A system for managing material accumulation relative to ground engaging tools of an agricultural implement may include a ground engaging tool and an acoustic sensor configured to generate data indicative of an acoustic parameter of a sound produced as the ground engaging tool engages the ground when a ground engaging operation is performed within a field. Additionally, the system may include a controller communicatively coupled to the acoustic sensor. The controller may be configured to monitor the data received from the acoustic sensor and determine a presence of material accumulation relative to the ground engaging tool based at least in part on the acoustic parameter.

In one aspect, a system for determining soil levelness as an agricultural implement is being towed across a field by a work vehicle may include a vision-based sensor configured to capture vision data associated with a portion of the field present within a field of view of the vision-based sensor. A controller of the system may be configured to receive, from the vision-based sensor, the vision data associated with the portion of the field present within the field of view of the vision-based sensor. Additionally, the controller may be configured to determine a soil levelness of the portion of the field present within the field of view of the vision-based sensor based on a spectral analysis of the received vision data.

A method including entering, by machine, a first field defined by first field boundaries; and automatically associating the machine with a first wireless network defined by the first field boundaries, the first wireless network comprising a secured data communications network.

A system for implementing a trial in one or more fields is provided. In an embodiment, a agricultural intelligence computing system receives field data for a plurality of agricultural fields. Based, at least in part, on the field data for the plurality of agricultural fields, the agricultural intelligence computing system identifies one or more target agricultural fields. The agricultural intelligence computing system sends, to a field manager computing device associated with the one or more target agricultural fields, a trial participation request. The server receives data indicating acceptance of the trial participation request from the field manager computing device. The server determines one or more locations on the one or more target agricultural fields for implementing a trial and sends data identifying the one or more locations to the field manager computing device.

A system for adjusting actuator pressure on an agricultural implement includes a fluid-driven actuator configured to adjust a position of a tool of the implement relative to the implement frame, with the fluid-driven actuator defining a fluid chamber. Furthermore, the system includes a valve configured to control a flow of a fluid to the fluid-driven actuator. In addition, the system includes a fluid conduit fluidly coupled between the valve and the fluid chamber. Moreover, the system includes a computing system is configured to determine the current position of the tool relative to the implement frame based on the data captured by a position sensor. Additionally, the computing system is configured to determine a current volume of the fluid chamber and the fluid conduit based on the determined current position. Furthermore, the computing system is configured to control the operation of the valve based on the determined current volume.

A localized product injection system includes a composite boom tube having a carrier fluid passage within a tube body, and at least one injection product passage within the tube body isolated from the carrier fluid passage. A plurality of port stations are provided at locations along the tube body. Each of the port stations includes a carrier fluid outlet port and at least one injection product outlet port. A localized injection interface is coupled at a port station. The injection interface includes a carrier fluid input coupled with the carrier fluid outlet port, and at least one injection product input coupled with the at least one injection product outlet port. The injection interface includes at least one throttling element in communication with the at least one injection product input, a mixing chamber, and an injection port configured for localized coupling and injection to a product dispenser.

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.

An agricultural work system for optimizing agricultural work flows has at least one agricultural work unit and a plurality of functional units, each having a control device for controlling the respective functional unit based on a stored set of rules. The agricultural work system has a central pattern recognition system which stores at least one agricultural work situation as a situation pattern. Work situation-specific information is transferrable to the pattern recognition system which identifies a stored work situation and the associated situation pattern based on the obtained information and transmits meta-information (M) characterizing the identified work situation to the functional units. The pattern recognition system and/or the control devices coordinate the cooperation of those functional units which work together in the identified work situation based on the meta-information so that the control devices carry out corresponding parameter adjustments of the associated functional unit.

A memory embodies instructions, and a processor is coupled to the memory and is operative by the instructions to facilitate: accessing a source of information regarding farm cultivation techniques; constructing a cultivation knowledge graph by parsing the source of information regarding farm cultivation techniques, using natural language processing; identifying cultivation quality assessment factors by applying machine learning to the cultivation knowledge graph; estimating quality of a farm cultivation task by comparing a stream of real-time data to the cultivation quality assessment factors, wherein the stream of real-time data is related to performance of the farm cultivation task; identifying from the stream of real-time data, using the cultivation knowledge graph, a controllable variable that affects the quality of the farm cultivation task; and improving the quality of the farm cultivation task by facilitating a change in the controllable variable. The controllable variable may be the identity of a tractor operator.

An agricultural implement has implement settings for soil engaging tools that are controlled based on measured temporal and long-term soil properties in a field. A controller receives data from various soil and optical sensors and provides decision support for adjusting the implement settings. The soil sensors include a square or modified square electrical array that includes two independent, isolated disk coulters running side-by-side followed by two independent, isolated soil engaging runners. One runner has an optical sensor for organic matter, and the other runner has a temperature and moisture sensor. Above-ground optical sensors can be used to measure soil and plant material ahead of and behind the soil engaging tool. The controller can provide real time alerts to an operator that adjustments to the implement settings are needed, or the adjustments can be made automatically based on operator set thresholds, factory settings, or historical individual or global grower adjustments.