WO2024074674A1

WO2024074674A1 - Nozzle decision engine

Info

Publication number: WO2024074674A1
Application number: PCT/EP2023/077696
Authority: WO
Inventors: Steffen TELGMANN; Greg Robert KRUGER
Original assignee: Basf Agro Trademarks Gmbh
Priority date: 2022-10-06
Filing date: 2023-10-06
Publication date: 2024-04-11

Abstract

A computer implemented method for validating a nozzle configuration for a planned treatment of an agricultural relevant organism on an agricultural field, comprising the steps of: providing operation data associated with the planned treatment, determining one or more spray characteristics of an individual nozzle based on the provided operation data with a model relating operation data to one or more spray characteristics, validating the individual nozzle for the planned treatment based on the determined spray characteristics of the individual nozzle and one or more reference spray characteristics, generating control data in response to the validation step, providing the generated control data.

Description

NOZZLE DECISION ENGINE

TECHNICAL FIELD

The present disclosure relates to a computer-implemented method for validating a nozzle configuration , uses of such a method, a computer program element, an apparatus for validating a nozzle configuration a treatment device fo treatment of an agricultural field based on a validated nozzle configuration., uses of such a method, and a computer program element.

TECHNICAL BACKGROUND

The general background of this disclosure is the treatment of plants in an agricultural field, which may be an agricultural field, a greenhouse, or the like. The treatment of plants, such as the cultivated crops, may also comprise the treatment of weeds present in the agricultural field, the treatment of insects present in the agricultural field or the treatment of pathogens present in the agricultural field. In the technical field of agriculture, there is steady push to make farming or farming operations more sustainable. Precision farming or agriculture is seen as one of the ways to achieve better sustainability and reducing environmental impact. To date various approaches towards more precise farming have emerged. One of the main challenges is to provide plant treatment well targeted in the desired amount. This may be performed by selectively providing plant treatment. More specifically, the general background relates to the selection of nozzles for treatment on treatment devices. Currently, expert knowledge from the farmer is necessary in order to provide the plant treatment well targeted in the desired amount. Thus, there is a need for a robust, reliable method to make plant treatment more sustainable and reduce environmental impact.

SUMMARY OF THE INVENTION

In one aspect, a computer implemented method for validating a nozzle configuration for a planned treatment of an agricultural relevant organism on an agricultural field is proposed, comprising the steps of: providing operation data associated with the planned treatment, determining one or more spray characteristics of an individual nozzle based on the provided operation data with a model relating operation data to one or more spray characteristics, validating the individual nozzle for the planned treatment based on the determined spray characteristics of the individual nozzle and one or more reference spray characteristics, generating control data in response to the validation step, providing the generated control data.

In an aspect a system for validating a nozzle configuration is disclosed, the system comprising an input interface for receiving operation data an output interface for providing control data and a processing device configured for determining one or more spray characteristics of an individual nozzle based on the provided operation data with a model relating operation data to one or more spray characteristics, validating the individual nozzle for the planned treatment based on the determined spray characteristics of the individual nozzle and one or more reference spray characteristics, generating control data in response to the validation step, providing the generated control data.

In an aspect a treatment device is disclosed, the treatment device comprising a nozzle holder, comprising at least two nozzles and a motor for activating a specific nozzle, a communication interface for receiving control data provided by the method of validating a nozzle configuration, a motor controller configured for controlling the motor based on the control data,

In an aspect a display device is disclosed, the display device comprising a communication interface for receiving control data control data provided by the method of validating a nozzle configuration, a display controller for controlling the display device to visualize the validated nozzle configuration based on the generated control data.

In a further aspect the use of a treatment device in or for performing any one of the methods disclosed herein is presented. In another aspect a method for using a treatment device in or for performing any one of the methods disclosed herein is presented.

In a further aspect the use of control data obtained by any one of the methods disclosed herein for operating at least one treatment device is presented.

In a further aspect a computer element, inparticular a computer program product or a computer readable medium, with instructions, which when executed on one or more computing device(s) is configured to carry out the steps of any of the methods disclosed herein in any of the systems disclosed herein is presented.

In a further aspect the use of a treatment product in any of the methods disclosed herein or in any of the systems disclosed herein is presented. In another aspect a method for treating an agricultural field is presented, the method comprising the step of providing a treatment product for use in any of the methods disclosed herein or in any of the systems disclosed herein.

Any disclosure and embodiments described herein relate to the methods, the systems, the treatment devices, the computer element lined out above and vice versa. Advantageously, the benefits provided by any of the embodiments and examples equally apply to all other embodiments and examples and vice versa.

As used herein ..determining" also includes ..initiating or causing to determine", “generating" also includes ..initiating or causing to generate" and “provding” also includes “initiating or causing to determine, generate, select, send or receive”. “Initiating or causing to perform an action” includes any processing signal that triggers a computing device to perform the respective action.

The methods, systems and computer elements disclosed herein provide an efficient, sustainable and robust way for treating an agricultural field.

In particular validation of the individual nozzle configuration based on the planned treatment prevents overdosing or underdosing of the treatment product and enables targeted operation. By considering the operation data associated with a planned treatment for determining spray ch acartei sties of it is ensured that the nozzle configuration is suited for the planned treatment. This enables more precise targeting of treatment and thereby reduces the risk for over and/ or underdosing treatment products. This in turn leads to a a more efficient, sustainable robust way of treating an agricultural field.

It is an object of the present invention to provide an efficient, sustainable and robust way of treating an agricultural field. These and other objects, which become apparent upon the following description, are solved by the subject matter of the independent claims. The dependent claims refer to preferred embodiments of the invention.

The term “treatment device” is to be understood broadly in the present case and comprises any device configured to treat an agricultural field. The treatment device may be configured to traverse the agricultural field. The treatment device may be a ground or an air vehicle, e.g. a rail vehicle, a robot, an aircraft, an unmanned arial vehicle (UAV), a drone, or the like. The treatment device may be equipped with one or more treatment unit(s) and/or one or more monitoring unit(s). The treatment device may be configured to collect field data via the treatment and/or monitoring unit. The treatment device may be configured to sense field data of the agricultural field via the monitoring unit. The treatment device may be configured to treat the agricultural field via the treatment unit. Treatment unit(s) may be operated based on monitoring signals provided by the monitoring unit(s) of the treatment device. The treatment device may comprise a communication unit for connectivity. Via the communication unit the treatment device may be configured to provide, receive or send field data, and/or to provide, send or receive operation data. In another example the field data and/or operation data in addition or as an alternative are provided via a user interface.

The treatment device may be a unmanned arial vehicle (UAV) and/or sprayer or a tractor.

The term “treatment” is to be understood broadly in the present case and may relate to any treatment for the cultivation of plants. The term treating or treatment is to be understood broadly in the present case and may relate to any treatments of the agricultural field, such as for the cultivation of plants. Treatment may include treatment to be conducted during a season on an agricultural field such as applying products, including but not limited to, fertilization, crop protection, growth regulation, soil treatment, soil nutrient management, soil nitrogen management.

The term “treatment product” is to be understood broadly in the present case and may refer to any object or material useful for the treatment. In the context of the present invention, the term treatment product may include: chemical products such as fungicide, herbicide, insecticide, acaricide, molluscicide, nematicide, avicide, piscicide, rodenticide, repellant, bactericide, biocide, safener, plant growth regulator, urease inhibitor, nitrification inhibitor, denitrification inhibitor, or any combination thereof. biological products such as microorganisms useful as fungicide (biofungicide), herbicide (bioherbicide), insecticide (bioinsecticide), acaricide (bioacaricide), molluscicide (biomolluscicide), nematicide (bionematicide), avicide, piscicide, rodenticide, repellant, bactericide, biocide, safener, plant growth regulator, urease inhibitor, nitrification inhibitor, denitrification inhibitor, or any combination thereof. fertilizer and nutrient, seed and seedling, water, and any combination thereof.

“Spray characteristics” is understood broadly. The spray characteristics may refer to characteristics associated whith a spray nozzle. The spray characteristics may refer to a spray pattern, in particular a spray pattern in a target distance from a nozzle orifice. The spray characteristics may refer to a capacity of a nozzle. The spray characteristics may refer to a droplet size associated with a nozzle.

“Spray angle” as used herein is to be understood broadly. It may refer to an angle formed by the of liquid leaving the nozzle. It may in particular refer to the angle formed by the liquid leaving a nozzle at the nozzle orifice. In an example, the spray angle may be the angle of the nozzle cone. The spray angle may substantially be formed at the exit of the nozzle and/or at the nozzle orifice.

“Nozzle configuration” as used herein is understood broadly. It may refer to a configuration of one or more individual nozzles on a treatment device. The term may also refer to the orientation of the one or more individual nozzles, in particular relative to the moving direction of the treatment device. For example, when referring to one individual nozzle, the configuration may comprise the one individual nozzle. The nozzle configuration may also comprise the orientation relative to the moving direction of the treatment device. This may reduce a shadow effect caused by the plant to be treated.

“Distributed computing environment” is to be understood broadly in the present case and may refer to a distributed machinery setup with a least one treatment device for treating the agricultural field. The at least one treamend device may be internconnected to a monitoring device. The at least one treatmend device may be interconnected to a nozzle validation device. The devices may be connected via one or more distributed computing device(s). The computing device(s) may be part of the treatment device and/or remote from the treatment device connected through a network.

“Agricultural field” is to be understood broadly in the present case and may refer to an agricultural field to be treated. The agricultural field may be any plant or crop cultivation area, such as a farming field, a greenhouse, or the like. It may also include any area to be treated such as a rail way, a street side stipes or the like. A plant may be a crop, a weed, a volunteer plant, a crop from a previous growing season, a beneficial plant or any other plant present on the agricultural field. The agricultural field may be identified through its geographical location or geo-referenced location data. A reference coordinate, a size and/or a shape may be used to further specify the agricultural field. The agricultural field may be identified through a reference coordinate and a field boundary.

“Field data” is to be understood broadly in the present case and may comprise any data that may be obtained by the treatment device. Field data may be obtained from the treatment unit and/or the monitoring unit of the treatment device. Field data may comprise measured data obtained by the treatment device. Field data may comprise monitoring unit data configured to control or for controlling the monitoring unit of the treatment device. Field data may comprise treatment unit data configured to control or for controlling the treatment unit of the treatment device. Field data may comprise data from which a field condition on the agricultural field may be derived. Field data may comprise data related to an treatment and/or monitoring operation of the treatment device. Field data may comprise image data, spectral data, section data based on which sections may be analysed or sections may be flagged with e.g. a monitoring or a treatment status, crop data, weed data, soil data, geographical data, measured environmental data (e.g. humidity, airflow, temperature, and sun radiation).

"Dose rate" refers to an amount of product to be applied per area, for example expressed as liter per hectare (L/ha).

“Agricultural relevant organism” as used herein is to be understood broadly and may refer to organisms on an agricultural field. In particular organisms , with an impact on crop biomass in the field, including but not limited to crop plants, insects, fungi or weed.

“Target-area” as used herein is to be understood broadly and refers to an area that is to be targeted by the treatment. The target area may be a function of the distance from a nozzle and the drive speed of the treatment device.

“non-target area” refers to an area outside the target-area that is not intended for treatment.

“Spray pattern” is understood broadly and refers to a pattern formed by a liquid leaving a nozzle at a target area. In particular, it may refer to a lateral distribution of the liquid at a target area.

The term “operation data” or “operational data” as used herein is understood broadly and may comprise data relevant for operation of the planned treatment. In other words, operation data substantially comprise data to specify the planned treatment. Operation data in an example may be provided as operating parameters. Operation data may include data related to any data configured to operate the treatment device, e.g. treatment device data. The term “operation data” may further comprise field data. In an example, operation data may comprise data that have impact to a spray characteristic of an individual nozzle. The operation data may comprise set up data and/or setting data for the treatment device and/or environmental data such as weather data and/or field data. The operation data may comprise influencable data and/or fixed data. The drive speed of the treatment device may be classified as influencable data. However, the weather condiction may be seen as fixed data. The operation data may comprise readings from sensors of the treatment device, e.g. the actual setup of actuators of the treatment device. Operation data may comprise treatment device intrinsic data, i.e. data that are influenced by the setup of the treatment device, and treatment device extrinsic data, i.e. data that are substantially influenenced by other parameter, which are substantially independent from the setup of the treatment device.

“Treatment device data” is understood broadly and refers to data associated with the treatment device, this may include a treatment device speed, a boom height, a pressure or a pressure range for the fluid system of the treatment device, nozzle distance, volume per area.

The providing control data may be carried out by one or more computing device(s) that validates an individual nozzle. The computing device may be part of the treatment device and/or any remote computing device. Providing may include any communication between interfaces of the distributed computing device(s) or any process making the result of a determination, generation, selection, sending or receiving available to any interface, hardware element or software element of the distributed computing device(s), or any internal interface, hardware element or software element implemented on the distributed computing device(s). The providing control data may comprise providing a control signal to actuators of the treatment device and/or providing control signals for a display. In an example the control signal is sent to the display device substantially simultaniously with the control signal being sent to the actuators. In this way control data may allow to monitor changes in the treatment device and in particular changes in the nozzle setup and/or in the nozzle configuration. In other words, a control signal may initate the treatment device to activate and/or setup the selected and/or validated nozzle.

In an embodiment, the nozzle configuration may comprise a measure for the orientation of the individual nozzle. Including the orientation has the advantage that the spray characteristics of the nozzle can be tailored such that the target area is evenly treated. This reduces the risk of resistances. In particular, the nozzle configuration may comprise the measure of the orientation of the individual nozzle relative to the moving direction of the treatment device. In an example, this measure may be an angle. This may prevent a shadowing effect that may occur behind a plant seen from the moving direction of the treatment device. Some treatment product require targeting plant leafs, when the treatment device passes the plant, in the moving direction, a shadowing effect may occur that may lead to a reduced amount of applied treatment product.

By including the orientation into the nozzle configuration this can be accounted for. This in turn leads to a a more efficient, sustainable robust way of treating an agricultural field. In these cases the nozzle orientation may be such that a spray jet is directed at least partially against the moving direction of the treatment device. Treatment devices are often configured to obtain field data, e. g via a camera. A nozzle orientation where the spray jet is directed at least partially against the moving direction of the treatment device allows to provide more time between opbtaining field data at a specific location and application of treatment product at that location. This enables a faster speed of the treatment device, e.g. driving or flying speed.

In a further embodiment the operational data or operation data may comprise a targeted and/or current speed of the treatment device. It turned out that the shadowing effect is influenced by the speed of the treatment device. Including the speed of the treatment device for determining the nozzle configuration enables reduction of a shadowing effect. This in turn leads to a a more efficient, sustainable robust way of treating an agricultural field.

In an embodiment, operation data may obtained by the treatment device. Obtaining the operation data with the treatmend device allows considering current data for the validation. This enables an adaption of the treatment based on the obtained operation data. This in turn leads to a more efficient, sustainable robust way of treating an agricultural field. As an example, changes in drive speed may be obtained. Due to changes in operating conditions, it may be appropriate to adapt the nozzle configuration or to halt the treatment. Consequently, the control signal may change based on the result of the validation step. By considering obtained operating data, a suitable nozzle may be selected. This will result in a more precise application of treatment product. The control signal may be derived from the operation data.

In other words, the changes in the operating conditions may result in changes of the operation data. The method may allow to react to such changes and provide amended control data.

In an embodiment the validation step is repeated while treating the field. This allows considerations of current operation data in the validation step. This in turn leads to a more efficient, sustainable robust way of treating an agricultural field.

In other words, the operation data may be gathered before the planned treatment. In this example the operation data may comprise planned setup data for the treatment device which data is/are intended to be used for the planned treatment. In this case the operation data may also comprise prediction data such as the weather forecast and/or wind speed at the time for the planned treatment. In an alternative and/or additional example the operation data may comprise current data gathered during the execution of the planned treatment. In this way corrections may be made to the operation data such as the current wind speed at the time of the treatment and the current data may be used instead of the predicted value. In general, predicted data may be replaced by measured data. The measured data may be provided by the monitoring unit of the treatment device and/or by the distributed system. In an example the method for validating a nozzle configuration for a planned treatment may be executed in a loop during the execution of the planned treatment. In this way a closed loop conficguration may be formed that allow for reacting to changing conditions and/or changing setups during the execusion of the planned treatment.

In an embodiment, the model may comprise a data driven model, a rigorous model or a combination thereof.

In an embodiment, the model may comprise a data driven model. In particular, the data driven model may be based on experiments. Experiments can easily be perfomed under well defined conditions and operation data can be varied over a broad range, without the need to collect operation data in the field. Collecting operation data in the field in a structured way would result in application of treatment product in a field in non optimal conditions, therefore result in pollution of the environment. Currently, simulations are increasingly improving. This allows providing a data diven model based on simulation data. It is also envisioned to provide a data driven model comprising experimental and simulated date. Data driven models are advantageous when rigorous models are missing or to complext to perform the necessary calculations in a reasonable time. In particular on treatment devices and/or handheld devices computational power is limited. Data driven models do not need to perform major calculations and are therefore faster.

In an embodiment field data may be obtained from a monitoring unit and/or a treatment unit attached to the treatment device. The monitoring unit and/or the treatment unit may collect field data. The monitoring unit and/or the treatment unit may provide the field data collected. This allows to base the nozzle validation on current field data. Leading to a more accurate result. Providing control data may be based on the obtained field data. This enables a nozzle validation based on current data. This allows a more efficient treatment. The obtained field data may comprise information related to the current wind speed. In an example a nozzle suitable for the current wind speed may be validated. Providing operation data may include determining or updating treatment unit data based on the field data. Treatment unit data may relate to control parameters of the treatment device. E.g. it may relate to valve or nozzle control parameters for a spray unit to adapt e.g. application rate or voltage control parameters for an electrical system to adapt the strength of the electrical puls. This enables selection of a specific nozzle suited for most efficient application of treatment product.

In a further embodiment providing operation data may be based on a mission schedule, a mission schedule may refer to instructions for treating a field. Misstion schedule may include a date for a planned treatment. When the mission schedule comprises a date, field data for that date may be obtained and provided as operation data. The nozzle validation may then be based on more precise operation data. In an example, a weather forecast data may then be obtained. This allows validation of a nozzle targeted to the conditions in the field at the scheduled time. This in turn leads to a a more efficient, sustainable robust way of treating an agricultural field.

Mission schedule may include an allocation and/or availability of the treatment device for treating the agricultural field. This is beneficial to realize a central architecture with a remote computing device controlling operation of the treatment device. The mission schedule may comprise identification data that includes device identifiers for the treatment device. The device identifier may be associated with a nozzle configuration and/or a nozzle holder available for the treatment device. The mission schedule may comprise geolocation data of a target field. The mission schedule may comprise a digital representation of an agricultural relevant organism. The mission schedule may comprise information assoziated with the treatment product. It turns out that the treatment product has an influence on the spray pattern.

In an embodiment, the control data may cause a display device to visualize the validated nozzle. This enables the operator of the treatment device to monitor the validation. Monitoring may be possible during the operation of the treatment device. In a further embodiment, the control data may comprise instructions for mounting the validated nozzle. This is in particular useful, when setting up the treatment device for a planned treatment. Combining a mission schedule with control data causing the display to visualize the validated nozzle enables preparation of the treatment device ahead of time. This enables configuration of the treatment device prior to the execution of the treatment process. By this preparation of the treatment device ahead of time, logistics can be improved, because availability of suitable treatment devices may be determine. This in turn leads to a more efficient, sustainable robust way of treating an agricultural field. In a further embodiment, the control data may be confirmed in a confirmation step. This allows the user to surveil the control data .which provides a further layer of security. In an example the control data may comprise the visualized nozzle. Confirmation may be e.g. be perfromed by e.g. by touching a touch area on the display device.

In an embodiment, the field data comprises obtained by the treatment device comprise an image of an are in the field to be treated. In particular a ?

The methods disclosed herein may further comprise the step of forwarding the field data and/or the operation data to a remote computing device for storing the field data and/or the operation data for further data processing. Owing to the limited storage capacity of treatment devices and the utilization of big data to enhance treatment operations on the field, remote storage capacity is beneficial. To reduce impact of such forwarding on processing capacities, forwarding may be done through batch data processing.

The systems and computer elements disclosed herein may further be configured to execute the methods described above. The systems may be configured to provide operation data via a cloud environment or a ground station e.g. in a centralized architecture. The systems may be configured to analyse field data and to provide the result of such analysis via the cloud environment or the ground station e.g. in a centralized architecture. The systems may be configured to determine and/or provide control data based on a mission schedule via the cloud environment or the ground station e.g. in a centralized architecture. The systems may be configured to dynamically adjust upon providing the operation data the control data.

In an embodiment, the validation step comprises comparing the determined spray characteristic with a target spray characteristic. Upon meeting the target spray characteristics control data indicating suitability of the validated nozzle for the treatment may be provided. Meeting the targes spray characteristics is understood broadly. Various technical implementations may be realized apparent to a person skilled in the art e. g. defining a threshold and consider meeting as being above the threshold.

In an embodiment, the spray characteristics may comprise a measure for uniformity of a spray pattern of an individual nozzle in a target area. Considering a measure for the uniformity of the spray pattern is beneficial, uniform spray patterns avoid over and underdosing of treatment product in th target area. Considering a measure for uniformity of the spray pattern leads to a more efficient, sustainable robust way of treating an agricultural field. It may be beneficial to predefine the target area.

In an embodiment the spray characteristics may comprise a measure for the spray pattern of an individual nozzle in a non-target area. Considering a measure of the spray characteristics in a non-target area, in particular adjacent to the target are is beneficial. This allows validation of a nozzle having low amounts of treatment product applied in the non-target area. This leads to a a more efficient, sustainable robust way of treating an agricultural field.

The measure for the spray pattern in the non-target area may comprise a measure for the amount of treatment product applied in the non-target area. Considering the amount of treatment allows to validate the nozzle configuration based on the applied product not reaching the target area allows validation of a nozzle that reduces application of treatment product in the non-target area thereby reducing the risk of building of resistances and/or pollution of the environment. Thus leading to a a more efficient, sustainable robust way of treating an agricultural field. The measure for the amount of treatment product applied in the non-target area may be a volume of treatment product in the non-target area.

The measure for the spray pattern in the non-target area may comprise a measure for the non- target area covered by the spray pattern. It is desired to have a small non-target area in the speay pattern. Considering the measure for the the non-target area covered by the spray pattern allows to validate the individual nozzle based on the size of unintended application of the treatment product helps reducing application of treatment product, thereby reducing the risk of building of resistances and/or pollution of the environment. Thus leading to a a more efficient, sustainable robust way of treating an agricultural field. The measure for the non-target area covered by the spray pattern may determined by a of target distance distance between the end of the target-area and the start of an area, where no treatment product is applied. A way for determining this distance is by projection of the spray pattern perpendicular to the movement direction of the treatment device.

The measure for the spray pattern in the non-target area may comprise a measure for the decay of treatment product application in the non-target area. In an example the decay may be defined as slope starting at the mean volume of the volume distribution in the target area over the length of the in the in the off target distance. Considering the decay in the validation step allows validation of individual nozzles with a more precise spray characteristic. This leads to a more efficient, sustainable robust way of treating an agricultural field. In an embodiment the spray characteristics of a nozzle may comprise the measure for uniformity in the target area, the measure for the amount of treatment product applied in the non-target area, the measure for the non-target area covered by the spray pattern, and the a measure for the decay of treatment product application in the non-target area. This allows an easy comparable description of the spray pattern. Including these measures has the advantage that the each measure can be weighted in the validation step. This enables a more flexible situation targeted validation of an individual nozzle. This leads to a a more efficient, sustainable robust way of treating an agricultural field.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following, the present disclosure is further described with reference to the enclosed figures:

Fig. 1 illustrates an example embodiment of a system with a treatment device for treatment of an agricultural field;

Figs. 2 a, c illustrates treamtment devices;

Fig. 2b illustrates a nozzle holder comprising multiple nozzles

Fig. 3 illustrates a further treatment device;

Fig. 4 illustrates spray patterns of a boom sprayer;

Fig. 5 illustrates spray patterns of a band sprayer;

Fig. 6 illustrates spray patterns of a spot sprayer;

Fig. 7 illustrates a user interface for providing operation data;

Fig. 8 illustrates a user interface for providing control data;

Fig. 9 illustrates a block diagram of example computing components of a treatment device;

Fig. 10 illustrates a workflow of validating a nozzle; Fig. 11 illustrates an alternative workflow of validating a nozzle;

Fig. 12 illustrates a spray pattern of an individual nozzle;

DETAILED DESCRIPTION OF EMBODIMENT

The disclosure is based on the finding that for treatment in agricultural fields a nozzle configuration has a huge impact on efficacy of the treatment. Finding a suitable nozzle configuration is difficult, because the operation parameters influence spray characteristics. A suitable nozzle configuration is influenced by operattion data. The operation data may comprise, e. g. treatment device data and/or field data. In an example , operation data may be provided prior to application of the treatment product, in that case, the method and/or apparatus may provide a nozzle recommendation based on the provided operation data. The provided operation data may in particular comprise the type of application, e.g. banding sprot srpaying, boom application, the target organism, the date and the treatment product. This allows to provide a nozzle recommendation prior to a planned treatment. This enables configuration of the treatment device prior to the application of the treatment product. This results in a more precise application of treatment product.

In other cases the field data may not completely known before the treatment devices treat the agricultural field. By monitoring with means of a treatment device during a treatment process of an agricultural field, these specific characteristics of the agricultural field are at least partly revealed. The field data may change during the treatment. The collected information about these specific characteristics serves to beneficially improve the treatment strategy of one or more further treatment devices. By doing so, it is possible to (re-)act on changing conditions in the agricultural field on demand.

The following embodiments are mere examples for implementing the methods, the systems or the computer elements disclosed herein and shall not be considered limiting.

FIG. 1 illustrates a treatment device 102 shown here as part of a distributed computing environment. The treatment device 102 is used for performing and/or conducting an agricultural farming operation on a field which comprises a plurality of geographical locations 108. The farming operation may be a treatment for a crop which comprises a crop plant 114 located at a first geographical location 108a. The farming operation may even relate to a control or eradication of weed plants. 108d may refer to a second geographical location which may also include crop. 108c may refer to a third geographical location, comprising weed. 108b may refer to a third geographical location comprising weed and crop.

The treatment device 102, 105, 107 may include a connectivity interface 104. The connectivity interface 104 may either be a part of a network interface, or it may be separate unit. In this drawing for simplicity it is assumed that the connectivity interface 104 and the network interface are the same unit. The connectivity interface 104 is operatively coupled to a computing unit (not shown explicitly in FIG. 1). The computing unit is operatively connectable to the treatment device 102, 105, 107. The connectivity interface 104 is configured to communicatively couple the treatment device 102, 105, 107 to the distributed computing environment. The connectivity interface 104 can be configured to provide field specific data at the computing unit. Moreover, the connectivity interface 104 can also be configured to provide update data, for example collected at the treatment device 102, 105, 107 to any one or more remote computing resources 106, 110, 112 of the distributed computing environment. Any one or more of the computing resources 106, 110, 112 may be a remote server 106, which can be a data management system configured to send data to the treatment device 102, 105, 107 or to receive data from the treatment device 102. For example, as detected maps or as farming operation maps comprising update data recorded during the farming operation on a geographical location 108a may be sent from the treatment device 102 to the remote server 106, shown in this example as a cloud based service. Any one or more of the computing resources 106, 110, 112 may be a field management system 110 that may be configured to provide a control protocol, an activation code or a decision logic, or in general field specific data, to the treatment device 102 or to receive data, for example, update data, from the treatment device 102, 105, 107.

Alternatively, or in addition, such data may be received by the field management system 110 via the remote server 106 or data management system. Any one or more of the computing resources 106, 110, 112 may be a client computer 112 that may be configured to receive client data from the field management system 110 and/or the treatment device 102, 105, 107. Such client data may include for instance farming operation schedule to be conducted on one or more fields or on the plurality of geographical locations 108 with the treatment device or field analysis data to provide insights into the health state of certain one or more geographical locations or field. The client computer 112 may also refer to a plurality of devices, for example a desktop computer and/or one or more mobile devices such as a smartphone and/or a tablet and/or a smart wearable device. The treatment device 102, 105, 107 may be at least partially equipped with the computing unit, or the computing unit may be a mobile device that can be connected to the treatment device, via the connectivity interface 104. It will be appreciated that the field management system 110 and the remote server 106 may be the same unit. The computing unit may receive the field specific data either via the client computer 112, or it may receive it directly from the remote server 106 or the field management system 110.

In particular when data such as update data is recorded by the treatment device 102, 105, 107, such data may be distributed to any one or more of the computing resources 106, 110, 112 of the distributed computing environment.

Figure 2a illustrates a more detailed view of the treatment device 102. In this example treatment device 102 is equipped with a boom 120, comprising various nozzle arrangements 122, 124, 126 and 128. The limitation to four nozzle arrangements is for illustration purposes only. The nozzle arrangement may comprise a single nozzle or a nozzle holder. The nozzle holder may comprise a plurality of different nozzles.

An example of a nozzle holder is depicted in Figure 2b.

In an embodiment each nozzle arrangement may be activated individually. This allows a more precise adjustment of the spray characteristics of the treatment device 102. On a boom sprayer it may be desired to have different nozzle configurations at edges of the boom compared to the nozzle configurations across the boom, e.g. a nozzle configuration with asymmetric spray characteristics may be desired to prevent non-target application of treamtment product near edges of a field.

Figure 2b illustrates a nozzle arrangement 122 comprising multiple nozzles in a nozzle holder 132, the arrangement in this example comprises three nozzles 122a, 122b, 122c, the nozzles may be selected by rotating nozzle holder 132, nozzle arrangements 124, 126, and 128 may be built in a similar way. The nozzle arrangement 124 comprising the nozzle holder 132 allows to equip the treatment device 102, 105, 107 with nozzles having different spray characteristics.

This allows to adapt the nozzle configuration to conditions in the field without the need to return to the farm and to reconfigure the treatment device by mounting adapted nozzles. In another embodiment, the nozzle arrangement may be controlled based on a control signal. In this case, the nozzle holder may comprise an actuator and the control signal may initiate the actuator to activate a specific nozzle e. g. by rotating the specific nozzle into an activated position. In another example in addition to rotating and/or as an alternative to rotating the nozzels, the different nozzles may be selected by selecteing and/or activating a valve of the respective nozzle. Another example of the treatment device 105 is depicted in figure 2c. In this example, the treatment device is a unmanned areal vehicle (UAV). The UAV may equipped with a nozzle holder 132, similar to the one described with respect to figure 2 b.

Treatment device 105 is therefore enabled to perform a treatment under different conditions. An example may be, a changing weather condition, where the wind speed is increasing. An increasing wind condition may render the active nozzle inappropriate. For example, the droplet size generated with the active nozzle is small, such that a maximum drift will be exceeded for that nozzle. The disclosed method may be used to activate a nozzle that sprays larger droplets, thereby reducing drift. Sensors on the treatment device 105 may detect field conditions e. g. weather conditions and/or environmental conditions. For this treatment device 105 may be equiped with a field sensor e.g. wind sensor for this example. In another example, the wind data may be provided via connectivity interface 104, e.g. from a database and/or from a server. The method of validating a nozzle configuration can advantageously be applied in that scenario. The treatment devices 102 amd 107 may also be equipped with sensors for detecting field conditions.

Fig. 3 shows yet another example of a large-scale treatment device such as the field sprayer 107, that includes spray nozzles 107a or nozzle holders 132 comprising various individual nozzles 107a for treatment. The nozzle holder 132 may be similar to the nozzle holder described in accordance with figure 2b. It is noted that Fig. 10 is merely schematically illustrating main components, wherein the field sprayer 107 may comprise more or less components than shown.

Spray nozzles 107a may exhibit different nozzle configurations, e.g. different spray patterns, orifice sizes, orientations.

The field sprayer 107 may be part of the system shown in Fig. 1 and configured to apply treatment product to the field 108 or to one or more subareas thereof. The field sprayer 107 may be releasably attached or directly mounted to a tractor. In at least some embodiments, the field sprayer 107 comprises a boom with multiple spray nozzles 107a arranged along the boom. The spray nozzles 107a and or nozzle holders 132 may be fixed or may be attached movably along the boom in regular or irregular intervals. Each spray nozzle 107a may be arranged together with one or more, preferably separately, controllable valves 107b to regulate fluid release from the spray nozzles 107a to the field 108. One or more tank(s) 107c,d,e are placed in a housing 107f and are in fluid communication with the nozzles 107a through one or more fluidic lines 107g, which distribute the one or more treatment product(s) or composition ingredients like water to the spray nozzles 107a. This may include chemically active or inactive ingredients like a treatment product or mixture, individual ingredients of the treatment product or mixture, a selective or non-selective treatment product, a fungicide, ingredients of a fungicide mixture, a plant growth regulator, ingredients of a plant growth regulator mixture, water, oil, or any other treatment product. Each tank 107c,d,e may further comprise a controllable valve to regulate fluid release from the tank 107c,d,e to the fluid lines 107g.

For monitoring and/or detecting, the field sprayer comprises a detection system 107h with multiple monitoring units 107i arranged along e.g. the boom. The monitoring units 107i may be arranged fixed or movable along the boom in regular or irregular intervals. The monitoring units 107i may be configured to sense field data and to derive one or more conditions of the field 107j. The monitoring units 107i may be optical components providing images of the field 112.

Suitable optical monitoring components 107i are multispectral cameras, stereo cameras, IR cameras, CCD cameras, hyperspectral cameras, ultrasonic or LIDAR (light detection and ranging system) cameras. Alternatively or additionally, the monitoring components 107i may comprise further sensors to measure humidity, light, temperature, wind or any other suitable condition on the field 108.

The obtained field data may be provided as operation data to a nozzle validation apparatus. From data obtained from optical monitoring components a target area may be determined. In some embodiments, the velocity of the sprayer may be provided and a nozzle is validated based on the determined target area and the velocity of the sprayer.

The sprayer may further comprise an actuator for adapting the nozzle orientation of an individual nozzle based on the received control signal.

In at least some embodiments, the monitoring units 107i may be arranged as shown in Fig. 2a with units 107i perpendicular to the movement direction of the treatment device 107 and in front of the nozzles 107a (seen from drive direction). In the embodiment shown in Fig. 10, the monitoring units 107i are optical monitoring units 107h and each monitoring unit 107i is associated with a nozzle holder 107a such that the field of view comprises or at least overlaps with the spray profile of the respective nozzle holder 107a once the nozzle reach the respective position. In other arrangements each monitoring unit 107i may be associated with more than one nozzle holders 107a or more than one monitoring units 107i may be associated with each nozzle holder 107a. Nozzle holders 107a may comprise the features as described with respect to figure 2b.

The monitoring units 107i, the tank valves and/or the nozzle valves 107b are communicatively coupled to a control system 107k. In the embodiment shown in Fig. 10, the control system 107k is located in a main housing 107f and wired to the respective components. In another embodiment monitoring units 107i, the tank valves or the nozzle valves 107b may be wirelessly connected to the control system 107k. In yet another embodiment more than one control system 107k may be distributed in the device housing 107f and communicatively coupled to the monitoring units 107h, the tank valves or the nozzle valves 107b.

The control system 107k may be configured to control and/or monitor the monitoring components 107i, the tank valves or the nozzle valves 107b based on a control file or operation data provided by a control file and/or following a communication control protocol. In this respect, the control system 107k may comprise multiple electronic modules. One module for instance may be configured to control the monitoring units 107i to collect field data such as images of the field 112. A further module may be configured to analyze the collected field data such as the images to derive parameters for the tank or nozzle valve control 107b. A further module may be configured to receive the operation data to derive a control signal. Yet further module(s) may be configured to control the drive system, the tank valves and/or nozzle valves 107b based on such derived control signal.

As described above, the field sprayer 107 comprises or is communicatively coupled to the monitoring units 107i, such as image capturing devices 107i, and is configured to provide one or more images of the area of interest to the control system 107k, e.g. as image data which can be processed by a data processing unit. It is noted that both capturing the at least one image by the monitoring unit 107i and processing the same by the control system 107k is performed onboard or through communication means during operation of the field sprayer, i.e. in real-time. It may further be noted that any other dataset than image data from which field conditions are derivable may be used.

The monitoring unit(s) 107i may provide operation data. This operation data may then be used for providing control data according to the method described in figures figures 10 and 11.

Figure 4 illustrates a close up view of boom 120 in broadcast application. In broadcast application the agricultural field is treated along the width of the boom. In order to enable even application of the crop protecting product. Most booms provide a fixed spacing between two adjacent active nozzles 142 between adjacent nozzles, is typically fixed. Currently a coarse rule of thumb for nozzle selection is applied by farmers. The spray angle of the nozzle should be chosen, such that at a desired spray height 130 the overlap between the nozzle cones is 100%.

Quality of the spray pattern is then visualized by spraying on the ground and/or by simulating the spray pattern and/or by calculating the spray pattern. The spray angle alone already depends on various parameters and/or operation data, such as e.g. pressure, viscosity of the crop protection product. It is clear that this coarse approach does yield in inefficient use of crop protection product. In case of application of pesticides an inefficient application may lead to overdosing, which stresses the environment or underdosing, which bears the risk of resistant pest organisms. The disclosed method enhances the spray pattern of broadcast applications, by considering the spray characteristics of each individual nozzle on the boom. Each nozzle along the boom can be identified by its location on the boom. The spray characteristics all nozzles on the boom may be determined by summing/integrating spray characteristics of the individual mounted nozzles along the boom. In other words, the spray characteristics result of a combination of the spray characteristics of all active nozzles on the boom may be determined by summing and/or integrating spray characteristics of the individual mounted nozzles along the boom The resulting width of the boom spray characteristics 140’ is denominated 150. A measure 160 for the quality of the spray characteristics of a boom is often provided as coefficient of variation (CV), which is a statistical method used for determining spray uniformity across a spray boom.

Figure 5 illustrates a boom configured for a banding application. In banding, the agricultural field is arranged in bands. Returning back to figure 1 , the band may refer to the spacing between the first 108a and the second geographical location 108d. In this example, we envision application of applying a fertilizer on geographic location 108a and 108d without fertilizing the third geolocation 108c. For this the nozzle spacing between two adjacent active nozzles 142 is set to the distance between the rows of crop plants. The objective is to target rows comprising crop evenly and completely, while not applying treatment to areas between rows. In this example illustrative spray characteristics of nozzles are shown.

Nozzles 122a and 126a exhibit a broad width, indicating, that the treatment will not only cover the crop in the first 108a and second 108d geographical location, but also spray into areas that are not intended, e.g. 108c. Furthermore, the lateral distribution of nozzle 122a and 126a is uneven, leading to a high dose potentially to high in the middle of the first and second geographical locations and a potential underdosing around the edges of the respective geographical locations.

Second set of nozzles 122b and 126b provide a sharper lateral distribution of the spray characteristics. This reduces overspray into the third geographical location, but the spray characteristics across each respective geographical location is even more uneven.

Finally, third spray characteristics are illustrated in figure 5. The spray characteristics associated with nozzles 122c and 126c are essentially constant across the first and second geographical locations and provide a very sharp drop around the edges of the respective geographical location. It is clear that nozzles 122c and 126c with the shown spray characteristics are desirable and will provide best treatment in both, evenness of the application as well in least overspray. For banding application, the operating parameters may include a target size associated with the width of first and second geographical location 108a, 108d respectively.

A further example illustrating the selection of appropriate nozzles is shown in figure 6. Here the method of selecting a nozzle is applied to a spot application. For spot application the objective corresponds essentially to the objectives for band application with the difference, that only one nozzle needs to be considered. For use in spot application the operating parameters may further include a target spot size.

Figure 7 illustrates a user interface according to one embodiment. The user interface allows to provide operating parameter and/or operation data. The user interface allows to select an application type, e.g. broadcast, banding, boomless, spot application. In this example spot application is selected. The menu may then enable selection of a target size. The target size may be related to the planned treatment. The target size be provided in units of an area or a length. In this example the target size is provided by a length. Additionally in this example, the drive speed or estimated wind speed during treatment can be entered. Optionally the crop protection product may be entered. The provided data may then be used in selecting a nozzle.

In an example the operation data is separated into operation data relating to input data of the model and operation data relating to the planned treatment and/or target data. Based on the target data a desired target spray characteristic is determined, in particular a target spray characteristic for the boom is determined. Based on the input data and the model a model based spray characteristic is determined and/or calculated. The desired target spray characteristic is compared with the determined and/or calculated model based spray characteristic. In this way an individual nozzle which may be selected for the planned treatment is validated based on the determined and/or calculated spray characteristics of the individual nozzle and one or more reference spray characteristics.

Figure 8 illustrates a user interface according to one embodiment. The user interface provides control data generated according to the methods disclosed herein. The control data in this example may comprise a validated nozzle typ, a boom height and a drive speed. In an embodiment, the control data may directly be applied to the treatment device. In further examples, the control data may be confirmed in a confirmation step. This allows the user to surveil the control data .which provides a further layer of security.

Fig. 9 illustrates a block diagram of example internal components of the treatment device 102, 105, 107, illustrated in Figs. 2a, 2b or 4.

The treatment device 102, 105, 107 includes a treatment unit 130 including actuator(s) 134 and an actuator control 136. The actuator(s) may include engine actuators, steering actuators which may be used to maneuver the treatment device 102, 105, 107. The actuator(s) may control a nozzle arrangement based on a control signal. The control signal may initiate the actuator to activate a specific nozzle e. g. by rotating the specific nozzle into an activated position. The actuator(s) may include treatment actuators configured to treat the field 112 and/or to provide field data e.g. via the actuator control 136. The actuator control 136 may include subunits such as an obtaining unit, a providing unit or a control unit. In an example the actuator control 136 is adapted to provide a setup and/or configuration of the actuator(s) 134.

The treatment device 102, 105, 107 further includes a monitoring unit 132 with sensor(s) 138 and an sensor control 140. The sensor(s) 138 may include an accelerometer, a gyroscope, and a magnetometer which may be used to estimate acceleration and speed of the treatment device 102, 105, 107. The sensor(s) 138 may include field monitoring sensor(s) configured to sense field conditions and to provide field data. The sensor control 140 may include subunits such as obtaining unit, providing unit or control unit.

The treatment device 102, 105, 107 includes a processing device 142 configured to control or monitor the treatment device 102, 105, 107 on the field 112.

The treatment device 102, 105, 107 also includes an onboard memory 148 for storing e.g. the field data, the operation data or the like. The treatment device 102, 105, 107 further includes a positioning system 146 configured to provide the current position of the treatment device 102, 105, 107 such as a global positioning system (GPS) or a camera based positioning system e.g. based on optical flow.

For communication with other devices such as the ground station 110 or other treatment devices 102, 105, 107 or the cloud environment 100 the treatment device 102, 105, 107 includes a wireless communication interface 144. The wireless communication interface 144 may be configured with one or more cellular communication circuitrie(s), such as 4G or 5G circuitry, or one or more short range communication circuitrie(s), such as Bluetooth or ZigBee interfaces. The wireless communication interface 144 enables communication with other devices of the distributed system, such as, the ground station 110, the cloud environment 100 or a remote controller 108. The cloud environment 100 access may be provided via the communication interface 144 of the treatment device 102, 105, 107 or via a client device 108 such as the remote controller 108 of the treatment device 102, 105, 107 or via the ground station 110.

Figure 10 illustrates a workflow according to an embodiment. In step 702 operating parameters are provided. The provided operating parameters may be provided via user interface as depicted in figure 8. At step 704 the system is initialized by selecting a start nozzle from a data base comprising a selection of nozzles. In step 706 spray characteristics for the selected nozzle are determined based on the provided operating parameters. In one embodiment, a model may be provided for determining the spray characteristics of the selected nozzle. The determination step may comprise determination based on the provided operating parameters and a model associating operating parameters to spray characteristics of individual nozzles. The model may be a data driven model or based on physico-chemical models. Due to the complexity of the operating parameters a data-driven model may be advantageous.

In one embodiment, the data driven model may include a data base comprising data associated with measurements spray characteristics of individual nozzles under various operation conditions.

In another embodiment the model may be a statistical model. The statistical model is an example for a model that is adapted to simulate and/or calculate the individual nozzle characteristic and/or the combined boom characteristic.

For the sake of illustration, the model in this example is a database. At step 708 the spray characteristics are validated. This validation may be performed by a comparison with the target spray characteristics. When the target spray characterics are met, a selection signal may be provided at step 710. The control signal is indicative of a validated nozzle. In an example the control signal may be suitable for controlling a display device for displaying the type and/or brand of the selected nozzle. In another embodiment, the selection signal may initiate the treatment device 102, 105, 107 to activate the selected nozzle.

In an alternative embodiment, shown in figure 11 , operation data are provided at step 802. The provided operating parameters and/or operation data may be provided via user interface as depicted in figure 7. At step 804, for initialisazion a start nozzle, nozzle (k) is selected from a database of available nozzles. In step 806, the spray characteristics for nozzle (k) are determined, based on the operating parameters and/or operation data and the nozzle (k).

The determination step may comprise determination based on the provided operating parameters and/or operation data and a model associating operating parameters to spray characteristics of individual nozzles. The model can be a model as described with respect to figure 10.

In this example, shown in figure 11 , a loop starts to determine the spray characteristics of all available nozzles. The spray characteristics of individual nozzles are then pairwise compared. If a spray characteristic is inferior, the respective nozzle is discarded and a next nozzle is selected for determining the spray characteristics. At the end of this loop, a nozzle with optimal spray characteristics is identified. A control signal may finally be provided. The control signal is indicative of the validated nozzle (k). In an example the control signal may be suitable for controlling a display device for displaying the type and brand of the selected nozzle. In another embodiment, the control signal may initiate the treatment device 102 to activate the selected nozzle.

This easy algorithm is for illustration purposes only, there are various ways of finding an appropriate nozzle.

Figure 12 depicts a sketch of a spray pattern of an individual nozzle. Denominated as 122a is an individual nozzle. A spray cone is illiustrated. For illustration purposes the amount of treatment product applied by the nozzle is depicted as filling level of vials across an axis of the area.

The spray pattern may be characterized by a measure for uniformity of a spray pattern of an individual nozzle in a target area easure for uniformity of the spray pattern of the individual nozzle. This measure may e.g. be a coefficient of variation of a nozzle (CV_nozzle), which is a statistical method used for determining spray uniformity across a target area, based on the ratio of the standard deviation to the mean and shows the extent of variability in relation to the mean of the volume of treatment product in the target area across the target area.

The spray pattern may be characterized based on a measure for application on a non target area. The non-target area may be directly adjacent to the target area. The width of the nontarget area may be defined as the region between the target area and the region, not covered by the treatment product, e.g. no fluid volume is deposited. A small non-target area reates to a more precise application. In other words, a good and/or optimal spray characteristic is a nozzle and/or a combination of nozzles that generate(s) a small non-target area. In this way a spray pattern with a lower and/or smaller non-target area is better than a spray pattern with a broader and/or larger non-target area.

The spray pattern may also be characaterized by a slope indicative of the decay of the deposited treatment product across the non-target area. A steep slope relates to small overdosing in the non-target area.

In an embodiment, the spray pattern may be characterized by a combination of the three measures described above. In particular a combination of the measures of application in the non-target areas is beneficial. This allows not only to focus on the size of the non-target area but also on the distributiuon across the non-targe area. The three measures may comprise uniformity of a spray pattern of an individual nozzle, the application on a non target area and/or the slope indicative of the decay of the deposited treatment product across the non-target area.

The present disclosure has been described in conjunction with a preferred embodiment as examples as well. However, other variations can be understood and effected by those persons skilled in the art and practicing the claimed invention, from the studies of the drawings, this disclosure and the claims. Notably, in particular, the any steps presented can be performed in any order, i.e. the present invention is not limited to a specific order of these steps. Moreover, it is also not required that the different steps are performed at a certain place or at one node of a distributed system, i.e. each of the steps may be performed at a different nodes using different equipment/data processing units.

In the claims as well as in the description the word “comprising” does not exclude other elements or steps and the indefinite article “a” or “an” does not exclude a plurality. A single element or other unit may fulfill the functions of several entities or items recited in the claims. The mere fact that certain measures are recited in the mutual different dependent claims does not indicate that a combination of these measures cannot be used in an advantageous implementation.

Claims

1. A computer implemented method for validating a nozzle configuration for a planned treatment of an agricultural relevant organism on an agricultural field, comprising the steps of: providing operation data associated with the planned treatment, determining one or more spray characteristics of an individual nozzle based on the provided operation data with a model relating operation data to one or more spray characteristics, validating the individual nozzle for the planned treatment based on the determined spray characteristics of the individual nozzle and one or more reference spray characteristics, generating control data in response to the validation step, providing the generated control data.

2. The method according to claim 1, wherein the operation data comprises field data and/or treatment device data.

3. The method according to any one of the preceding claims, wherein the operation data is obtained by the treatment device.

4. The method according to any one of the preceding claims, wherein the operation data comprises a targeted and/or current speed of the treatment device.

5. The method according to any one of the preceding claims, wherein the field data comprises an image of a plant.

6. The method according to claim 1, wherein validating comprises comparing the determined spray characteristic with a target spray characteristic.

7. The method according to any one of the preceding claims, where in the spray characteristics comprises a measure of the orientation of the individual nozzle.

8. The method according to any one of the preceding claims, wherein the spray characteristics comprise a measure for uniformity of a spray pattern of an individual nozzle in a target area.

9. The method according to any one of the preceding claims, wherein the spray characteristics comprise a measure for a spray pattern of an individual nozzle in a nontarget area.

10. The method according to claim 9, wherein the measure measure for a spray pattern of an individual nozzle in a non-target area comprises a measure for the amount of treatment product applied in the non-target area.

11. The method according to claim 9, wherein the measure for the spray pattern in the non- target area comprises a measure for the decay of treatment productapplication in the non- target area and/or a measure for the non. target area covered by the spray pattern.

12. Use of a treatment device (102, 105, 107) or a treatment product based on control data generated in a method according to any one of the claims 1 to 11 or use of operation data obtained by a method according to any one of the claims 1 to 11 for operating at least one treatment device (102, 105, 107).

13. A system for validating a nozzle configuration, the system comprising an input interface for receiving operation data an output interface for providing control data and a processing device configured for determining one or more spray characteristics of an individual nozzle based on the provided operation data with a model relating operation data to one or more spray characteristics, validating the individual nozzle for the planned treatment based on the determined spray characteristics of the individual nozzle and one or more reference spray characteristics, generating control data in response to the validation step, providing the generated control data.

14. A treatment device comprising: a nozzle holder, comprising at least two nozzles and a motor for activating a specific nozzle, a communication interface for receiving control data provided by the method of validating a nozzle configuration according to any one of claims 1 to 11 , a motor controller configured for controlling the motor based on the control data, Computer element with instructions, which, when executed on one or more computing device(s), is configured to carry out the steps of the method according to any one of the claims 1 to 11.