planting density, and seed variety attributes relate to maize seed.
12. The method of claim 9 , wherein the crop nutrient is nitrogen, and the hydrological attributes for the soil type of the management zone is one or more of the predicted wilting point or saturation point of the soil.
13. The method of claim 9 , wherein the weather data comprises both historical and real-time weather data.
14. The method of claim 9 , wherein the crop nutrient is nitrogen, and the optimum point of the crop nutrient to be applied to the management zone prevents or minimizes soluble nitrogen runoff.
15. The method of claim 9 , further comprising a user interface that enables the user to view the predicted amount of the crop input at different points in time.
16. The method of claim 9 , wherein the crop input is phosphorous or potassium.
17. The method of claim 9 , wherein the crop input is fertilizer or lime.
18. The method of claim 9 , wherein the crop input is water.
19. A method of preventing nitrogen loss, the method comprising: receiving, by a computing device, information associated with a management zone, wherein the information comprises the hydrological attributes for the soil type of the management zone; receiving, by the computing device real-time weather data associated with the management zone; generating a nitrogen response curve for the management zone with a crop model or with artificial intelligence utilizing inputs comprising the hydrological attributes for the soil type of the management zone and weather data associated with the management zone; calculating an optimal amount of nitrogen to be applied to the management zone based upon a difference between a predicted optimal amount of nitrogen and a predicted current soil rate of nitrogen such that the predicted optimal amount of nitrogen prevents nitrogen loss; storing the optimal amount of nitrogen to be applied to the management zone in an electronic data file and using the electronic data file to automate application of a nitrogen application source to apply the calculated optimal amount of nitrogen to be applied to the management zone.
20. The method of claim 19 , wherein the nitrogen loss prevented is soluble nitrogen.