A system for an agricultural sprayer includes a boom assembly operably coupled with a chassis. A steering system is operably coupled with the chassis and includes a steering sensor. The system also includes one or more imaging devices and one or more nozzle assemblies. A computing system is operably coupled with the one or more imaging devices and the one or more nozzle assemblies. The computing system is configured to receive data related to a first imaged portion of an agricultural field from the one or more imaging devices; identify a target within the first imaged portion of the agricultural field; receive data related to an inputted steering command from the steering system; and determine a target offset of the target relative to the sprayer path and a boom offset of the assembly relative to the sprayer path.

The invention relates to a device and method for applying a spraying means using a portable spraying device.

A system for controlling a ground speed of an agricultural sprayer includes a boom and a nozzle mounted on the boom. The nozzle, in turn, is configured to dispense a fan of an agricultural fluid as the agricultural sprayer travels across a field. Additionally, the system includes a sensor configured to capture data indicative of a spray quality parameter associated with the dispensed fan of the agricultural fluid. Furthermore, the system includes a controller communicatively coupled to the sensor. As such, the controller is configured to receive the captured data from the sensor as the agricultural sprayer travels across the field. Moreover, the controller is configured to determine the spray quality parameter based on the received data. In addition, the controller is configured to control a ground speed of the agricultural sprayer based on the determined spray quality parameter.

Described herein are techniques for generating contextually rich plant images. A number of data captures of raw plant data are generated via a sensing unit configured to navigate a growing facility. Metadata is generated and assigned to the raw plant data including at least one of: plant location, timestamp, plant identification, plant strain, facility identification, facility location, facility type, health risk factors, plant conditions, and human observations. Images generated by the sensing unit are analyzed and pixel annotations are generated in the images based on their relation to one or more plant well-being features. Data tags are generated and assigned the data captures based on an analysis of the data captures. The data tags are text phrases linking a particular data capture to a specific threat to plant well-being.

Implementations set forth herein relate to using fiducial markings on one or more localized portions of an agricultural apparatus in order to generate local and regional data that can be correlated for planning and executing agricultural maintenance. An array of fiducial markings can be disposed onto plastic mulch that surrounds individual crops, in order that each fiducial marking of the array can operate as a signature for each individual crop. Crop data, such as health and yield, corresponding to a particular crop can then be stored in association with a corresponding fiducial marking, thereby allowing the certain data for the particular crop to be tracked and analyzed. Furthermore, autonomous agricultural devices can rely on the crop data, over other sources of data, such as GPS satellites, thereby allowing the autonomous agricultural devices to be more reliable.

A module for measuring and monitoring an inlet and outlet pressure is described herein. The module includes an inlet pressure port for fluid communication to a fluid line before a filter and the inlet pressure port comprising a first pressure sensor. The module includes an outlet pressure port for fluid communication to a fluid line after the filter and the outlet pressure port comprising a second pressure sensor. At least one signal port is disposed in the module. The first pressure sensor and the second pressure sensor during operation are in signal communication with the at least one signal port.

The present invention relates to an unmanned aerial vehicle (UAV) for agricultural field management. The UAV comprises a control and processing unit (20) and a camera (30). The control and processing unit is configured to control the UAV to fly to a location inside the canopy of a crop and below the vertical height of the crop and/or between a row of a plurality of crops and below the vertical height of the plurality of crop. The control and processing unit is configured to control the camera to acquire at least one image relating to the crop at the location inside the canopy of the crop and below the vertical height of the crop and/or between a row of a plurality of crops and below the vertical height of the plurality of crops. The control and processing unit is configured to analyse the at least one image to determine at least one disease, at least one pest and/or at least one nutritional deficiency.

Systems and methods are provided for use in applying treatments to crops in fields. One example computer-implemented method includes calculating a growth stage of a crop in a field on a defined date based on planting data and weather data for the field and/or crop, and then, in response to the growth stage being within a spray window for the crop, defining a plurality of synthetic sprays within the spray window for the field. The method then includes, for each one of the synthetic sprays, calculating at least one disease risk for the crop in the field and calculating a response to the synthetic spray. The method then further includes compiling a report including a selected one or more of the responses, based on yield differences of the responses, as a recommendation for applying the treatment to the crop consistent with the synthetic spray associated with the selected one or more of the responses.

A system includes a first nozzle assembly positioned along a boom assembly. The first nozzle assembly includes a first valve operably coupled with a first nozzle. A first imaging device is associated with the first nozzle assembly. A second nozzle assembly is positioned along the boom assembly and includes a second valve operably coupled with a second nozzle. A second imaging device is associated with the second nozzle assembly. A computing system is operably coupled with the first nozzle assembly, the first imaging device, the second nozzle assembly, and the second imaging device. The computing system is configured to receive data from the first imaging device, identify a first reference point within the data provided by the first imaging device, receive data from the second imaging device, identify a second reference point within the data provided by the second imaging device, and determine a boom deflection model.

A sprayer control system includes a plurality of smart nozzles each having at least one control valve with a valve operator, an electronic control unit for the valve operator, and one or more spray nozzles. The at least one control valve and the ECU control a flow rate of liquid agricultural product through the nozzles. A duty cycle modulator is in communication with the ECU and generates an applied duty cycle for the at least one control valve. The duty cycle modulator includes a specified duty cycle input having a specified duty cycle and a pressure monitor associated with the at least one control valve. A pressure comparator compares the valve pressure determined with the pressure monitor with a system pressure and generates a pressure error. An applied duty cycle generator generates the applied duty cycle based on the specified duty cycle modified by the pressure error.