A method for classifying plants. In the method, the plants or their plant components, in particular plant leaves, are detected in an evaluation region with the aid of an optical and/or infrared detection unit, and the detected image data of the detection unit are evaluated with the aid of an algorithm, via the evaluation a first plant type being distinguished from a second plant type, the second plant type being treated in particular with a medium, preferably a liquid spray, and the first plant type being planted in the form of a plant row in a tubular cultivation row tube.

Described herein are implements and applicators for placement of fluid applications with respect to agricultural plants of agricultural fields. In one embodiment, a fluid applicator for applying fluids to plants in rows in a field includes a frame, a coulter connected to the frame and disposed to open a trench between the rows of plants, and at least one application member connected to the frame or to the coulter and disposed to apply fluid to a rhizosphere of the plants.

Application units provide placement of fluid applications with respect to agricultural plants of agricultural fields. In one embodiment, an application unit includes a frame to be positioned in operation between two rows of plants and a plurality of flexible members coupled to the frame in operation such that the plurality of flexible members guide a lateral position of the frame to be approximately equidistant from the two rows of plants based upon whether at least one flexible member of the plurality of flexible members contacts one or more plants of the two rows of plants. The plurality of flexible members include a plurality of fluid outlets for spraying crop input in close proximity to the rows of plants.

Method for generating an application map (20) for treating a field with an agricultural equipment comprising the following steps: providing (S10) a field map (10) of a field to be treated; determining (S20) areas in the field map (10) with a weed and/or pest infestation by using an image classification algorithm; and generating (S30) an application map (20) specifying areas for treating the field with an agricultural equipment, wherein the application map (20) is based on the determined areas infested by weed and/or pest infestation; wherein the method further comprises the step of providing boundary data with respect to the field.

Method for generating an application map (20) for treating a field with an agricultural equipment comprising the following steps: providing (S10) a field map (10) of a field to be treated; determining (S20) areas in the field map (10) with a weed and/or pest infestation by using an image classification algorithm; and generating (S30) an application map (20) specifying areas for treating the field with an agricultural equipment, wherein the application map (20) is based on the determined areas infested by weed and/or pest infestation; wherein the method further comprises the step of providing boundary data with respect to the field.

A device for removing or killing weeds, comprising a first image capturing apparatus for capturing a first ground image, a data processing unit connected thereto and an agricultural machine controlled by the data processing unit, which is designed for the targeted removal or killing of weeds, wherein the data processing apparatus is configured to receive the first ground image from the first image capturing apparatus, to receive manually determined position data from at least one connected terminal, which indicate the position of weeds and/or crops and/or ground structures, e.g. rows of plants, which have been detected in the first ground image by one or more users, and, on the basis of the position data, to control the agricultural machine in such a way that it removes or kills the weeds in a targeted manner.

A method and apparatus worn by a user for controlling weeds using concentrated solar energy is disclosed. Solar energy may be concentrated by Fresnel lens over the wearer and directed by manual methods by the wearer at surfaces of weed plants to heat portions thereof causing damage. Shutters or other devices may be used to direct, and control intensity of concentrated, solar energy, such control preferably applied before significant concentration of the solar energy. In some embodiments, solar energy concentration apparatus may be integrated with solar photovoltaic cells for generating electric power for purposes such as an electrical temperature sensor, a camera and video display device for viewing underneath a crop canopy, control of solar intensity and other purposes.

A method and apparatus worn by a user for controlling weeds using concentrated solar energy is disclosed. Solar energy may be concentrated by Fresnel lens over the wearer and directed by manual methods by the wearer at surfaces of weed plants to heat portions thereof causing damage. Shutters or other devices may be used to direct, and control intensity of concentrated, solar energy, such control preferably applied before significant concentration of the solar energy. In some embodiments, solar energy concentration apparatus may be integrated with solar photovoltaic cells for generating electric power for purposes such as an electrical temperature sensor, a camera and video display device for viewing underneath a crop canopy, control of solar intensity and other purposes.

Method for plantation treatment of a plantation field, the method comprising taking an image of a plantation of a plantation field; recognizing items on the taken image by running a first image recognition analysis of a first complexity on the taken image based on a stored parametrization of a machine learning algorithm; identifying an unsatisfying image analysis result; determining ambient data corresponding to the taken image; recognizing items on the taken image by miming a second image recognition analysis of a second complexity on the image based on the ambient data on an external device, wherein the second complexity is higher than the first complexity; determining an improved parametrization based on the second image recognition analysis for the machine learning algorithm for improving the first image recognition analysis; and controlling a treatment arrangement of a treatment device based on the first image recognition analysis.

An apparatus for weed control includes a processing unit that receives at least one image of an environment. The processing unit analyses the at least one image to determine at least one mode of operation of a vegetation control technology from a plurality of modes of operation of the vegetation control technology to be used for weed control for at least a first part of the environment. An output unit outputs information that is useable to activate the vegetation control technology in the at least one mode of operation.