The Climate Corporation

Ricardo T Lemos

Nicholas Charles Cizek

Moslem Ladoni

Gardar Johannesson

Stephan Hoyer

Brian Lutz

Maria Antonia Terres

James Delaney

Carlos Carrion

Systems and methods for utilizing a spatial statistical model to maximize efficacy in performing trials on agronomic fields are disclosed herein. In an embodiment, a system receives first yield data for a first portion of an agronomic field, the first portion of the agronomic field having received a first treatment, and second yield data, for a second portion of the agronomic field, the second portion of the agronomic field having received a second treatment that is different than the first treatment. The system uses a spatial statistical model and the first yield data to compute a yield value for the second portion of the agronomic field, the yield value indicating an agronomic yield for the second portion of the agronomic field if the second portion of the agronomic field had received the first treatment instead of the second treatment. Based on the computed yield value and the second yield data, the system selects the second treatment. In an embodiment, in response to selecting the second treatment, the system generates a prescription map, the prescription map including the second treatment. The system may also generate one or more scripts which, when executed by an application controller, cause the application controller to control an operating parameter of an agricultural implement to apply the second treatment.

Utilizing spatial statistical models for implementing agronomic trials

Systems and methods for utilizing a spatial statistical model to maximize efficacy in performing trials on agronomic fields are disclosed herein. In an embodiment, a system receives first yield data for a first portion of an agronomic field having received a first treatment, and second yield data for a second portion of the agronomic field having received a second treatment different than the first treatment. The system uses a spatial statistical model and the first yield data to compute a yield value for the second portion of the agronomic field, where the yield value indicates an agronomic yield for the second portion of the agronomic field if the second portion of the agronomic field had received the first treatment instead of the second treatment. Based on the computed yield value and the second yield data, the system selects the second treatment and generates a prescription map including the second treatment.

In an approach, a method for fusing point data with areal averages is performed by a computing system. The fusion procedure is coherent, in the sense that the computing system takes into account what the areal averages represent with respect to the point data. The overarching goal is to fit a model that takes into account the information derived from both data sets. The areal averages provide an estimate for what the integral of a model representing the behavior of the environmental variable should be over a particular district and the point values indicate the estimated value at particular locations. Thus, the integral of the fitted model over a district of the grid should approximate the value provided by the areal averages while also approximating the value provided by the point data for locations which are provided by the point data.

Statistical blending of weather data sets

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San Francisco, CA, United States of America

Ricardo T Lemos