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

Abstract

To operate a harvester using a plant growth model.SOLUTION: The present invention describes a method for operating a harvester for harvesting a harvest in a field related to a method for determining at least one operation value of an operation mechanism of the harvester based on at least one plant characteristic of the harvest. In the present invention, the plant characteristic is mapped on a plant growth model, and the plant growth model models a chronological growth of the plant characteristic and determines a prediction value or a prediction characteristic of the plant characteristic during a harvest period.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates to a method for operating a harvester for harvesting a crop in a field, wherein at least one operating value of an operating part of the harvester is determined based on plant characteristics of said crop.

[0002] The speed at which a harvester travels through a field to harvest the crop planted in front of it is one example of such an operating value for the harvester's drive motor or gear mechanism. The prior art discloses control devices that provide a value for the speed of travel as a function of plant characteristics in the form of crop canopy height or density.

[0003] DE 4431824 C1 discloses a method for operating a combine harvester that relies on a data register. The data register stores past area-specific yield data measured based on position coordinates. In this case, the crop yield is also a plant characteristic. Based on the current position coordinates of the combine harvester, data from the data register is used to calculate the setpoint for the combine harvester's travel speed. This method ultimately uses past data that is only somewhat applicable to the current harvesting situation.

[0004] DE102005000770B3 describes a method for controlling the operating parts of a combine harvester using georeferenced data, which are acquired and recorded during biomass development. This biomass data is used to create a reference map, which serves as a basis for controlling the combine harvester. In an exemplary embodiment, the biomass canopy is georeferenced and surveyed by a satellite-assisted sensing system during biomass development prior to harvesting. This biomass can also be considered a plant characteristic and is recorded in a biomass canopy map. However, this method does not detect all plant characteristics of the crop that affect the operating values ​​of the various operating parts of the harvester. Also, there may be a period between the last recording of the biomass canopy and the time of harvest, and as a result, events that occur before harvest, such as dry periods or heavy rains, which can have a significant effect on plant characteristics such as grain or straw moisture content, are not taken into account.

[0005] EP 2586286 B1 discloses a method for predictive survey of a crop to be gripped by a harvester, in which a sensor assembly arranged on the harvester emits contactless signals for at least one plant characteristic of the crop and uses them to derive statistical values. Furthermore, a measuring device detects the plant characteristic of the crop actually gripped by the harvester. An evaluation unit in this case automatically determines a relationship between the signals of the sensor assembly and statistical values ​​of the signals of the measuring device. These relationships are then taken into account in calculating the plant characteristic of the gripped crop. The signals of the sensor assembly are used to control the travel speed of the harvester, taking the determined relationship into account. As a result, the travel speed depends on the absolute measurement values ​​of the contactless sensors of the sensor device, which in practice does not always work accurately enough.

[0006] EP 2803256 A1 discloses a combine harvester in which a sensor is mounted on the roof of the cab, enabling contactless detection of the planted crop in front of the harvester. This is used to prepare data on the predicted mass throughput. Furthermore, the actual mass throughput is determined by a measuring device. The travel speed control device is designed so that the measured values ​​of the measuring device and the predicted mass throughput are compared with each other, and the result of this comparison is used as a feedback value for setting the travel speed of the harvester. However, the operating values ​​of certain operating parts of the combine harvester depend on plant characteristics, which are very difficult to detect using measuring means and are therefore often inaccurate. The problem with the sensor mounted on the roof of the cab is that it can only predict plant characteristics to a certain extent, which means that there is a great need for control of the operating values ​​of the combine harvester.

[0007] The invention is therefore based on the object of providing a method for operating a harvester for harvesting crops, in which the operating values ​​of at least one operating part of the harvester can be easily and satisfactorily determined.

[0008] The object on which the invention is based is achieved by the feature combination according to claim 1. Exemplary embodiments of the invention can be seen from the dependent claims. As already mentioned above, 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, which models the development of the plant characteristic over time and determines a predicted value or characteristic of the plant characteristic at harvest time.

[0010] At least one plant characteristic can be the biomass of the crop. Crop canopy height or density can also be mapped into the plant growth model as a plant characteristic whose development over time is modeled. A predicted harvest date for, for example, crop canopy height can then be determined from this modeling.

[0011] Further examples of plant characteristics that can be recorded in a plant growth model are yield data on straw and on grain in the case of cereals, grain moisture content and straw moisture content, corn cob diameter, initial growth height of the corn cob, corn stalk diameter, individual grain size (thousand kernel weight (Tausendkorngewicht)), shattering tendency (degree to which the ear breaks down), protein content in the case of cereals, and disease pressure (mycotoxin content), canopy height and position risk.

[0012] Preferably, the plant growth model records many different plant properties, and hereinafter when reference is made to a plant property or at least one plant property, this includes all other plant properties modeled by the plant growth model.

[0013] For example, for a corn crop, the plant characteristics of corn cob diameter, corn stalk diameter, and initial corn cob height are considered and modeled in the plant growth model. One or more plant characteristics can be used to derive one or more additional plant characteristics, such as crop yield data. Typically, such second plant characteristics are derived from the first plant characteristic. Correspondingly, the plant growth model allows the derived second plant characteristic to be expressed in terms of the temporal variation of the first plant characteristic, if available.

[0014] The harvester may be a combine harvester, a forage harvester or other machine by which standing or lying crops are gripped and collected from the field, possibly for passing on to further processing steps intact.

[0015] In the case of a combine harvester, a height-adjustable cutting unit may be used to cut grain crops, particularly cereals, which can then be fed into a threshing unit equipped with a rotating threshing drum and a receiving screen to separate the grain from the straw. The threshing intensity can be increased or decreased by adjusting the threshing drum speed and the threshing gap between the threshing drum and the receiving screen. A separating device may be placed after the threshing unit, where the remaining grain and ears that were not completely threshed are separated from the straw. A cleaning device may further separate the grain from non-grain components. The cleaning device preferably includes a sieve and a blower, which blows air onto the sieve. This airflow serves the purpose of blowing away lighter components, such as non-grain components, instead of passing through the sieve, and thus separating them from the grain that has passed through the sieve.

[0016] For example, if the straw moisture content is mapped by a plant growth model, according to the invention a predicted straw moisture content can be determined for the time of harvest. If a higher value is calculated by the plant growth model, a correspondingly higher threshing drum speed (operating value) can be provided to the threshing unit (actuating part). The air flow (here, air flow corresponds to a possible operating value of the blower as an operating part) can also be set correspondingly higher, since straw with a higher moisture content is heavier and can only be blown by a stronger air flow.

[0017] In the case of forage harvesters, the straw moisture content can be used as an influencing variable for setting the chopping length. For dry silage, a short chopping length is advantageous to allow for sufficient compaction.

[0018] If the plant growth model records the individual grain size (thousand kernel weight) as a plant characteristic, the threshing gap between the threshing drum and the receiving screen can be set based on this parameter. In the case of small grains, the intensity of the airflow from the threshing drum can be reduced, since otherwise an excessive proportion of the grains would be blown away in the cleaning device along with non-grain components. If values ​​for shatterability (the degree to which the ear breaks down) are available at harvest, in the case of brittle ears, the threshing drum speed can be set to a rather low value, thus weakening the cleaning device downstream of the threshing unit, since a lower threshing drum speed generally results in a lower proportion of short stems in the cleaning device.

[0019] The adjustable clamping plate spacing also corresponds to an operating value determined by the method according to the present invention based on the plant characteristics of the crop. For example, if the plant growth model specifies a value for the corn stalk diameter, the clamping plate spacing can be set accordingly. A well-set clamping plate spacing ensures clean feeding and reduces the risk of clogging. Alternatively or additionally, the method may also provide the corn cob diameter as an influencing variable for the clamping plate spacing.

[0020] The initial growth height of the corn cob, which can also be modeled by the plant growth model, can be used as an influencing variable for the height of the cutting unit. The higher the cutting unit is transported, the lower the risk of damage and the lower the power requirements for the cutting unit. The height of the cutting unit can also depend on the height of the crop canopy or the storage risk calculated by the plant growth model.

[0021] In the case of corn, biomass can serve as an influencing variable in determining the preferred or optimal running speed of the forage harvester. In the case of cereals, straw yield data can influence the running speed of the combine harvester. In the case of cereals, grain yield data can be used to set the airflow speed in the cleaning device. If the results of the plant growth model show very low values ​​for the grain moisture content (very dry corn), corresponding settings of the actuators can be made accordingly to reduce the number of broken grains.

[0022] A further example is yield formation in the cob of a corn plant. If there is short-term drought stress during the flowering stage, not all early kernels are fertilized. These cobs contain significantly fewer kernels. This relationship can be reproduced in plant simulation models, but not by means of remote sensing or environmental detection sensors on the harvester.

[0023] The predicted values ​​or characteristics of plant properties in a field can be determined in a georeferenced manner. This means that the predicted values ​​or characteristics of plant properties can be assigned to corresponding location coordinates at a certain spatial resolution. The result of such assignment can be a map representing the values ​​of the plant properties at a higher spatial resolution, such as 100 x 100 m, 50 x 50 m, or even 5 x 5 m. Absolute or even relative values ​​of one or more plant properties can be stored for each area element. Each area element may be assigned only a quantitative class for the plant property, such as "1, 2, ... 5," a maximum of 5, or "very small, small, medium, large, and very large." This map or corresponding data record can be provided to a harvester control device, which then sets the individual operating units so that their operating values ​​result in optimal harvesting results. Alternatively, the operating values ​​can only be suggested to the harvester driver, who can then set the individual operating values ​​of the operating units himself after comparing them with values ​​from his personal experience.

[0024] The plant growth model determines a predicted value or predicted characteristic of the plant property for the time of harvest, which may be, for example, the week or day of harvest. However, to enable accurate identification of the value or characteristic of the plant property that changes over the course of a day, this period may be only a few hours, for example, less than 3 hours. Thus, the time of harvest may be understood as an externally supported input variable. In another exemplary embodiment, the preferred or optimal time is calculated by the plant growth model.

[0025] In one exemplary embodiment, meteorological data that can affect the characteristic values ​​of plant properties are used. For example, temperature, atmospheric humidity, sunshine hours and / or precipitation can be considered, preferably with high spatial resolution. On the one hand, these variables have a decisive influence on crop growth and, as a result, affect many plant properties. On the other hand, these variables may also have a direct effect on some plant properties, such as straw moisture content.

[0026] Soil data that influences crop growth may also be used in the method according to the invention, for example the water content of the soil 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 can then model the amount of water that the crop extracts from the soil. The soil water content is preferably again represented with high spatial resolution for individual area elements and can again be calculated taking meteorological data into account.

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

[0028] In addition, soil moisture can be measured by remote sensing. Ground moisture can then be taken into account in the calculation of soil moisture content. In this case, the plant growth model only uses data on ground moisture indirectly, specifically by modeling the soil moisture content. A measuring device can be attached to the harvester, and a predicted value or predicted characteristic of the plant characteristic is calculated based on the signal of the measuring device. The measuring device can include a non-contact sensor and / or a sensor for the actual harvested crop. For example, a non-contact sensor can be attached to the roof of the harvester's cab and designed to measure the height of the crop canopy. The measurement results can be used to confirm and possibly adapt the canopy height calculated by the plant growth model. If the canopy height calculated by the plant growth model is found to deviate from the measured canopy height, at least this plant characteristic can be corrected accordingly based on this deviation. Such corrections can also affect other plant characteristics, which can then be adapted as well. The corrections can be made once at the start of the harvesting operation or else continuously during the harvest, i.e. as the harvester travels through the field and collects the crop.

[0029] Corrections may also be made by sensors for the actual harvested crop. For example, in this way, the weight of the harvested grain can be compared with the weight that would have been harvested based on the plant growth model, taking into account the specific grain losses of the harvester. The corresponding plant characteristics can then be readjusted. This calibration may also be made in a georeferenced manner, where the georeferenced yield data of the sensors for the actual harvested crop is 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 properties, in this way certain assumptions in the modeling of plant properties can be verified and more accurately formulated.

[0031] A field can be divided into plots, and then a distinction can be made between a first group of plots and at least one second group of plots that differ from each other in terms of plant characteristics. For example, a threshold value for the protein content of the crop can be defined, so that all plots below the threshold are assigned to the first group, and all plots characterized by a protein content above the threshold are assigned to the second group. Depending on the spatial resolution, these plots can be individual area elements, but they can also be composed of multiple area elements. In an exemplary embodiment, the first group of plots are harvested first, followed by the second group of plots. In this way, selective harvesting characterized by different protein contents can be performed.

[0032] Another possibility is that the first crop container is filled when harvesting is performed in one of the first group of plots, and the second crop container is filled when harvesting is performed in one of the second group of plots. In this case, the harvester comprises a separation device that fills the first or second crop container depending on the protein content of the plant characteristic. In controlling the separation device, a certain time delay caused by the travel speed of the harvester and the time required to transport the crop from an area element of the field to the separation device of the harvester can be taken into account.

[0033] Another application for the selective harvesting mentioned above is mycotoxin content, which can also be the result of calculations of a plant growth model. Again, selective harvesting can be done by harvesting plots at different times (first, plots with a somewhat lower mycotoxin content, then plots with a somewhat higher mycotoxin content) or by operating a separation device and feeding the crop into either the first or second crop container.

Claims

1. 1. A method of operating a harvester to harvest a crop in a field, comprising: Enter the harvest time, Mapping plant characteristics in a plant growth model, the development of the plant characteristics over time being modeled 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 the crop; 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. A method comprising:

2. 2. The method of claim 1, wherein the plant characteristic is mycotoxin content, protein content, straw moisture content, individual particle size (thousand kernel weight) or shattering habit.

3. 3. The method of claim 1 or 2, wherein crop canopy height or density is mapped as a plant property into the plant growth model.

4. 4. The method according to any one of claims 1 to 3, wherein the plant characteristics mapped to the plant growth model are yield data on straw in case of cereals, yield data on kernel in case of cereals, kernel moisture content, straw moisture content, corn cob diameter, corn cob height, corn stalk diameter, individual grain size, shattering habit, protein content in case of cereals and / or canopy height.

5. The method according to any one of claims 1 to 4, wherein the operating values ​​of the operating parts of the harvester are the height of the cutting unit of the combine harvester, or the threshing drum speed of the threshing unit of the combine harvester and the threshing gap between the threshing drum and the receiving net.

6. 5. The method according to claim 4, wherein the height of a cutting unit is adjustable as an operating value of an operating part of the harvester, and the height of the corn cob is used as an influencing variable for the height of the cutting unit.

7. The method according to any one of the preceding claims, 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.

8. 8. The method according to claim 7, wherein said corrections are made once at the start of a harvesting operation, or else continuously during harvesting, i.e. while the harvester is travelling through the field and collecting the crop.

9. The method according to any one of claims 1 to 8, wherein historical values ​​from previous growing periods or previous harvests are used in modelling the plant properties.

10. The method according to any one of claims 1 to 9, wherein the predicted values ​​or characteristics of the plant properties are determined in a georeferenced manner.

11. The method of claim 10 , wherein the predicted values ​​or characteristics of the plant properties are assigned to corresponding location coordinates at a particular spatial resolution.

12. 12. The method according to claim 10 or 11, wherein a map or data record containing plant characteristics for each area element of the field is provided to a control device of the harvester, which control device sets the individual actuators.

13. The method according to any one of claims 10 to 12, 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.

14. 14. The method of claim 13, wherein the first group of plots are harvested first, then the second group of plots.

15. 14. The method of claim 13, 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.