Patent Description:
Historically, producers of forage crop material for animals have grown fields of single, mono-culture crop material, such as but not limited to, alfalfa. More recently, producers have begun planting fields of mixed or multiple-culture crop materials, such as but not limited to combinations of alfalfa and grass. These mixed stands of multiple crop materials may provide advantages over mono-culture crop materials, such as but not limited to, better fiber digestion by the animal, reduced fertilizer requirements, and less strain on the soil.

While stands of mixed crop materials may provide benefits to some producers, different animals may require different feed rations of the different crop materials. Additionally, some crop materials or weed species may be poisonous to some animals. Accordingly, it is important for a producer to know the content of the feed material so that the feed ration may be optimized for the animal, and any harmful feed materials may be avoided.

Often, the crop material is harvested and formed into a bale. While a producer may be able to visually identify different crop material species while the crop material is standing in a field, it is difficult to identify the different species of crop material once formed into a bale, and even more difficult to determine the different quantities of the different crop material species when formed into a bale. <CIT> discloses a biomass harvesting system comprising an active tracking system to identify discrete units of accumulated biomass. <CIT> discloses a method for dividing a field into zones with similar crop attributes. <CIT> discloses a system for tracking a harvested agricultural product unit. <CIT> discloses a bale retrieval system to identify bales included in images captured by the imaging device.

A method of harvesting crop material in a field is provided. The method includes capturing an image of each of a plurality of regions of the field with an image sensor. A region identifier is assigned to each of the plurality of regions with a computing device. The respective image of each of the plurality of regions is analyzed with the computing device to determine data related to constituent species of the crop material located within each of the plurality of regions. The data related to constituent species for each respective one of the plurality of regions is associated with the region identifier assigned to the respective one of the plurality of regions with the computing device, and saved in a memory of the computing device. The crop material in the field is then harvested with a harvester implement and formed into a bale with a baler implement. The harvested crop material formed into the bale is gathered from a subset of the plurality of regions. A bale identifier is attached to the bale with the baler implement. The computing device may then identify which of the plurality of regions is included in the subset of the plurality of regions, and associate the region identifier of each of the plurality of regions included in the subset of the plurality of regions with the bale identifier, such that the data related to constituent species of the crop material included in the bale is associated with the bale and may be obtained by querying the computing device.

In one aspect of the invention the method of harvesting the crop material includes saving the region identifier for each of the plurality of regions, the data related to constituent species for each respective one of the plurality of regions, and the bale identifier associated with the region identifier of each of the plurality of regions included in the subset of the plurality of regions in a memory. The memory may be part of the computing device and located on the harvester implement and/or the baler implement, or may be remotely located at a centralized or cloud based storage facility.

In one aspect of the invention, the method of harvesting the crop material includes segmenting the field into the plurality of regions with the computing device. The field may be segmented into the different regions in any manner. In one implementation, the different regions are sized and arranged to provide discrete portions of the bale, such as a single flake of a square bale. In other implementations, the different regions may be sized and arranged to provide discrete portions of a round bale. Additionally, the field may be segmented into generally rectangular regions aligned along a harvest path.

In one aspect of the invention, the method of harvesting the crop material includes defining a geographic boundary of each of the plurality of regions. The geographic boundary of each of the plurality of regions may be defined in a suitable manner, such as by a latitude and a longitude for reach respective region, an absolute coordinate of each respective region, etc. The geographic boundary may include a coordinate for a centralized location, and dimension descriptions describing the regions relative to the centralized location. The geographic boundary of each respective region may be defined and saved in the memory of the computing device so that the location of the crop material from each respective region may be tracked.

In one aspect of the invention, the method of harvesting the crop material may include tracking a geographic location of the crop material within each respective one of the plurality of regions after harvesting the crop material. For example, if the crop material is moved after harvesting and before being formed into the bale, the crop material may be moved, e.g., raked or combined with other crop material. By knowing the geographic boundary of each respective region, the movement of the crop material may be tracked so that the location of the crop material may be known.

In one aspect of the invention, the method of harvesting the crop material includes the crop material harvested from at least two different regions of the field may be combined into a windrow. If the crop material from two different regions is combined, then the computing device may track the movement and location of the crop material from each.

In one aspect of the invention, the method of harvesting the crop material includes communicating the image of each of the plurality of regions to the computing device. The computing device may be located remote from the image sensor. The computing device is configured to receive the images from the image sensor for each of the respective regions of the field.

In one aspect of the invention, the method of harvesting the crop material includes analyzing the respective image of each of the plurality of regions to determine data related to constituent species of the crop material located within each of the plurality of regions includes identifying at least one crop species and a percentage of the at least one crop species included in a total quantity of the crop material located within the respective region. Additionally, the data related to the constituent species of the crop material may include, but is not limited to, type and percentage of weeds, stage of growth of the different crop species, crop quality metrics such as but not limited to non-digestible fiber content, acid detergent fiber content, neutral detergent fiber content, crude protein content, etc..

In one implementation of the invention, the image sensor is mounted on the harvester implement and positioned to capture images immediately ahead of the harvester implement relative to a direction of travel while harvesting. The plurality of regions may be defined as an area immediately ahead of the harvester implement and the respective image captured as the harvester implement moves through the field. As such, the step of capturing the image of each of the plurality of regions of the field is further defined as capturing the image of each of the plurality of regions of the field as the harvester implement harvests the crop material.

In one implementation of the disclosure, not part of the current invention, the image sensor is disposed on an aerial device. Capturing the image of each of the plurality of regions of the field includes maneuvering the aerial device over the field prior to harvesting the crop material in the field. The field may be segmented into the plurality of regions and their respective boundaries defined and saved into a memory of the aerial device. The aerial device may then be flown over the field and capture the respective images of the regions based on the location of the aerial device.

In one aspect of the invention, the method of harvesting the crop material includes associating a respective geographic location of each respective one of the plurality of regions of the field with the image of each respective one of the plurality of regions of the field. The image and the associated region may then be saved in the memory of the computing device.

A harvesting system for harvesting crop material in a field is also provided. The harvesting system includes an image sensor operable to capture a respective image of each of a plurality of regions of the field, harvester implement operable to harvest the crop material within the field, and a baler implement operable to gather the harvested crop material and form the crop material into a bale. The baler implement is further operable to attach a bale identifier to each respective bale during formation of the bale. A computing device includes a processor and a memory having a harvesting algorithm stored thereon. The processor is operable to execute the harvesting algorithm to receive an image of each of the plurality of regions of the field from the image sensor, and assign a region identifier to each of the plurality of regions. The computing device may then analyze the respective image of each of the plurality of regions to determine data related to constituent species of the crop material located within each of the plurality of regions, and associate the data related to constituent species for each respective one of the plurality of regions with the region identifier assigned to the respective one of the plurality of regions. The harvester implement may be controlled to harvest the crop material in the field, and the baler implement may be controlled to form the harvested crop material gathered from a subset of the plurality of regions into a bale, and attach the bale identifier to the bale. The computing device may then identify which of the plurality of regions is included in the subset of the plurality of regions, and associate the region identifier of each of the plurality of regions included in the subset of the plurality of regions with the bale identifier such that the data related to constituent species of the crop material included in the bale is associated with the bale and may be obtained by querying the computing device.

In one aspect of the harvesting system, the processor is operable to execute the harvesting algorithm to segment the field into the plurality of regions and determine a geographic boundary of each of the plurality of regions. In one aspect of the harvesting system, the processor is operable to execute the harvesting algorithm to associate a respective geographic location of each respective one of the plurality of regions of the field with the image of each respective one of the plurality of regions of the field.

In one aspect of the harvesting system, the processor is operable to execute the harvesting algorithm to track a geographic location of the crop material within each respective one of the plurality of regions after the crop material has been harvested.

The harvesting system and the method of harvesting the crop material described above identify and track the different constituent crop species in the field. The image of each respective region may be analyzed to determine or identify the different crop species, their respective percentages of the crop material in the region, as well as other data related to the crop materials. The data related to the crop materials from a respective region is associated with the region identifier of that respective region and saved in the memory of the computing device. By doing so, the crop data for each specific region is known. As the crop material is handled in the future, the location of the crop material from each specific region may be tracked. For example, if alfalfa is moved or combined with crop material from another region, the computing device may track the location of the crop material. The baler implement may also access this data so that the baler implement knows the data related to the crop materials being gathered and formed into a specific bale. The computing device may then assign or associate the bale identifier with the region identifier, thereby linking the data related to the crop material to the bale identifier. An end user may access the data related to the constituent crop materials included in a specific bale at a future time by referencing the bale identifier, thereby learning the content of that specific bale and enabling the end user to properly establish a feed ration for their specific purpose.

Referring to the Figures, wherein like numerals indicate like parts throughout the several views, a harvesting system is generally shown at <NUM>. In the example implementation shown in the Figures and described herein, the harvesting system <NUM> includes an image sensor <NUM>, a harvester implement <NUM>, and a baler implement <NUM>. The harvesting system <NUM> is configured for identifying constituent crop species of standing crop material <NUM> in a field <NUM>, and tracking the identified constituent crop species through the harvesting and baling process, such that an end user may learn or obtain the crop species, and potentially other data related to the cop species, included in each bale <NUM> of crop material <NUM> harvested from the field <NUM>.

The image sensor <NUM> is operable to capture an image of a plurality of regions <NUM> of the field <NUM>. In one implementation, the image sensor <NUM> captures a respective image for each respective region <NUM> of the field <NUM>. In another implementation, the image sensor <NUM> captures an image including more than one region <NUM> of the field <NUM>.

The image sensor <NUM> may include any device capable of capturing an image and communicating the image to a computing device <NUM>. The image sensor <NUM> may include, but is not limited to, a camera, a video camera, etc. The image sensor <NUM> may capture the image in a suitable light spectrum. In one implementation, the image sensor <NUM> is operable to capture the image in a Near InfraRed (NIR) light spectrum as understood by those skilled in the art. The specific type, components, function, etc. of the image sensor <NUM> are understood by those skilled in the art and are therefore not described in greater detail herein.

In one implementation, as shown in <FIG>, the image sensor <NUM> is mounted on the harvester implement <NUM>. The image sensor <NUM> may be positioned to capture an image in front of the harvester implement <NUM> relative to a direction of travel <NUM> of the harvester implement <NUM> when harvesting the crop material <NUM> from the field <NUM>. As noted above, the field <NUM> may be segmented into discrete regions <NUM> for species identification and tracking. For example, the field <NUM> may be segmented into regions <NUM> corresponding to a width approximately equal to a width of the harvester implement <NUM>. As such, the image sensor <NUM> may be configured to capture the image of each of the regions <NUM> of the field <NUM> as the harvester implement <NUM> harvests the crop material <NUM> from the field <NUM>. In this manner, the regions <NUM> of the field <NUM> may be defined simultaneously while capturing the respective images. In other words, the image sensor <NUM> may capture an image ahead of the harvester implement <NUM> while harvesting, and then define the boundary and location of the region <NUM> of the field <NUM> from which that respective image was captured, thereby defining that region <NUM> of the field <NUM>. This process may be followed for the entire field <NUM>.

In another implementation, the image sensor <NUM> may be disposed on an aerial device <NUM>. The aerial device <NUM> may include an unmanned aerial device <NUM>, such as but not limited to an aerial drone or satellite. In other implementations, the aerial device <NUM> may include a manned aerial device <NUM>, such as but not limited to a plane or a helicopter. The aerial device <NUM> may be maneuvered over the field <NUM> prior to harvesting the crop material <NUM> in the field <NUM> in order to capture the image for each respective region <NUM> of the field <NUM>. In this implementation, the boundary and location of each of the plurality of regions <NUM> may be defined prior to flying the aerial device <NUM> over the field <NUM>. The aerial device <NUM> may then capture an image of each predefined region <NUM> of the field <NUM>. It should be appreciated that the harvesting system <NUM> may include multiple image sensors <NUM>. For example, the harvesting system <NUM> may include both an image sensor <NUM> mounted on the harvester implement <NUM>, and another image sensor <NUM> mounted on the aerial device <NUM>.

The harvester implement <NUM> is operable to harvest the crop material <NUM> within the field <NUM>. The crop material may include, but is not limited to, grasses, alfalfa, small grains, corn, other forage crops suitable for animal feed, etc. The type, configuration, operation, etc. of the harvester implement <NUM> is dependent upon the specific type of crop being harvested. The harvester implement <NUM> may include, but is not limited to, a self-propelled windrower, a tractor pulling and/or pushing a mower or a mower conditioner, a forage harvester, a combine, etc. In one implementation, the harvester implement <NUM> cuts the standing crop material in the field <NUM> and moves the cut crop material into a windrow <NUM>. The specific type and/or configuration of the harvester implement <NUM> for the specific crop material to be harvested are known to those skilled in the art, are not pertinent to the teachings of this disclosure other than as described herein, and are therefore not described in greater detail.

The baler implement <NUM> is operable to gather the harvested crop material <NUM> after the crop material has been cut by the harvester implement <NUM> and form the crop material into a bale <NUM>. In some implementations, the baler implement <NUM> may be configured to form the bale <NUM> to include a parallelepiped shape, such as but not limited to, a large square baler or a small square baler. In other implementations, the baler implement <NUM> may be configured to form the bale <NUM> to include a cylindrical shape, such as but not limited to a round baler. The type and configuration of the baler implement <NUM> are known to those skilled in the art, are not pertinent to the teachings of this disclosure other than as described herein, and are therefore not described in greater detail.

The baler implement <NUM> may include a bale identification system that is operable to attach a bale identifier <NUM> to each respective bale <NUM> during formation of the bale <NUM>. The bale identifier <NUM> may include, but is not limited to, a Radio Frequency Identification (RFID) device, a label, etc. The bale identifier <NUM> may include any device capable of being associated with and identifying a respective bale <NUM>. The bale identifier <NUM> may be attached to the bale <NUM> during formation with the baler implement <NUM>, or subsequent to formation by some other implement.

In one implementation, the bale identifier <NUM> includes a RFID tag attached to the bale <NUM> during formation. The RFID tag includes a unique identification code that may be read by a RFID reader. As understood by those skilled in the art, the RFID reader emits an interrogation signal, to which the RFID tag responds by emitting a signal including the identification code. The identification code may be associated with a specific bale <NUM>, and reference to identify that specific bale <NUM> and any properties or characteristics associated with that specific bale <NUM>. The configuration and operation of RFID reader/tag systems are known to those skilled in the art, are not pertinent to the teachings of this disclosure other than as described herein and are therefore not described in greater detail.

As noted above, the image sensor <NUM> is in communication with the computing device <NUM>. The computing device <NUM> is operable to receive image signals from the image sensor <NUM>. While the computing device <NUM> is generally described herein as a singular device, it should be appreciated that the computing device <NUM> may include multiple devices linked together to share and/or communicate information therebetween. Furthermore, it should be appreciated that the computing device <NUM> may be located on the harvester implement <NUM>, the baler implement <NUM>, located remotely from the harvester implement <NUM> and baler implement <NUM>, or be located in a combination of the harvester implement <NUM>, the baler implement <NUM>, and a remote location.

The computing device <NUM> may alternatively be referred to as a computer, a controller, a control unit, a control module, a module, etc. The computing device <NUM> includes a processor <NUM>, a memory <NUM>, and all software, hardware, algorithms, connections, sensors, etc., necessary to identify and track data related to the constituent crop species in the field <NUM>. As such, a method may be embodied as a program or algorithm operable on the computing device <NUM>. It should be appreciated that the computing device <NUM> may include any device capable of analyzing data from various sensors, comparing data, making decisions, and executing the required tasks.

As used herein, "computing device <NUM>" is intended to be used consistent with how the term is used by a person of skill in the art, and refers to a computing component with processing, memory, and communication capabilities, which is utilized to execute instructions (i.e., stored on the memory or received via the communication capabilities) to control or communicate with one or more other components. In certain embodiments, the computing device <NUM> may be configured to receive input signals in various formats (e.g., hydraulic signals, voltage signals, current signals, CAN messages, optical signals, radio signals), and to output command or communication signals in various formats (e.g., hydraulic signals, voltage signals, current signals, CAN messages, optical signals, radio signals).

The computing device <NUM> may be in communication with other components on the baler implement <NUM> and/or the image sensor <NUM>, such as hydraulic components, electrical components, and operator inputs within an operator station of an associated work vehicle. The computing device <NUM> may be electrically connected to these other components by a wiring harness such that messages, commands, and electrical power may be transmitted between the computing device <NUM> and the other components. Although the computing device <NUM> is referenced in the singular, in alternative embodiments the configuration and functionality described herein can be split across multiple devices using techniques known to a person of ordinary skill in the art.

The computing device <NUM> may be embodied as one or multiple digital computers or host machines each having one or more processors, read only memory (ROM), random access memory (RAM), electrically-programmable read only memory (EPROM), optical drives, magnetic drives, etc., a high-speed clock, analog-to-digital (A/D) circuitry, digital-to-analog (D/A) circuitry, and any required input/output (I/O) circuitry, I/O devices, and communication interfaces, as well as signal conditioning and buffer electronics.

The computer-readable memory <NUM> may include any non-transitory/tangible medium which participates in providing data or computer-readable instructions. The memory <NUM> may be non-volatile or volatile. Non-volatile media may include, for example, optical or magnetic disks and other persistent memory. Example volatile media may include dynamic random access memory (DRAM), which may constitute a main memory. Other examples of embodiments for memory <NUM> include a floppy, flexible disk, or hard disk, magnetic tape or other magnetic medium, a CD-ROM, DVD, and/or any other optical medium, as well as other possible memory devices such as flash memory.

The computing device <NUM> includes the tangible, non-transitory memory <NUM> on which are recorded computer-executable instructions, including a harvesting algorithm <NUM>. The processor <NUM> of the computing device <NUM> is configured for executing the harvesting algorithm <NUM>. The harvesting algorithm <NUM> implements a method of harvesting crop material in the field <NUM>, including identifying and tracking data related to the constituent crop species of the crop material, described in detail below.

Referring also to <FIG>, the method includes segmenting the field <NUM> into the plurality of regions <NUM>. The step of segmenting the field <NUM> into the regions <NUM> is generally indicated by box <NUM> in <FIG>. Each region <NUM> includes a discrete area of the field <NUM> in which the different crop species of the crop material may be identified and tracked. As described above, each region <NUM> may be segmented and defined prior to harvesting the crop material with the harvester implement <NUM>. Segmentation of the field <NUM> into the respective regions <NUM> may occur simultaneously while capturing images of the field <NUM>, or may occur prior to capturing images of the field <NUM>.

The computing device <NUM> may assign a region identifier <NUM> to each of the regions <NUM>. The step of assigning the respective region identifier <NUM> to the respective region <NUM> is generally indicated by box <NUM> in <FIG>. The region identifier <NUM> for each respective region <NUM> may include, but is not limited to, an alpha-numeric descriptor that is unique to that region <NUM>. In other words, each specific region <NUM> includes it's own unique region identifier <NUM>. The region identifier <NUM> may be considered a name used to track that specific region <NUM>.

The computing device <NUM> may determine and/or define a geographic boundary <NUM> of each of the regions <NUM>. The step of determining the geographic boundary <NUM> of each of the regions <NUM> is generally indicated by box <NUM> in <FIG>. The geographic boundary <NUM> may de defined in a suitable manner enabling or describing the geographic location of the region <NUM> within the field <NUM>. The geographic boundary <NUM> may include, but is not limited to, coordinates, distances, bearings, or other descriptors describing the geographic boundary <NUM> of each region <NUM>. The geographic boundary <NUM> of each region <NUM> may then be saved in the memory <NUM> of the computing device <NUM>. The geographic boundary <NUM> of each region <NUM> may be defined in a suitable manner understood by those skilled in the art. For example, a Global Positioning Satellite (GPS) system, global coordinates, lidar, radar, etc. may be used as understood by those skilled in the art to identify the geographic boundary <NUM> of each region <NUM>.

An image of each of a plurality of regions <NUM> of the field <NUM> may then be captured or sensed and communicated to the computing device <NUM>. The step of capturing the image of the regions is generally indicated by box <NUM> in <FIG>. The image may include a single image including all of the respective regions <NUM> of the field <NUM>, or may include multiple images. In one implementation, a respective image is captured for each respective region <NUM> of the field <NUM>. In another implementation, an image is captured including multiple regions <NUM> of the field <NUM>. The image may be captured to show the different crop species in enough detail for the computing device <NUM> to identify the different crop species, and potentially other data related to the different constituent crop species of the crop material. The resolution of the image and the size of each of the regions <NUM> may be coordinated and/or dependent upon the other. For example, the size or area of each region <NUM> may be dependent upon the resolution of the image sensor <NUM>.

The computing device <NUM> is operable to receive the image of each of the regions <NUM> of the field <NUM> from the image sensor <NUM>. The computing device <NUM> may be connected to the image sensor <NUM> through either a wired connection and/or a wireless connection as is understood by those skilled in the art. The computing device <NUM> may associate each image with a respective one of the regions <NUM>, the region identifier <NUM>, and/or the respective geographic location or boundary of that region <NUM> of the field <NUM>, and save the same in the memory <NUM>.

The computing device <NUM> may then analyze the respective image of each of the plurality of regions <NUM> to determine data related to constituent species of the crop material located within each of the plurality of regions <NUM>. The step of analyzing the images to determine the data related to the crop material is generally indicated by box <NUM> in <FIG>. As used herein, the constituent species of the crop material include the different species of plants existing in the field <NUM> and/or region <NUM>. For example, in a field <NUM> planted with alfalfa and grass, the constituent crop species may include alfalfa, grass, and one or more other plant species. The other plant species may include, for example, one or more weed species. The data related to the constituent species may include a list of the different plant species, a percentage of an entire quantity of each different plant species, a stage of growth of each plant species, a crop quality and/or nutritional metric, etc. The computing device <NUM> determines the data related to the constituent species for each individual region <NUM> of the field <NUM>, associates that data with the respective region <NUM> and/or region identifier <NUM> assigned to the respective region <NUM>, and may save all of the same in the memory <NUM>.

The crop material in the field <NUM> may then be harvested with the harvester implement <NUM>. As noted above, the operation of the harvester implement <NUM> depends upon the specific crop material being harvested. For example, if the crop material is hay and forage crop, then the harvester implement <NUM> may include a self-propelled windrower, and harvesting the crop material may include cutting the crop material in the field <NUM> and forming the crop material into a windrow <NUM>. It should be appreciated that the process of harvesting the crop material may differ from the example implementation described herein.

The computing device <NUM> may track a geographic location of the crop material within each respective one of the regions <NUM> after the crop material has been harvested. For example, if the harvesting operation includes multiple processes that may cause the crop material to move within its respective region <NUM>, or to combine crop material from at least two different and/or adjoining regions <NUM>, then the computing device <NUM> may track the location of the crop material from each region <NUM>. For example, if the crop material includes hay and forage material, and the harvesting process includes cutting and forming the crop material into a windrow <NUM>, a subsequent harvesting process may include raking adjacent windrows <NUM> together and/or moving one windrow <NUM>. Because the computing device <NUM> knows the location of each region <NUM>, the computing device <NUM> may track the location of crop material within that region <NUM> based on any subsequent harvesting processes. As such, the computing device <NUM> may know the location of the crop material from the image of respective region <NUM> and track the location of that crop material during subsequent harvesting processes to maintain knowledge of the location of that crop material.

The harvested crop material from a subset <NUM> of the plurality of regions <NUM> may then be gathered and formed into a bale <NUM> with the baler implement <NUM>. Forming the harvested crop material <NUM> into the bale <NUM> is generally indicated by box <NUM> in <FIG>. The subset <NUM> of the regions <NUM> may include any number of the regions <NUM>, e.g., <NUM>, <NUM>, <NUM>, <NUM>,. , n regions <NUM>. For example, the subset <NUM> of the regions <NUM> may include a single region <NUM>, in which case the bale <NUM> would be formed from the crop material gathered from that single region <NUM>. In another example, the subset <NUM> of the regions <NUM> may include four different regions <NUM>, in which case the bale <NUM> would be formed from the crop material gathered from those four different regions <NUM>.

The computing device <NUM> may determine and/or identify which of the regions <NUM> is included in the subset <NUM> of the regions <NUM> in a suitable manner. The step of determining which regions <NUM> are included in the bale <NUM> is generally indicated by box <NUM> in <FIG>. For example, the computing device <NUM> may use the GPS system to track a location of the baler implement <NUM> and knowing the location of the baler implement <NUM>, determine which regions <NUM> are being gathered for that specific bale <NUM> based on the geographic boundary <NUM> of the regions <NUM> saved in the memory <NUM> and associated with the different regions <NUM> and region identifier <NUM>. It should be appreciated that the computing device <NUM> may determine which regions <NUM> are included in the subset <NUM> of regions <NUM> for each bale <NUM> in some other manner not described herein.

The bale identifier <NUM> may be attached to the bale <NUM>. The step of attaching the bale identifier <NUM> to the bale <NUM> is generally indicated by box <NUM> in <FIG>. In one implementation, the bale identifier <NUM> may be attached by the bale <NUM> by the baler implement <NUM> during formation of the bale <NUM>. In another implementation, the bale identifier <NUM> may be attached to the bale <NUM> subsequent to formation of the bale <NUM>, by some other device, implement, and/or process. As noted above, the bale identifier <NUM> for each respective bale <NUM> includes an identification code that is unique to that respective bale <NUM>.

The computing device <NUM> may then associate the region identifier <NUM> of each of the regions <NUM> included in the subset <NUM> of the regions <NUM> gathered to form the bale <NUM> with the bale identifier <NUM>. The step of associating the region identifier <NUM> for each region <NUM> included in the bale <NUM> is generally indicated by box <NUM> in <FIG>. In so doing, the data related to the constituent species of the crop material included in the that respective bale <NUM> is associated with that respective bale <NUM> and may be obtained by querying the computing device <NUM>. In other words, because the data related to the constituent crop species is known for the crop material from each respective region <NUM> and associated with that respective region identifier <NUM>, by associating the region identifier <NUM> for each region <NUM> gathered to form a respective bale <NUM> with the bale identifier <NUM> for that respective bale <NUM>, the data related to the constituent species of the crop material is thereby associated with the bale identifier <NUM>.

The computing device <NUM> may then save the region identifier <NUM> for each region <NUM> gathered to form the respective vale and the associated bale identifier <NUM> in the memory <NUM>. The computing device <NUM> may communicate this information to a remote memory <NUM>, e.g., a network server and/or a Cloud memory <NUM> device. An end user may then query the computing device <NUM> with an identification code, e.g., by scanning the bale identifier <NUM> of a bale <NUM>. The step of obtaining the data related to the bale is generally indicated b box <NUM> in <FIG>. The computing device <NUM> may then report back the data related to the constituent plant species that are included in that specific bale <NUM>. This enables the end user to determine how best to use the crop material included in that bale <NUM>, such as by combining the crop material with other feed sources and/or feeding that specific bale <NUM> to only one type of animal. For example, if the data related to the constituent plant species indicates that a specific bale <NUM> includes horse nettle, which may be poisonous to horses, then the end user may then know that it is unsafe to feed this particular bale <NUM> to horses.

Claim 1:
A method of harvesting crop material in a field (<NUM>), the method comprising:
capturing an image of each of a plurality of regions (<NUM>) of the field (<NUM>) with an image sensor (<NUM>);
assigning a region identifier (<NUM>) to each of the plurality of regions (<NUM>) with a computing device (<NUM>);
analyzing the respective image of each of the plurality of regions (<NUM>), with the computing device (<NUM>), to determine data related to constituent species of the crop material located within each of the plurality of regions (<NUM>);
associating the data related to constituent species for each respective one of the plurality of regions (<NUM>) with the region identifier (<NUM>) assigned to the respective one of the plurality of regions (<NUM>), with the computing device (<NUM>);
harvesting the crop material in the field (<NUM>) with a harvester implement (<NUM>);
forming the harvested crop material gathered from a subset (<NUM>) of the plurality of regions (<NUM>) into a bale with a baler implement (<NUM>);
attaching a bale identifier (<NUM>) to the bale with the baler implement (<NUM>);
identifying which of the plurality of regions (<NUM>) is included in the subset (<NUM>) of the plurality of regions (<NUM>) with the computing device (<NUM>); and
associating the region identifier (<NUM>) of each of the plurality of regions (<NUM>) included in the subset (<NUM>) of the plurality of regions (<NUM>) with the bale identifier (<NUM>), with the computing device (<NUM>), such that the data related to constituent species of the crop material included in the bale is associated with the bale and may be obtained by querying the computing device (<NUM>).