An agricultural data system comprising at least one stalk sensor disposed on a harvester configured to sense incoming crop stalks, at least one processor in communication with the at least one stalk sensor, and a display in communication with the at least one processor, wherein the processor is configured to align as-planted data with as-harvested data from the at least one stalk sensor.

The disclosure relates generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object. In some examples, a method may include identifying a subset of payloads to provide one or more actions based on data representing a policy for one or more subsets of agricultural objects, causing one or more cartridges to be charged based on the subset of payloads, and, and implementing one or more cartridges at an agricultural projectile delivery system.

In an embodiment, computer processes are programmed to determine planting plans based on planting characteristics data received for an agricultural field and a plurality of management zone delineation options defined for the agricultural field. Each of the planting plans specifies different planting recommendations for the agricultural field. A first graphical representation of the planting plans, and an interactive object is generated and displayed on a computing device. The interactive object is configured to receive input specifying a relative importance ratio between the planting plans for determining a new planting plan for the agricultural field. A particular relative importance ratio is received via the interactive object, and is used to determine the new planting plan, which specifies new planting recommendations for the agricultural field. Information about the new planting plan is displayed on the computer device.

A method of updating an all-attitude angle of an agricultural machine based on a nine-axis MEMS sensor includes the following steps: establishing an error model of a gyroscope, an electronic compass calibration ellipse model and a seven-dimensional EKF filtering model, and setting a parameter vector corresponding to a vehicle motional attitude (S1); acquiring data including an acceleration and an angular velocity of a motion of vehicle, and an geomagnetic field intensity in real time (S2); calculating an angle, a velocity, position information, and a course angle of the vehicle by established error model of the gyroscope and the electronic compass calibration ellipse model(S3); data-fusion processing the angle, the velocity, the position information and the course angle of the vehicle by the seven-dimensional EKF filtering model, and updating a motional attitude angle of the vehicle in real time. The steps of the method have a small error, high precision, and reliability.

A pattern recognition system including an image gathering unit that gathers at least one digital representation of a field, an image analysis unit that pre-processes the at least one digital representation of a field, an annotation unit that provides a visualization of at least one channel for each of the at least one digital representation of the field, where the image analysis unit generates a plurality of image samples from each of the at least one digital representation of the field, and the image analysis unit splits each of the image samples into a plurality of categories.

An agricultural harvester includes a frame and a crop cleaning assembly supported on the frame. The crop cleaning assembly, in turn, includes an oscillating component configured to oscillate relative to the frame in a manner that conveys crop material across the oscillating component. Furthermore, the agricultural harvester includes a RADAR sensor configured to emit an output signal directed at the crop material present on the oscillating component and detect an echo signal reflected by the crop material present on the oscillating component. Additionally, the agricultural harvester includes a computing system communicatively coupled to the RADAR sensor. In this respect, the computing system is configured to determine a thickness of the crop material present on the oscillating component based on detected echo signal.

A crop constituent value is sensed by a crop constituent sensor on an agricultural machine. The crop constituent value is distributed among subregions covered by the agricultural machine. A vegetative index-estimated crop constituent value is obtained for each of the subregions. A weighted crop constituent value is generated for each subregion based upon the distributed constituent value for each subregion and the vegetative index-estimated constituent value for that subregion. An action signal is generated based upon the weighted crop constituent value for the subregion.

An agricultural implement includes a sensor configured to emit output signals for reflection off of a surface and detect reflections of the output signals as return signals. Furthermore, the agricultural implement includes a computing system configured to control the sensor such that the sensor emits the output signals for reflection off of a calibration device including a base portion and a plurality of projections extending outward from the base portion such that a top surface of the calibration device approximates a surface profile of the field. Moreover, the computing system is configured to receive data indicative of a profile of the top surface of the calibration device from the sensor in a spatial domain. Additionally, the computing system is configured to convert the received data to a frequency domain using a spectral analysis technique and calibrate an operation of the sensor based on the converted data.

An agricultural implement includes a sensor supported on the frame. The sensor, in turn, is configured to emit output signals for refection off of a field surface of a field and detect reflections of the output signals as return signals. Moreover, the agricultural implement includes a computing system communicatively coupled to the sensor. In this respect, the computing system configured to receive data associated with the detected reflections from the sensor and fit a line or plane to received data. In addition, the computing system is configured to determine at least one of an orientation of the frame or a distance between the frame and the field surface based on the fitted line or plane.

A method includes receiving a machine data set; determining a respective soil strength measurement; processing the respective soil strength measurement to generate a recommendation including an executable agricultural prescription; and storing the executable agricultural prescription. A computing system includes a processor and a memory storing instructions that, when executed by the one or more processors, cause the computing system to: receive a machine data set; determine a respective soil strength measurement; process the respective soil strength measurement to generate a recommendation including an executable agricultural prescription; and store the executable agricultural prescription. A non-transitory computer readable medium includes program instructions that when executed, cause a computer to receive a machine data set; determine a respective soil strength measurement; process the respective soil strength measurement to generate a recommendation including an executable agricultural prescription; and store the executable agricultural prescription.