A method comprising: activating a strobed or pulsed illumination source to produce illuminating light; polarising the illuminating light in a first polarisation axis; illuminating at least part of a tall plant crop with the polarised illuminating light to produce reflected illuminating light; polarising the reflected illuminating light in a second polarisation axis transverse to the first polarisation axis produce cross-polarised reflected illuminating light; capturing an image of at least part of the tall plant crop using the cross-polarised reflected illuminating light; and analysing the captured image to determine a condition of the tall plant crop. Also a vehicle mounted image capture system, a vehicle mounted spraying system and a plant health management system.

Control zones are dynamically identified on a thematic map and work machine actuator settings are dynamically identified for each control zone. A position of the work machine is sensed and actuators on the work machine are controlled based on the control zones that the work machine is in, and based upon the settings corresponding to the control zone. When modification criteria are met, an actuator setting in a control zone can be modified, during operation. The control zone is then divided on a near real-time display into a harvested portion of the control zone, and a new control zone that has yet to be harvested, and that has the modified actuator setting value. A record is then generated and stored, for the harvested control zone, and for the new control zone.

Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to an agricultural observation and treatment system and method of operation. Fluid may be provided through a first pressurized fluid line from a fluid source within an agricultural treatment system to a fluid port of a treatment head assembly of the agricultural treatment system. The fluid may be delivered from the fluid port to one or more spraying tips when the fluid regulator is actuated when in a desired position.

A system for spraying plants comprises a location-determining receiver for estimating a position of a sprayer with respect to one or more rows of plants. A distance sensor is arranged to measure a distance between a nozzle assembly and a plant row segment. A guidance module is adapted to align the nozzle assembly with a target path between the rows of plants, such as a centered path between the rows, or offset between the rows of the plants. A first nozzle is targeted toward a first zone with respect to the plant row segment based on a first spray pattern of the first nozzle. A second nozzle is targeted toward a second zone with respect to the plant row segment based on a second spray pattern of the second nozzle. A nozzle selection module for selecting automatically a first nozzle or a second nozzle based on maximum coverage of a target zone around the plant segment based on the first zone, the second zone, and the measured distance.

An object of the present invention is to provide an agricultural work apparatus, an agricultural work management system, and a program capable of appropriately managing agricultural work information and smoothly implementing agricultural work and business in the future by making use of agricultural work information. An agricultural work apparatus may include: a first image-capturing device; an agricultural work determination unit that determines, on the basis of first image information obtained by capturing an image of a target of agricultural work through the first image-capturing device, whether or not to execute the agricultural work on the target; an agricultural work execution unit that executes the agricultural work; an agricultural work information generation unit that generates agricultural work information including a result of the agricultural work; a measurement unit that measures a position of the target; and an agricultural work information management unit that manages the agricultural work information and positional information.

A modular system includes a hub and a set of modules removably coupled to the hub. The modules are physically coupled to the frame relative to each other so that each module can operate with respect to a different row of a field. An individual module includes a sensor for capturing field measurement data of individual plants along a row as the modular system moves through the geographic region. An individual module further includes a treatment mechanism for applying a treatment to the individual plants of the row based on the field measurement data before the modular system passes by the individual plants. An individual module further includes a computing device that determines the treatment based on the field measurement data and communicates data to the hub. The hub is communicatively coupled to the modules, so that it may exchange data between the modules and with a remote computing system.

An improvement to a roadside sprayer fixates spray nozzles on a registration plate. The registration plate may include integral tabs depending on the application. Inclination of the tabs is adjustable to place streams and droplets in a desired swath coverage. With the nozzles rigidly mounted onto the plate, the entire plate is notated. The use of the registration plate in a spray unit creates a uniform nutation among the nozzles, thereby reducing variability in droplet placement, and providing a more predictable spray from the nozzles. In other embodiments, the spray unit is utilized in a spray system adaptable to service vehicles, and may be utilized in conjunction with a vegetation engagement device, such as a cutter to engage multiple zones of a roadway right-of-way. Additionally, an improved spray unit includes an electromagnetic field and an attractor to generate plate motion.

A method and system for automatically removing undesirable vegetation is provided. The method includes receiving by a first vehicle, data describing a specified geographical area for scanning. The specified geographical area is divided into a plurality of sectors and a second vehicle is directed to a first sector of the plurality of sectors. First geographical coordinates associated with areas of undesirable vegetation growth located within the first sector are receiving from the second vehicle and an optimal travel path from a current location of the first vehicle to the areas of undesirable vegetation growth located within first sector are determined based on analysis of the first geographical coordinates. The first vehicle is directed to the areas of undesirable vegetation growth via the optimal travel path and a process for eliminating the areas of undesirable vegetation growth is executed.

Various embodiments detect and manage target vegetation in vegetation areas, including crop beds, between crop beds, and turfgrasses. In one embodiment, a machine learning model is trained to detect target vegetation in captured images. An information processing system is programmed utilizing the machine learning model. One or more images of a particular area are captured, and target vegetation is detected within the one or more images. A position of the detected target vegetation is determined within the one or more images. An applicator disposed on an agrochemical applicator system that is mapped to the position of the detected target vegetation within the one or more images is determined. The applicator is activated based on a current speed of a vehicle coupled to the agrochemical applicator system, and further based on configuration data associated with the applicator. Activating the applicator selectively applies an agrochemical to the detected target vegetation.

A method includes receiving first sensor data pertaining to plant-related parameters of each of one or more first plants that performed well over time. The method also includes analyzing at least some of the first sensor data to generate a predictive model associated with the one or more first plants. The method further includes receiving second sensor data pertaining to plant-related parameters of each of multiple second plants. In addition, the method includes identifying at least one of the second plants to receive one or more interventions by applying the predictive model to the second sensor data. Identifying the at least one of the second plants includes identifying the at least one of the second plants as having at least one of the plant-related parameters that deviates from at least one of the plant-related parameters of the one or more first plants.