Abstract: A controller is operatively connected to a dispensing system and configured to change the dispensement of an agricultural input from the dispensing system in different predetermined locations within at least one predefined test plot in a management zone of an agricultural field. The predetermined locations have been randomized and replicated for quantifying the agronomic response in a statistically valid manner.

Abstract: A controller is operatively connected to a dispensing system and configured to change the dispensement of an agricultural input from the dispensing system in different predetermined locations within at least one predefined test plot in a management zone of an agricultural field. The predetermined locations have been randomized and replicated for quantifying the agronomic response in a statistically valid manner.

Abstract: A controller is operatively connected to a dispensing system and configured to change the dispensement of an agricultural input from the dispensing system in different predetermined locations within at least one predefined test plot in a management zone of an agricultural field. The predetermined locations have been randomized and replicated for quantifying the agronomic response in a statistically valid manner.

Abstract: A controller is operatively connected to a dispensing system and configured to change the dispensement of an agricultural input from the dispensing system in different predetermined locations within at least one predefined test plot in a management zone of an agricultural field. The predetermined locations have been randomized and replicated for quantifying the agronomic response in a statistically valid manner.

Abstract: A controller is operatively connected to a dispensing system and configured to change the dispensement of an agricultural input from the dispensing system in different predetermined locations within at least one predefined test plot in a management zone of an agricultural field. The predetermined locations have been randomized and replicated for quantifying the agronomic response in a statistically valid manner.

Abstract: A method of performing an agricultural work operation includes the steps of: creating a prescription for a work operation in a geographic area; determining an estimated state for the geographic area; collecting real time data corresponding to an actual state for the geographic area; comparing the estimated state with the actual state; modifying the prescription, if the actual state varies from the estimated state by a threshold amount; and executing the work operation in the geographic area using the prescription.

Abstract: An agricultural automation system for use in an agricultural area includes an implement caddy carrying a plurality of implements, an elongate transport structure, and a field robot movable along the elongate transport structure. The field robot includes an arm movable in at least one direction different from the movement along the elongate transport structure. The field robot interfaces with the implement caddy for coupling the arm with at least one selected implement, such as a tool or sensor.

Abstract: A method for determining field readiness using moisture modeling of a plurality of fields in a region of interest includes (a) generating a detailed set of moisture factors covering a plurality of scenarios for each field element of the plurality of field elements for a particular field; (b) repeating act (a) for each field of the region of interest; (c) generating a general set of moisture factors for a particular field of the plurality of fields to be applied to each field element of the plurality of field elements in the particular field; (d) repeating act (c) for each field of the plurality of fields in the region of interest; and (e) estimating soil moisture for each field element in the region of interest based on the detailed set of moisture factors and the general set of moisture factors.

Abstract: A method for determining field readiness using moisture modeling of a plurality of fields in a region of interest includes (a) generating a detailed set of moisture factors covering a plurality of scenarios for each field element of the plurality of field elements for a particular field; (b) repeating act (a) for each field of the region of interest; (c) generating a general set of moisture factors for a particular field of the plurality of fields to be applied to each field element of the plurality of field elements in the particular field; (d) repeating act (c) for each field of the plurality of fields in the region of interest; and (e) estimating soil moisture for each field element in the region of interest based on the detailed set of moisture factors and the general set of moisture factors.

Abstract: A method for recalibrating a material attribute monitor for a mobile vehicle includes accumulating an aggregate amount of material from a plurality of material transfers; accumulating a plurality of material attribute data sets via a series of data transfers from at least one vehicle to another vehicle, wherein each material attribute data set of the plurality of material attribute data sets is associated with a corresponding material transfer of the plurality of material transfers; measuring aggregate material attributes of the aggregate amount of material; and generating material attribute calibration data from the accumulated plurality of material attribute data sets and the measured aggregate material attributes.

Abstract: Presented herein is a method for predicting suitable times for performing a crop harvesting operation within a field. The method includes the steps of accessing predicted values for weather, crop, and soil conditions, and then predicting values for one or more additional operation variables indicating operation suitability. The method then predicts suitability for performance of the crop harvesting operation based on the predicted operation variables and selected suitability parameters.

Abstract: Presented herein is a method for predicting suitability for performing a remote sensing operation over a particular field. The method includes the step of accessing predicted operation variables at points within the field. These operation variables may include values for weather, crop, and soil conditions. Based on operation suitability parameters selected for each variable, the method predicts remote sensing operation suitability for different points in time.