An agricultural sprayer includes a computing system configured to receive a first input associated with a target application rate at which agricultural fluid is to be dispensed onto the field. Moreover, the computing system is configured to receive a second input associated with a turn being made or to be made by the sprayer. Additionally, the computing system is configured to determine a maximum ground speed for the turn at which a selected nozzle dispenses the agricultural fluid onto the field at the target application rate based on the received first and second inputs. Furthermore, when the turn is being made, the computing system is configured to control an operation of the sprayer such that the ground speed of the sprayer is at or below the determined maximum ground speed.

A method is provided for operating a system consisting of an agricultural working vehicle, at least one working tool arranged thereon, and a controller assigned to the working vehicle. The method includes detecting, by at least one sensor assembly arranged at least on the working tool and having at least two sensors, two different physical variables. The method further includes storing, by a memory, information characterizing the working tool, continuously storing, by the memory, operating data of at least the working tool, and communicating wirelessly via Bluetooth network with the controller by the at least one sensor assembly via a transmitter. The controller is brought into a transmission range of the sensor assembly to activate the communication between them and the operating data temporarily stored in the memory is transmitted to the controller.

Methods, apparatus, systems and articles of manufacture are disclosed for milestone prediction of fuel and chemical usage. An example apparatus includes one or more memories comprising computer readable instructions; one or more processors to execute the computer readable instructions to determine a current amount of fuel required without halt and a current fuel consumption rate for a machine during a harvesting event in a field based on a first amount of fuel required without halt, a first fuel consumption rate, and real time information from sensors of the machine, and determine a real time amount of fuel required based on the current amount of fuel required without halt, the current fuel consumption rate, and a halt time for the machine during the harvesting event, the one or more processors to use the real time amount of fuel required to schedule fuel delivery for the machine.

A precision agriculture support system is provided with a measuring device, a storage device and a plant species determining unit. The measuring device measures a first spectral characteristic of light derived from vegetation in a support target area. The storage device stores a database of spectrum according to species that shows a spectral characteristic of a desired crop. The plant species determining unit determines whether a plant included in the vegetation is the desired crop or not based on the database of spectrum according to species and a measurement result of the first spectral characteristic. The plant species determination unit further carries out distinction of agricultural crops, distinction of agricultural crops and weeds and the like. Furthermore, the precision agriculture support system identifies an area where abnormality is occurring, estimates a nature of the abnormality and carries out an early warning by providing a countermeasure against the abnormality.

A spraying work method includes generating a target route for a work vehicle that performs a spraying work on crops arranged in a plurality of rows in a field, causing the work vehicle to autonomously travel along the target route, and switching a spraying direction of a spray material for the crop by spraying units and provided in the work vehicle in accordance with a position of either the crop on a work route, on which the work vehicle performs the spraying work while autonomously traveling, or the crop adjacent to the work route.

An automatic traveling method includes causing a work vehicle to automatically travel according to a target route in a farm field, execute a spraying work of spraying a chemical liquid on crops, execute a stirring work of stirring the chemical liquid in a storage tank, and start the stirring work if a predetermined condition is satisfied before the work vehicle starts automatic travel.

A route generation method executes generating a plurality of work routes where a work vehicle travels straight in a first direction that is a travel direction of the work vehicle, in a work area where a crop is arranged, generating a movement route that is a route continuous with the work route and that includes a straight route where the work vehicle travels straight, in a headland area adjacent to the work area in the first direction, in non-work areas surrounding the work area, where the crop is not arranged, and generating a movement route that is a single route continuous with the movement route and that guides the work vehicle to each of the plurality of work routes.

A route determination method, a route determination system, and a route determination program are provided for determining a target route where a work vehicle can work while performing automatic traveling without damaging the topsoil of the work site.

A farming machine including a number of treatment mechanisms treats plants according to a treatment plan as the farming machine moves through the field. The control system of the farming machine executes a plant identification model configured to identify plants in the field for treatment. The control system generates a treatment map identifying which treatment mechanisms to actuate to treat the plants in the field. To generate a treatment map, the farming machine captures an image of plants, processes the image to identify plants, and generates a treatment map. The plant identification model can be a convolutional neural network having an input layer, an identification layer, and an output layer. The input layer has the dimensionality of the image, the identification layer has a greatly reduced dimensionality, and the output layer has the dimensionality of the treatment mechanisms.

A boom sprayer includes any number of components to treat plants as the boom sprayer travels through a plant field. The components take actions to treat plants or facilitate treating plants. The boom sprayer includes any number of sensors to measure the state of the boom sprayer as the boom sprayer treats plants. The boom sprayer includes a control system to generate actions for the components to treat plants in the field. The control system includes an agent executing a model that functions to improve the performance of the boom sprayer treating plants. Performance improvement can be measured by the sensors of the boom sprayer. The model is an artificial neural network that receives measurements as inputs and generates actions that improve performance as outputs. The artificial neural network is trained using actor-critic reinforcement learning techniques.