Patent Publication Number: US-2022217905-A1

Title: Processor roll gap control using crop moisture content

Description:
TECHNICAL FIELD 
     The disclosure generally relates to a harvester implement having a crop processor for processing crop material, and a method of controlling the harvester implement. 
     BACKGROUND 
     A harvester implement gathers crop material from a field and directs the crop material through a pair of opposing feed rollers. The crop material is fed between the opposing feed rollers, which move the crop material along a processing flow path. The feed rollers counter-rotate relative to each other to move the crop material in a direction of crop processing, which is generally rearward relative to a direction of travel of the harvester implement. Crop processing operations may include one or more post collection operations that improves the digestibility of the crop material, thereby increasing nutrient value of the crop material when consumed by animals. 
     The crop processing operations may include, but are not limited to, cutting the crop material to a length and/or fracturing/cracking kernels of the crop material. For example, the crop material may move along the flow path through a cutter head. The cutter head includes a rotating drum with a plurality of knives disposed on the periphery of the drum. The cutter head cooperates with a shear bar to cut stem portions of the crop material into small pieces. Following the cutter head, the crop material may flow through a kernel processor. The kernel processor includes a pair of processing rolls spaced apart from each other by a roll gap. Kernels in the crop material are fractured, i.e., cracked, as they move between the pair of processing rolls. The kernels include an outer shell or hull, which acts as a barrier against digestion by an animal. The hull of the kernel must be broken. The hull of the kernels may be broken by the animal via chewing, or may be mechanically broken by the kernel processor prior to being fed to the animal. Fracturing or cracking the hull improves the digestibility of the kernel, thereby allowing a greater amount of the nutrients within the kernel to be absorbed by the animal, and reducing waste of useful nutrients. The crop material is directed from the kernel processor into a discharge spout, which directs the crop material through an exit and into a storage container. 
     A maximum potential nutrient value of the crop material may be achieved when the crop material is processed to a desired degree or level of processing. Failure to process the crop material to these desired levels may result in the crop material failing to deliver its maximum potential nutrient value to an animal when consumed. The nutrients of the crop material that are not absorbed by the animal are wasted, thereby reducing the effectiveness and/or efficiency of the crop material as animal feed. Accordingly, it is desirable to process the crop material to the desired degree or level of processing to maximize nutrient absorption by the animal. 
     Different crop materials, or crop materials at different stages of maturation may require different amounts of processing and/or different settings for the crop processor to achieve the desired degree or level of processing to maximize nutrient absorption by the animal. For example, kernels of corn that are more mature tend to have a lower moisture content and have a drier, harder shell. Corn kernels having a lower moisture content, and thereby having a harder shell require a smaller roll gap between processing rolls of a kernel processor to achieve a desired level or kernel fracture or cracking, whereas corn kernels having a higher moisture content, and thereby having a softer shell may use a larger roll gap between the processing rolls to achieve the same level of kernel fracture or cracking. 
     SUMMARY 
     A harvester implement is provided. The harvester implement includes a head unit that is operable to gather crop material and direct the crop material along a flow path. A crop processor is positioned to receive the crop material from the head unit and partially defines the flow path of the crop material. The crop processor is operable to process the crop material to alter a characteristic of the crop material. A moisture sensor is operable to sense data related to a moisture content of the crop material as the crop material moves along the flow path. A computing device is in communication with the moisture sensor. The computing device includes a processor and a memory having a crop processing analysis algorithm stored thereon. The processor is operable to execute the crop processing analyses algorithm to receive the data related to the moisture content of the crop material from the moisture sensor. The computing device may then analyze the data related to the moisture content to determine an actual moisture content of the crop material. The computing device may then adjust the crop processor based on the actual moisture content of the crop material to achieve a desired level of alteration to the characteristic of the crop material. 
     In one aspect of the disclosure, the crop processor includes a kernel processor. The kernel processor includes a first processing roll and a second processing roll spaced from the first processing roll by a roll gap. The crop material passes through the roll gap between the first processing roll and the second processing roll for fracturing a kernel portion of the crop material. The processor is operable to execute the crop processing analyses algorithm to adjust the roll gap based on the actual moisture content of the crop material. 
     In one aspect of the disclosure, the processor is operable to execute the crop processing analyses algorithm to receive a plurality of user defined moisture ranges via a user input, such as but not limited to a touch screen display. Each of the user defined moisture ranges has a corresponding user defined processor setting. In one implementation, the user defined processor setting is a user defined roll gap for the kernel processor. The computing device may determine which one of the plurality of user defined moisture ranges the actual moisture content of the crop material is within, and adjust the crop processor to the corresponding user defined processor setting, e.g., the user defined roll gap setting. 
     In one aspect of the disclosure, the moisture sensor is positioned downstream of the crop processor along the flow path of the crop material. The harvester implement may include a discharge spout that is positioned to receive the crop material from the crop processor and partially define the flow path of the crop material. In one implementation, the moisture sensor is positioned in the discharge spout. 
     In one aspect of the disclosure, the processor is operable to execute the crop processing analyses algorithm to predict a moisture content immediately ahead of the head unit relative to a direction of travel of the head unit. The computing device may predict the moisture content based at least partially on the actual moisture content of the crop material previously processed. The computing device may then adjust the crop processor based on the predicted moisture content immediately ahead of the head unit to achieve the desired level of alteration to the characteristic of the crop material. 
     A method of controlling a harvester implement is also provided. The method includes determining an actual moisture content of crop material with a computing device. The computing device may then adjust a roll gap between a first processing roll and a second processing roll of a kernel processor based on the actual moisture content of the crop material. 
     In one aspect of the disclosure, a plurality of user defined moisture ranges are defined. Each of the plurality of user defined moisture ranges has a corresponding user defined roll gap setting that is also defined. The plurality of user defined moisture ranges and the corresponding user defined roll gap setting for each moisture range is saved in a memory of the computing device. 
     The computing device may determine which one of the plurality of user defined moisture ranges the actual moisture content of the crop material is within, and adjust the roll gap to the user defined roll gap setting corresponding with the user defined moisture range that the actual moisture range is within. 
     In one aspect of the disclosure, the computing device may predict a moisture content immediately ahead of the head unit relative to a direction of travel of the head unit based at least partially on the actual moisture content of the crop material. The computing device may then adjust the roll gap to the user defined roll gap setting corresponding with the user defined moisture range that the predicted moisture content immediately ahead of the head unit is within. 
     The harvesting implement and the method described herein enable the crop processor to be controlled based on the moisture content of the crop material. Because, in some situations, the amount of crop processing required to achieve a desired level of crop processing is strongly related to the moisture content of the crop material, controlling the crop processor based on the moisture content provides a simple and convenient process to automatically control the crop processor. 
     The above features and advantages and other features and advantages of the present teachings are readily apparent from the following detailed description of the best modes for carrying out the teachings when taken in connection with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a schematic cut-away side view of a harvester implement. 
         FIG. 2  is a schematic plan view of the harvester implement. 
         FIG. 3  is a chart showing a user input including a plurality of moisture ranges and a respective processor setting for each moisture range. 
         FIG. 4  is a flowchart representing a method of controlling the harvester implement. 
     
    
    
     DETAILED DESCRIPTION 
     Those having ordinary skill in the art will recognize that terms such as “above,” “below,” “upward,” “downward,” “top,” “bottom,” etc., are used descriptively for the figures, and do not represent limitations on the scope of the disclosure, as defined by the appended claims. Furthermore, the teachings may be described herein in terms of functional and/or logical block components and/or various processing steps. It should be realized that such block components may be comprised of any number of hardware, software, and/or firmware components configured to perform the specified functions. 
     Terms of degree, such as “generally”, “substantially” or “approximately” are understood by those of ordinary skill to refer to reasonable ranges outside of a given value or orientation, for example, general tolerances or positional relationships associated with manufacturing, assembly, and use of the described embodiments. 
     Referring to the Figures, wherein like numerals indicate like parts throughout the several views, a harvester implement is generally shown at  20 . The harvester implement  20  shown in the Figures and described herein is configured as a forage harvester. However, it should be appreciated that the harvester implement  20  may be configured differently than the example forage harvester shown in the Figures and described herein. 
     Referring to  FIG. 1 , the harvester implement  20  includes a frame  22 , which supports the various components of the harvester implement  20 . The frame  22  rotatably supports a plurality of ground engaging elements  24 , such as but not limited to a pair of front wheels or tracks and a pair of rear wheels or tracks. In the example embodiment shown in  FIG. 1  and described herein, the front wheels are drive wheels and the rear wheels are steerable wheels. However, it should be appreciated that the ground engaging elements  24  and the propulsion and steering thereof, may differ from the example embodiment shown in  FIG. 1  and described herein. 
     Referring to  FIG. 1 , the harvester implement  20  includes a head unit  26 . The head unit  26  is operable to gather crop material from a field and direct the crop material through the harvester implement  20  along a flow path  28 . The head unit  26  is disposed at the forward end  30  of the harvester implement  20 , relative to a direction of travel  32  of the harvester implement  20  when gathering the crop material. The head unit  26  is attached to and supported by the frame  22 . The configuration and operation of the head unit  26  may vary depending upon the crop material being gathered.  FIG. 1  shows an implementation of the head unit  26  operable for cutting and gathering standing corn. It should be appreciated that the head unit  26  may differ for other crop materials, such as alfalfa, grasses, sorghum, cereals, barley, fine grains, course grains, or other crop materials. The different configurations and operation of the different head units  26  are known to those skilled in the art, are not pertinent to the teachings of this disclosure, and are therefore not described in detail herein. 
     Referring to  FIG. 1 , the harvester implement  20  includes a feeder  34 . The feeder  34  is positioned immediately rearward of the head unit  26  relative to the flow path  28  of the crop material. The feeder  34  is operable to move crop material gathered by the head unit  26  in a direction of crop processing and along the flow path  28 . The direction of crop processing is generally directed rearward and possibly laterally relative to the direction of travel  32  of the harvester implement  20  when gathering crop material. In the example embodiment described herein, the feeder  34  may include a pair of opposing feed rollers, i.e., an upper feed roller  36  and a lower feed roller  38 . The upper feed roller  36  and the lower feed roller  38  are spaced apart from each, with the gathered crop material fed between the upper feed roller  36  and the lower feed roller  38 . The upper feed roller  36  and the lower feed roller  38  are counter-rotated relative to each other to move the crop material therebetween. The specific details and operation of the feeder  34  are known to those skilled in the art, are not pertinent to the teachings of this disclosure, and are therefore not described in greater detail herein. Furthermore, the configuration and operation of the feeder  34  may differ from the example embodiment shown in the Figures and described herein. 
     Referring to  FIG. 1 , the harvester implement  20  further includes at least one crop processor  40 A,  40 B. The crop processor  40 A,  40 B is disposed downstream of the feeder  34  relative to the direction of crop processing of the crop material. The crop processor  40 A,  40 B may include, but is not limited to, a cutter head  40 A and/or a kernel processor  40 B. The crop processor  40 A,  40 B is positioned to receive the crop material from the head unit  26  and partially define the flow path  28  of the crop material. In the example implementation described herein, the crop processor  40 A,  40 B receives the crop material from the head unit  26  via the feeder  34 . The crop processor  40 A,  40 B is operable to process the crop material to alter a characteristic of the crop material. The characteristic of the crop material may include a physical, chemical, or nutritional property of one or more components of the crop material. For example, the characteristic of the crop material may include, but is not limited to, a length of stem portions of the crop material, a degree of fracture or cracking of the stem portions of the crop material, or a degree of fracture or cracking of kernel portions or a kernel wall of the crop material. 
     In the example implementation shown in the Figures, the cutter head  40 A is positioned downstream of the feeder  34 , relative to the flow path  28  of the crop material. The cutter head  40 A is rotatably attached to the frame  22  and is rotatable about an axis of rotation. The axis of rotation of the cutter head  40 A is generally perpendicular to the direction of travel  32  of the harvester implement  20  while gathering crop material, and generally perpendicular to the direction of crop processing. The example embodiment of the cutter head  40 A shown in the Figures and described herein includes a cylindrical drum  42  having a plurality of knives  44  disposed circumferentially about the outer periphery of the drum  42 . 
     Referring to  FIG. 1 , a shear bar  46  is located immediately downstream of the feeder  34  relative to the direction of crop processing of the crop material. The shear bar  46  is attached to and supported by the frame  22 . The cutter head  40 A cooperates with the shear bar  46  to cut the crop material into smaller pieces, with each of the smaller pieces having or defining a respective cut length. As such, the characteristic of the crop material may include the cut length of the stem portions of the crop material, with at least the feeder  34  and/or the cutter head  40 A being operable to alter the cut length of the stem portions of the crop material. The drum  42  of the cutter head  40 A rotates in a rotational direction about its axis of rotation, with the knives  44  oriented to cut the crop material when the drum  42  rotates. The shear bar  46  braces the crop material against the cutting action of the knives  44  to facilitate the cutting of the crop material. At least one of the shear bar  46  and the cylindrical drum  42  may move relative to the frame  22  such that the shear bar  46  and the cylindrical drum  42  may be moveable relative to each other to adjust the cut length of the crop material. The specific features and operation of the cutter head  40 A and its relation to the shear bar  46  with regard to cutting the crop material to the cut length are known to those skilled in the art, are not pertinent to the teachings of this disclosure, and are therefore not described in greater detail herein. 
     Referring to  FIG. 1 , the kernel processor  40 B is positioned downstream of the cutter head  40 A relative to the flow path  28  of the crop material, and receives the crop material from the cutter head  40 A. The kernel processor  40 B includes a pair of opposing processing rolls, i.e., a first processing roll  48  and a second processing roll  50 . The first processing roll  48  and the second processing roll  50  are rotated at different speeds to further process portions of the crop material, e.g., kernels of the crop material, by fracturing or cracking one or more walls of the kernels. As such, the characteristic of the crop material may include the wall of the kernels, i.e., the kernel wall, with the kernel processor  40 B being operable to crack or fracture the kernel wall of the kernels of the crop material. As used herein, the term “kernel wall” includes the bran layer of a grain. As understood by those skilled in the art, the bran layer is the hard outer layer of a grain that protects the seed. The first processing roll  48  and the second processing roll  50  are separated by a roll gap  52  and are biased together. The roll gap  52  may be between, approximately, 0.75 mm and 3.0 mm. At least one of the first processing roll  48  and the second processing roll  50  is moveable relative to the frame  22 , such that the first processing roll  48  and the second processing roll  50  are moveable relative to each other to adjust the distance of the roll gap  52  for different crop materials. Each of the first processing roll  48  and the second processing roll  50  may include teeth, ridges, valleys, etc., that help fracture and/or crack the kernel walls of the kernel portions of the crop material to improve digestibility. The specific features and operation of the kernel processor  40 B are known to those skilled in the art, are not pertinent to the teachings of this disclosure, and are therefore not described in greater detail herein. 
     The harvester implement  20  further includes a discharge spout  54 . The discharge spout  54  is positioned downstream of the kernel processor  40 B relative to the flow path  28  of the crop material. The discharge spout  54  includes an inlet  56  positioned to receive the crop material from the crop processor  40 A,  40 B, e.g., the cutter head  40 A and/or the kernel processor  40 B, and partially defines the flow path  28  of the crop material. The discharge spout  54  may include an exit  58  that is positioned to expel the crop material into a storage container  60 . The discharge spout  54  may include, but is not limited to, an elongated tubular structure that is shaped to guide and direct the crop material into the storage container  60 . In one implementation, the storage container  60  may include a bin supported by the frame  22  and integral with the harvester implement  20 . In another implementation, such as shown in  FIG. 2 , the storage container  60  may include a truck, trailer, dump truck, semi-truck and trailer, or other similar vehicle and/or vehicle trailer combination that is positioned adjacent to the harvest implement and positioned to receive the crop material from the discharge spout  54 . 
     The harvester implement includes a moisture sensor  64  that is operable to sense data related to a moisture content of the crop material as the crop material moves along the flow path  28 . In the example implementation shown in the Figures and described herein, the moisture sensor  64  is positioned downstream of the crop processor  40 A,  40 B along the flow path  28  of the crop material. For example, the moisture sensor  64  may be positioned in the discharge spout  54 . However, in other implementations, the moisture sensor  64  may be positioned upstream of the crop processor  40 A,  40 B along the flow path  28  of the crop material. 
     The moisture sensor  64  may include any device that is capable of sensing data related to the moisture content of the crop material. For example, the harvester implement  20  may include a Near InfraRed (NIR) sensor  82  that is positioned to capture a NIR image of the crop material in a NIR light spectrum. The NIR sensor  82  may be positioned at any point along the flow path  28  of the crop material. In the example implementation shown in the Figures and described herein, the NIR sensor  82  is positioned within a wall  84  of the discharge spout  54  to capture the NIR image of the crop material within the discharge spout  54 . The NIR sensor  82  captures the NIR image in the NIR light spectrum. The NIR light spectrum includes light having a wavelength between the range of approximately 700 nanometers and 2,500 nanometers. The NIR image may be analyzed by the NIR sensor  82  or by a computing device  86  (described below) to determine the moisture content of the crop material. It should be appreciated that the moisture sensor  64  may be implemented in other ways using other systems and/or sensing devices that sense other types of data related to the moisture content of the crop material. 
     Referring to  FIG. 1 , the harvester implement  20  may further include the computing device  86 . The computing device  86  is disposed in communication with the moisture sensor  64  and the crop processor  40 A,  40 B. The computing device  86  may alternatively be referred to as a computer, a controller, a control unit, a control module, etc. The computing device  86  may be located on the harvester implement  20 , or remote from the harvester implement  20 . The computing device  86  is operable to monitor the operation of the crop processor  40 A,  40 B, and may additionally be operable to control the operation of the harvester implement  20 . The computing device  86  includes a processor  88 , a memory  90 , and all software, hardware, algorithms, connections, sensors, etc., necessary to monitor and/or control the operation of the one or more components of the harvester implement  20 , such as but not limited to, the crop processor  40 A,  40 B, etc. As such, a method may be embodied as a program or algorithm operable on the computing device  86 . It should be appreciated that the computing device  86  may include any device capable of analyzing data from various sensors, comparing data, making the necessary decisions required to monitor and/or control the operation of the crop processor  40 A,  40 B, or some other component of the harvester implement  20 . 
     As used herein, “computing device” or “controller” are 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  90  or received via the communication capabilities) to control or communicate with one or more other components. In certain embodiments, a controller may also be referred to as a control unit, vehicle control unit (VCU), engine control unit (ECU), transmission control unit (TCU), or electrical controller. In certain embodiments, a controller 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  86  may be in communication with other components on the harvester implement  20 , such as hydraulic components (e.g., valve block), electrical components (e.g., solenoid, accumulator sensor), actuators, sensors, and operator inputs within an operator station of the work vehicle. The computing device  86  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  86  and the other components. Although the computing device  86  is referenced in the singular, in alternative implementations the configuration and functionality described herein can be split across multiple computing devices using techniques known to a person of ordinary skill in the art. 
     The computing device  86  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  90  may include any non-transitory/tangible medium which participates in providing data or computer-readable instructions. The memory  90  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 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. 
     As described above, the computing device  86  includes the processor  88  and the memory  90 . The memory  90  includes a crop processing analysis algorithm  104  stored thereon. The processor  88  is operable to execute the crop processing analysis algorithm  104  to implement a method of monitoring the operation of the crop processor  40 A,  40 B, and/or controlling the harvester implement  20 . 
     Referring to  FIG. 4 , the processor  88  is operable to execute the crop processing analysis algorithm  104  to receive a user input providing a plurality of user defined moisture ranges  68 ,  70 ,  72 ,  74 ,  76 . The step of inputting the user defined moisture ranges  68 ,  70 ,  72 ,  74 ,  76  and their respective processor settings is generally indicated by box  220  shown in  FIG. 4 . Each of the user defined moisture ranges  68 ,  70 ,  72 ,  74 ,  76  has a corresponding user defined processor setting. Referring to  FIG. 1 , the user defined moisture ranges  68 ,  70 ,  72 ,  74 ,  76  and their respective user defined processor settings may be input by an operator into the computing device  86  using a suitable input device  66 , such as but not limited to, a keyboard, a touch screen display, audio receiver, joystick, etc. The input device  66  may be separate from, or integral with an output  62 . For example, the input device  66  and the output  62  may be combined as a touch screen display or other similar device located in a cab of the harvester implement  20 . 
     The actual moisture content of the crop material may be related to and/or correspond with a setting for the crop processor  40 A,  40 B that is necessary to achieve a desired level of crop processing. In other words, the settings for the crop processor  40 A,  40 B in order to achieve the desired level of alteration to the crop material or a desired level or crop processing may change dependent upon the actual moisture content of the crop material. For example, kernel portions of crop material having a higher actual moisture content are relatively easier to crack or fracture when compared to kernel portions of crop material having a lower actual moisture content. As such, in order to achieve a desired level of crop processing, e.g., a specific level of kernel wall fracture or cracking, the roll gap  52  of the kernel processor  40 B may be set to a smaller distance when processing kernels having a higher moisture content, and may need to be set to a larger distance when processing kernels having a lower moisture content. Accordingly, the roll gap  52  for the kernel processor  40 B required to achieve a certain level of kernel fracture varies or changes in relation to the moisture content of the crop material. The process described herein adjusts the crop processor  40 A,  40 B based on the actual moisture content of the crop material to achieve a desired level of alteration to the characteristic of the crop material. 
     The number or moisture ranges  68 ,  70 ,  72 ,  74 ,  76  may include two ranges, three ranges, four ranges, etc. Each of the moisture ranges  68 ,  70 ,  72 ,  74 ,  76  may be defined to include a lower limit and an upper limit. For example, referring to  FIG. 3 , a total of five example moisture ranges  68 ,  70 ,  72 ,  74 ,  76  are defined, with each of the respective moisture ranges  68 ,  70 ,  72 ,  74 ,  76  having a defined processor setting. It should be appreciated that the moisture ranges  68 ,  70 ,  72 ,  74 ,  76  may differ from the example number and value of the ranges shown in  FIG. 3 . 
     As shown in  FIG. 3 , a first range  68  is defined to include a lower moisture limit of 0.0%, and an upper moisture limit of 55.0%. A second range  70  is defined to include a lower moisture limit of 55.1% and an upper moisture limit of 60.0%. A third range  72  is defined to include a lower moisture limit of 60.1% and an upper moisture limit of 65.0%. A fourth range  74  is defined to include a lower moisture limit of 65.1% and an upper moisture limit of 70.0%. A fifth range  76  is defined to include a lower moisture limit of 70.1% and an upper moisture limit of 100%. 
     In the example implementation shown in  FIG. 3 , the defined processor setting for each respective one of the plurality of user defined moisture ranges  68 ,  70 ,  72 ,  74 ,  76  is a user defined roll gap setting for the kernel processor. However, in other implementations, the defined processor setting may include a different processor setting, such as but not limited to a cut length setting for the cutter head. In the example implementation shown in  FIG. 3 , the first range  68  has a respective first roll gap setting  92  that is equal to 1.00 mm. The second range  70  has a respective second roll gap setting  94  that is equal to 1.25 mm. The third range  72  has a respective third roll gap setting  96  that is equal to 1.50 mm. The fourth range  74  has a respective fourth roll gap setting  98  that is equal to 2.00 mm. The fifth range  76  has a respective fifth roll gap setting  100  that is equal to 2.50 mm. 
     Once the user defined moisture ranges  68 ,  70 ,  72 ,  74 ,  76  and their respective user defined processor settings have been input into the computing device  86 , operation of the harvester implement  20  may begin. The step of harvesting the crop material is generally indicated by box  222  shown in  FIG. 4 . It should be appreciated that operation of the harvester implement  20  includes maneuvering the harvester implement  20  through a field, whereby the head unit  26  gathers the crop material from the field. Once the crop material is gathered, the feeder  34  moves the crop material in the direction of crop processing along the flow path  28  of the crop material. In the example implementation of the harvester implement  20  shown in the figures and described herein, the crop material moves through the cutter head  40 A, whereby the stem portions of the crop material are cut to define an actual cut length of the stem portions. Following the cutter head  40 A, the crop material moves through the kernel processor  40 B, whereby the walls of the kernel portions of the crop material are fractured or cracked. As noted above, processing the crop material, i.e., cutting the stems and/or fracturing or cracking the kernels, improves the digestibility of the crop material, thereby allowing a greater amount of the nutrients within the crop material to be absorbed by the animal, and reducing waste of useful nutrients. Upon exiting the kernel processor  40 B, the crop material moves through the entrance of the discharge spout  54 . The discharge spout  54  directs the crop material therethrough and dispenses the crop material through the exit  58  of the discharge spout  54 , into the storage container  60 . 
     In the example implementation of the harvester implement  20  described herein, as the crop material moves through the discharge spout  54 , the processor  88  is operable to execute the crop processing analysis algorithm  104  to sense data related to the moisture content of the crop material with the moisture sensor  64 . The step of sensing the data related to the actual moisture content of the crop material is generally indicated by box  224  shown in  FIG. 4 . The moisture sensor  64  may then communicate the data related to the moisture content of the crop material to the computing device  86 . As described above, the moisture sensor  64  may be implemented with the NIR sensor  82  described herein. The NIR sensor  82  may continuously capture NIR images, and communicate the NIR images to the computing device  86  for analysis. 
     The computing device  86  is operable to receive the data related to the moisture content of the crop material from the moisture sensor  64 . For example, in the implementation described herein, the computing device  86  may receive the NIR images from the NIR sensor  82 . However, in other implementations, the data related to the moisture content of the crop material received from the moisture sensor  64  may differ from the example NIR images described herein. 
     Once the computing device  86  has received the data related to the moisture content of the crop material from the moisture sensor  64 , the computing device  86  may analyze the data related to the moisture content to determine an actual moisture content of the crop material. The step of determining the actual moisture content is generally indicated by box  226  shown in  FIG. 4 . The way the computing device  86  may analyze the data related to the moisture content may differ or vary based on the type and/or form of the data. In the example implementation described herein, the processor  88  may be operable to execute the crop processing analysis algorithm  104  to analyze the NIR image to determine the moisture content and/or a starch content of the crop material. For example, the computing device may include image and/or color recognition and analysis software that identifies the objects and their respective color in the near infrared color spectrum, and associates those colors with a respective moisture content. It should be appreciated that the computing device  86  may analyze the NIR image to determine the moisture content of the crop material in some other manner not described herein. Furthermore, it should be appreciated that the analysis of the NIR image may occur within the NIR sensor  82  itself, and that the data related to the moisture content of the crop material communicated to the computing device  86  from the NIR sensor  82  may include the actual moisture content percentage of the crop material. 
     Once the moisture content of the crop material has been determined, the processor  88  is operable to execute the crop processing analyses algorithm  104  to determine which one of the plurality of user defined moisture ranges  68 ,  70 ,  72 ,  74 ,  76  the actual moisture content of the crop material is within. The step of determining which of the plurality of moisture ranges  68 ,  70 ,  72 ,  74 ,  76  and the associated processor setting for the actual moisture content is generally indicated by box  228  shown in  FIG. 4 . For example, referring to  FIG. 3 , in the example implementation described herein, if the actual moisture content of the crop material is determined to be 63.0%, then the computing device  86  may determine that the actual moisture content of the crop material is within the third range  72 . 
     As noted above, each of the different user defined moisture ranges  68 ,  70 ,  72 ,  74 ,  76  has a respective user defined processor setting. Once the computing device has determined which one of the plurality of user defined moisture ranges  68 ,  70 ,  72 ,  74 ,  76  the actual moisture content of the crop material is within, then the computing device may adjust the crop processor  40 A,  40 B to the corresponding user defined processor setting. The step of adjusting the crop processor  40 A,  40 B to provide the user defined processor setting is generally indicated by box  230  shown in  FIG. 4 . In the example implementation described herein, the user defined processor setting is a user defined roll gap setting  92 ,  94 ,  96 ,  98 ,  100 . Accordingly, in the example implementation described herein, the processor  88  is operable to execute the crop processing analyses algorithm  104  to adjust the roll gap  52  to achieve the roll gap setting  92 ,  94 ,  96 ,  98 ,  100  based on the actual moisture content of the crop material. 
     Because the roll gap setting  92 ,  94 ,  96 ,  98 ,  100  is related to the desired level of alteration to the characteristic of the crop material, e.g., the percentage or actual degree of kernel wall fracture or cracking, adjusting the roll gap  52  based on the actual moisture content of the crop material enables the harvester implement  20  to achieve the desired level of alteration of the characteristic of the crop material, e.g., the percentage or actual degree of kernel wall fracture or cracking of the crop material. 
     As described above, the process of controlling the harvester implement  20  uses the actual moisture content of harvested crop material to retroactively control the processor setting, e.g., the roll gap  52  of the kernel processor  40 B. However, it is contemplated that the actual moisture content of the harvested crop material may be tracked throughout the field, thereby providing sufficient data for the computing device  86  to develop a model predicting the moisture content throughout the remainder of the field. The step of developing the model of the moisture content in the field is generally indicated by box  232 . As such, the processor  88  may be operable to execute the crop processing analyses algorithm to predict a moisture content immediately ahead of the head unit  26  relative to a direction of travel  32  of the head unit  26  based at least partially on the actual moisture content of the crop material previously processed. The computing device  86  may use the actual moisture content from crop material, in combination with other data, such as but not limited to previously harvested crop data, weather data, etc., and generate the map or model of predicted moisture content throughout the field. 
     The computing device  86  may determine if the model is complete, or is not complete. the step of determining if the model is complete is generally indicated by box  234  shown in  FIG. 4 . If the computing device  86  determines that the model is not complete, generally indicated at  236  in  FIG. 4 , then the process continues to control the crop processor  40 A,  40 B, retroactively based on the actual moisture content of the crop material previously harvested. 
     If the computing device  86  determines that the model is complete, generally indicated at  238  in  FIG. 4 , then the computing device may use the map of the predicted moisture content to determine a predicted moisture content of the crop material  108  immediately ahead of the head unit  26 . The step of predicting the moisture content of the crop material from the model is generally indicated by box  240  shown in  FIG. 4 . The process, techniques, and software for generating the model of predicted moisture content of the crop material are known to those skilled in the art, and are therefore not described in detail herein. 
     Once the computing device  86  has generated the model of the predicted moisture content of the crop material, based at least in part on the actual moisture content of the crop material previously harvested that day, the computing device  86  may then adjust the crop processor  40 A,  40 B based on the predicted moisture content immediately ahead of the head unit  26  to achieve the desired level of alteration to the characteristic of the crop material. The step of adjusting the processor setting based on the predicted moisture content of the crop material from the model derived from the actual moisture content of the crop material is generally indicated by box  242  shown in  FIG. 4 . For example, and as described above, the computing device  86  may adjust the roll gap  52  to provide the defined roll gap setting  92 ,  94 ,  96 ,  98 ,  100  for the predicted moisture content of the crop material. In doing so, the computing device  86  may determine which moisture range the predicted moisture content of the crop material  108  immediately ahead of the heat unit  26  is within, and then control the control the crop processor  40 A,  40 B to provide the processor setting, e.g., roll gap setting  92 ,  94 ,  96 ,  98 ,  100  associated with that respective moisture range. In so doing, the computing device  86  may proactively control the crop processor  40 A,  40 B, e.g., the roll gap  52  of the kernel processor  40 B, based on the actual moisture content of the crop material, because the model used to generate the predicted moisture content of the crop material is based on the actual moisture content of the crop material measured at that time. 
     As used herein, “e.g.” is utilized to non-exhaustively list examples, and carries the same meaning as alternative illustrative phrases such as “including,” “including, but not limited to,” and “including without limitation.” As used herein, unless otherwise limited or modified, lists with elements that are separated by conjunctive terms (e.g., “and”) and that are also preceded by the phrase “one or more of,” “at least one of,” “at least,” or a like phrase, indicate configurations or arrangements that potentially include individual elements of the list, or any combination thereof. For example, “at least one of A, B, and C” and “one or more of A, B, and C” each indicate the possibility of only A, only B, only C, or any combination of two or more of A, B, and C (A and B; A and C; B and C; or A, B, and C). As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. Further, “comprises,” “includes,” and like phrases are intended to specify the presence of stated features, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups thereof. 
     The detailed description and the drawings or figures are supportive and descriptive of the disclosure, but the scope of the disclosure is defined solely by the claims. While some of the best modes and other embodiments for carrying out the claimed teachings have been described in detail, various alternative designs and embodiments exist for practicing the disclosure defined in the appended claims.