Method for operating a harvester using a plant growth model - Patents.com

Abstract

To provide a method by which an operating value for at least one working part of a harvesting machine can be determined easily and well.SOLUTION: The invention relates to a method for operating a harvesting machine for harvesting a crop in a field, at least one operating value for a working part of the harvesting machine being determined in dependence on at least one plant property of the crop. According to the invention, the plant property is mapped in a plant growth model, the plant growth model modelling a development over time of the plant property and determining a predictive value or a predictive characteristic of the plant property for the time of the harvest.SELECTED DRAWING: None

Description

[Technical field]

[0001] The present invention relates to a method of operating a harvester to harvest a crop in a field, the method comprising the steps of: and wherein at least one operating value of the plant is determined based on plant characteristics of said crop.

[0002] The speed at which the harvester travels through the field to harvest the crops planted in front of it is determined by the harvesting speed. An example of such an operating value for the drive motor or gear mechanism of a machine is shown in FIG. A control device that provides a value for the driving speed depending on the plant characteristics in the form of the height or density of the crop canopy has been disclosed.

[0003] DE4431824C1 describes how to operate a combine harvester using a data register. The data stored in this data register is based on position coordinates. The yield data is specific to the area and has been determined in the past. The yield of the crop in this case is also a plant characteristic. Based on the current position coordinates of the combine harvester, data from the data register is It is used to calculate the setpoint for the drive speed of the combine harvester. However, historical data that can only be applied to a certain extent to the current harvest situation is used. .

[0004] DE102005000770B3 uses georeferenced data to combine A method for controlling the actuators of the harvester is described, and these data are used to estimate the yield of biomass. This biomass data is collected and recorded during the Biomass Network (Biomassenetwicklung). This is used to create a lens map for controlling the combine harvester. In an exemplary embodiment, the biomass community is harvested by germinating the biomass During the development of the island, it will be surveyed on a georeferenced basis by satellite-aided detection systems. Omass communities can likewise be considered plant traits and are recorded on biomass community maps. However, this method requires a large amount of information about the crop, which affects the operating values ​​of the various operating parts of the harvester. In addition, the time between the last recording of the biomass canopy and the time of harvest cannot be detected. There may be a period of time during which the grain moisture content or straw moisture content (Kornfeu Dry periods or heavy rains that can have a significant impact on plant characteristics such as soil erosion (chte or Strohfeuchte) This means that pre-harvest events such as the above will not be taken into account.

[0005] EP2586286B1 describes a method for detecting at least one of the grains of a crop by a sensor assembly arranged on a harvester. The idea is to emit non-contact signals for single plant characteristics and use them to derive statistics. A method for predictive survey of crops gripped by a harvester is disclosed. The measurement device detects the plant characteristics of the crop actually gripped by the harvester. The unit automatically determines the relationship between the sensor assembly signal and the measurement device signal statistics. These relationships are then taken into account in the calculation of the plant characteristics of the crop being clamped. The signal of the sensor assembly is used to control the travel speed of the harvester taking into account the determined relationship. As a result, the driving speed is an absolute measurement of the non-contact sensor of the sensor device. However, in practice this does not always work accurately enough.

[0006] EP2803256A1 discloses a method for detecting crops in front of a harvester without contact. The document discloses a combine harvester in which a sensor for detecting the temperature is mounted on the roof of the driver's cab. is used to prepare data on predicted mass throughput. The speed throughput is determined by a measuring device. The measured and predicted mass throughput are compared to each other and the result of the comparison is the harvester travel speed. It is designed to be used as a feedback value to set the The operating values ​​of the specific operating parts of the combine harvester depend on the plant characteristics and can be measured by the measuring means. The detection of the temperature is extremely difficult and often inaccurate. Of course, there is also the problem that the algorithm can only predict plant characteristics to a certain extent. This means that there is a great need for control over the operating parameters of the combine harvester.

[0007] Thus, the present invention provides a method for easily and satisfactorily determining the operating value of at least one operating part of a harvester. The present invention is based on the object of providing a method for operating a harvester to harvest a crop, which can

[0008] The object on which the invention is based is achieved by means of the feature combinations according to claim 1. Further embodiments can be seen from the dependent claims. The travel speed of the harvester during harvesting is also to be understood as an operating value for the operation of the harvester.

[0009] According to claim 1, at least one plant characteristic is mapped in a plant growth model. (die wenigstens eine Pflanzeneigenschaft in einem Pflanzenwachstumsmodell abge The plant growth model models the development of the plant properties over time. and determining a predicted value or predictive signature of said plant property at harvest.

[0010] The at least one plant characteristic may be a biomass of the crop. The temperature is also mapped to the plant growth model as a plant property whose development over time is modeled. A predicted harvest date, for example for crop canopy height, is then determined from this modelling. It can be done.

[0011] Further examples of plant properties that can be recorded in plant growth models are the straw properties for cereals. Yield data for corn and grain, grain moisture content and straw moisture content, Cob diameter, initial growth height of corn cob, corn stalk diameter, individual grain size (1,000 kernel weight) (Tausendkorngewicht), shedding tendency (degree of collapse of ears), protein content in the case of cereals, and disease pressure (mycotoxin content), community height and location risk.

[0012] Preferably, the plant growth model records many different plant characteristics. or at least one plant characteristic is mentioned, this is based on the plant growth model. This includes all other plant characteristics that are modeled.

[0013] For example, for corn as a crop, the diameter of the corn cob, the diameter of the corn stalk The plant characteristics of the initial growth height of the corn cob and the corn cob were taken into account, and the plant growth model was For example, one or more additional plant characteristics, such as crop yield data, are derived. In general, one or more plant characteristics may be used to produce a second plant. The trait is derived from the first plant trait. Correspondingly, the plant growth model is If temporal variation in plant quality is available, the derived second plant trait is expressed in terms of its temporal variation. This enables

[0014] The harvester may be a combine harvester, a forage harvester or a planting or Lying crops are picked up from the field and collected, possibly exposing them to the elements. The process step may be carried over to another machine.

[0015] In the case of combine harvesters, height-adjustable cutting devices are used to harvest grain crops, especially cereals. A cutting unit may then be used, which is then rotated through the threshing unit in order to separate the grain from the straw. The threshing unit can be supplied with a threshing net with a drum. The threshing intensity can be increased or decreased by adjusting the threshing gap between the drum and the receiving net. After the threshing step, a separation device may be placed, in which the remaining grains that were not completely threshed and The grains and ears are separated from the straw. In the cleaning device, further separation of the grain and non-grain components is performed. The cleaning device preferably includes a sieve and a blower, and the air flow (wind) acts on the sieve. This airflow allows lighter ingredients, such as non-grain ingredients, to be blown away rather than falling through the sieve. , thus serving the purpose of being separated from the grains which have fallen through the sieve.

[0016] For example, if straw moisture content is mapped by a plant growth model, according to the invention: A predicted value of straw moisture content can be determined for the time of harvest. Higher values ​​are calculated using plant growth models. If the threshing unit is operated at a higher speed, a correspondingly higher threshing drum speed (operating value) is provided to the threshing unit (operating part). The air flow can also be calculated (where the air flow is the possible operating value of the blower as the working part). Correspondingly, straw with a higher moisture content is heavier and can only be blown by a stronger air current. can be set higher since it is not possible to

[0017] For forage harvesters, straw moisture content is an influencing variable for setting the chopping length. For dry silage, a short chop length is advantageous to allow adequate compaction. be.

[0018] If individual grain size (thousand kernel weight) is recorded as a plant characteristic by the plant growth model, the threshing process The threshing gap between the drum and the receiving net can be set based on this parameter. The strength of the fan airflow can be reduced, which would otherwise cause excessive air pollution within the cleaning device. This is because a proportion of the kernels are blown away together with the non-kernel components. If sufficient grain (the extent to which the ears break apart) is available at harvest, this can be achieved by threshing the ears in the case of fragile ears. To weaken the cleaning devices downstream of the knit, the threading drum speed can be set to a rather low value. This is because a lower threshing drum speed generally results in a lower proportion of short rods in the cleaning device. It is.

[0019] The spacing of the clamping plates can also be adjusted according to the method of the invention based on the plant characteristics of the crop. For example, a plant growth model specifies a value for corn stalk diameter. In this case, the spacing of the clamping plates can be adjusted accordingly. The spacing of the support plates ensures a clean feed and reduces the risk of clogging. Thus, the method can also provide corn cob diameter as an influencing variable for the gap between the clamping plates.

[0020] The early growth of the corn cob can also be modeled using a plant growth model. The height can be used as an influencing variable for the height of the cutting unit. The lower the cut, the smaller the risk of damage and the lower the power requirements for the cutting unit. The height of the cutoff unit is determined based on the height of the crop canopy calculated by the plant growth model or the storage risk. It may also depend on

[0021] In the case of corn, biomass is the preferred or optimal running distance for the forage harvester. Straw yield data for cereals can be used as an influencing variable in determining the run speed. This can affect the travel speed of the harvester. The actuator can be used to set the speed of airflow within the cleaning device. If the model results show a very low value for the grain moisture content (very dry corn ), and a corresponding setting of the actuator can be made accordingly so that fewer broken grains are produced. .

[0022] A further example is yield formation in the cob of the corn plant. If there is a trace, not all of the early kernels will be fertilized. This relationship can be reproduced in a plant simulation model, but the remote control of the harvester It cannot be reproduced by means of sensing sensors or environmental detection sensors.

[0023] The predicted values ​​or characteristics of plant properties in the field can be determined in a georeferenced manner. This is because the predicted values ​​or features of plant properties correspond to a certain spatial resolution. This means that the result of such an assignment is Plants can be imaged at high spatial resolution, for example 100x100m, 50x50m or even 5x5m. A map representing the values ​​of the properties, either absolute or relative, of one or more plant properties. , can be stored for each area element. For each area element, for example, …5”, up to 5 or “very small, small, medium, large, and very large”. This map or the corresponding The data records may be fed to a control device of the harvester, which then controls the individual operations. The operating parts are set so that their operating values ​​give the optimum result for the harvest. The researchers only provide suggestions to the harvester drivers, who then incorporate them from their own personal experiences. It is also possible to set the individual operating values ​​of the actuators yourself after comparing them with these values.

[0024] The plant growth model determines predicted values ​​or predictive characteristics of plant characteristics at harvest time, The time period may be, for example, the week or day that harvesting occurs. However, it may vary over the course of a day. To be able to accurately identify the values ​​or characteristics of plant properties in this way, this period is short. It may be a few hours, e.g., less than 3 hours. Thus, the harvesting process is performed without external support. In another exemplary embodiment, the preferred or optimal The timing is calculated using a plant growth model.

[0025] In one exemplary embodiment, meteorological data that may affect the characteristic values ​​of plant properties is used. For example, temperature, atmospheric humidity, hours of sunlight and / or precipitation are controlled, preferably by high spatial resolution. These variables, on the one hand, have a decisive influence on crop growth and on the other hand, On the other hand, these variables also affect many plant characteristics, e.g. In some cases, it can have a direct effect on some plant properties, such as water content.

[0026] In the method according to the invention, soil data influencing crop growth may also be used. For example, soil moisture content may be calculated at different times during the growing season as a function of the area of ​​the field. Based on this value, the plant growth model then models the amount of water the crop extracts from the soil. The moisture content of the soil is preferably high, again with respect to the individual area elements. It is expressed in spatial resolution and, again, can be calculated taking meteorological data into account.

[0027] In one exemplary embodiment, the plant growth model is based on remote sensing data recorded by satellite. For example, vegetation indices (e.g., NDVI) are based on satellite data. It can be calculated in a georeferenced manner and used to derive field biomass. Such data on vegetation indices, on the other hand, cannot be detected by remote sensing. On the other hand, remote sensing data can serve as a basis for other plant characteristics that cannot be determined by the Used to verify and correspondingly adapt certain assumptions in growth modeling For example, if a plant growth model calculates the biomass of a field, this plant characteristic The properties can be confirmed and possibly adapted using satellite data. .

[0028] In addition, soil moisture on the ground can be measured by remote sensing means. The dampness of the ground can then be taken into account in the calculation of the water content of the soil. In this case, the plant growth model uses data on ground moisture indirectly, specifically on the soil moisture content. The moisture content is only used by modeling the moisture content. Based on the signal of the measuring device, a predicted value or predicted characteristic of the plant property can be obtained. The measuring device can be a non-contact sensor and / or a real harvested crop. For example, the non-contact sensor may be mounted on the roof of the harvester's cab. The system is designed to measure the height of crop canopies, and the measurements are fed into a plant growth model. This can be used to verify and possibly adapt the calculated canopy height. It was found that the canopy height calculated by the growth model deviated from the measured canopy height. In other words, at least this plant characteristic can be modified accordingly based on this deviation. Such modifications (Kalibrierung) may also affect other plant properties, which in turn The corrections can be made once at the beginning of the harvesting operation or once during the harvesting process. This can be done continuously, i.e. while the harvester is driving through the field and collecting the crop.

[0029] Corrections may also be made by sensors on the actual harvested crop. Thus, the weight of the harvested kernels is calculated based on the plant life, taking into account the specific kernel losses of the harvester. The weight that would have been harvested based on the breeding model can then be compared to the corresponding This calibration can also be done in a georeferenced fashion. where the sensor georeferenced yield data for the actual harvested crop is , and compared with the corresponding georeference of the plant growth model data.

[0030] Historical values ​​from previous growing seasons or previous harvests may be used in modeling plant characteristics. In this way, certain assumptions in the modelling of plant properties can be verified and refined more accurately. It can be formulated.

[0031] The field can be divided into plots, and then a first group of plots that differ from each other in terms of plant characteristics and At least one second group of compartments can be distinguished between, for example, crop proteins. A content threshold can be defined so that all compartments below that threshold are assigned to the first group. All compartments characterized by a protein content above the threshold are assigned to group 2. Depending on the spatial resolution, these sections can be individual area elements, but they can also be complex. In an exemplary embodiment, the first group of sections is first, then the second group of sections is second. Two groups of plots are harvested. In this way, selective yields characterized by different protein contents can be obtained. It is possible to carry out harvesting.

[0032] Another possibility is that the first crop container is harvested in one of the plots in the first batch. The first crop container is filled when the second crop container is harvested, and the second crop container is filled when harvesting is carried out in one of the plots of the second group. In this case, the harvester selects the first crop component according to the protein content as a plant characteristic. and a separation device for filling the tena or the second crop container. In this case, the speed of the harvester and the separation device of the harvester from certain area elements of the field are Certain time delays caused by the time it takes to transport goods may be taken into account.

[0033] Another application for selective harvesting as mentioned above is mycotoxin content, which is also Again, selective harvesting can be the result of calculations of a plant growth model at different times. By harvesting the plots (first with somewhat lower mycotoxin content, then with somewhat higher mycotoxin content) The plots with high mycotoxin content can be harvested or separated. The separation device is activated to separate the crop from either the first crop container or the second crop container. This can be done by a method of supplying goods.

Claims

1. 1. A method of assisting operation of a harvester for harvesting a crop in a field, comprising: mapping plant traits of the crop in a plant growth model, the mapping modeling the development of the plant traits over time as a plant simulation model; determining a predicted value or predictive characteristic of said plant property at harvest with said plant growth model; determining at least one operating value of an operating part of a harvester based on a predicted value or a predicted characteristic of at least one plant characteristic of said crop at harvest time; setting, by a control device, at least one operating value of an operating part of the harvester in response to a result calculated by the plant growth model. Including, The method, wherein the plant characteristic is one or more selected from the group consisting of crop canopy height, crop canopy density, and crop biomass.

2. 2. The method according to claim 1, wherein a combine harvester or a forage harvester is used as the harvesting machine.

3. The method according to claim 1 or 2, wherein the predicted values ​​or characteristics of the plant properties are determined in a georeferenced manner.

4. The method according to any one of claims 1 to 3, wherein a measuring device is attached to the harvester and the predicted value or characteristic of the plant property is modified based on a signal of the measuring device.

5. The method of claim 4 , wherein the measurement device comprises a non-contact sensor.

6. The method according to any one of claims 3 to 5, wherein the field is divided into plots and a first group of plots and at least one second group of plots are distinguished based on the plant characteristics.

7. 7. The method of claim 6, wherein the first group of plots is harvested first, followed by the second group of plots.

8. 7. The method of claim 6, wherein the first crop container is filled when harvesting is performed on one of the plots in the first group, and the second crop container is filled when harvesting is performed on one of the plots in the second group.