Patent Publication Number: US-2022232753-A1

Title: Implement mounted sensors sensing seed and residue characteristics and control

Description:
FIELD OF THE DESCRIPTION 
     The present description relates to agricultural machines. More specifically, the present description relates to the control of agricultural machines based on characteristics sensed by a sensor system mounted to the agricultural machine. 
     BACKGROUND 
     There are a wide variety of different types of agricultural machines that can be used in a wide variety of agricultural operations. Some of the agricultural machines can include a variety of sensors that sense different characteristics. For example, the sensors can sense characteristics of the agricultural surface upon which the agricultural machines can operate and/or characteristics relative to the operation and performance of the agricultural machine. 
     Some agricultural machines include planters that have row units. For instance, a row unit is often mounted on a planter with a plurality of other row units. The planter is often towed by a tractor over soil where seed is planted in the soil, using the row units. The row units on the planter follow the ground profile by using a combination of a downforce assembly, that imparts a downforce on the row unit to push disc openers into the ground to open a furrow, and gauge wheels to set the depth of penetration of the disc openers. 
     The discussion above is merely provided for general background information and is not intended to be used as an aid in determining the scope of the claimed subject matter. 
     SUMMARY 
     A mobile agricultural machine includes a row unit having a furrow opener mounted to the row unit and configured to engage a surface of ground over which the mobile agricultural machine travels to open a furrow in the ground. A furrow closer is mounted to the row unit behind the furrow opener relative to a direction of travel of the mobile agricultural machine and is configured to engage the surface of the ground to close the furrow. An image sensor system is mounted to the row unit and configured to sense characteristics of residue and seeds in the furrow opened by the furrow opener and generate a sensor signal indicative of the characteristics. The mobile agricultural machine can further include a control system configured to generate a residue/seed characteristic indicator corresponding to the sensed characteristics and to generate an action signal to control an action of the mobile agricultural machine based on the residue/seed characteristic indicator. 
     This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. The claimed subject matter is not limited to implementations that solve any or all disadvantages noted in the background. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIGS. 1A-C  show example images of an agricultural surface. 
         FIG. 2  shows one example of a top view of an agricultural machine. 
         FIG. 3  shows one example of a side view of a row unit of an agricultural machine. 
         FIG. 4  shows one example of a side view of a furrow sensing system of a row unit on an agricultural machine. 
         FIG. 5  is a block diagram of one example of an agricultural machine architecture. 
         FIG. 6  is a block diagram of one example of a seed/residue characteristic identifier system. 
         FIGS. 7A and 7B  (collectively referred to herein as  FIG. 7 ) are flow diagrams showing example operations of the agricultural machine. 
         FIG. 8  is a block diagram showing the architecture illustrated in  FIG. 5  deployed in a remote server architecture. 
         FIGS. 9-11  show examples of mobile devices that can be used in the architectures shown in the previous FIGS. 
         FIG. 12  is a block diagram showing one example of a computing environment that can be used in the architectures illustrated in previous FIGS. 
     
    
    
     DETAILED DESCRIPTION 
     During the performance of various agricultural operations, it can be helpful to have data indicative of characteristics relative to the agricultural surface, the quality of the job being performed, the operation of the agricultural machine, as well as various other data. In the example of planting, for instance, it can be helpful to understand the characteristics and quality of the environment that the seeds are being placed into. Several agronomic factors and machine operation parameters can have an affect on the characteristics and quality of that environment. 
     For example, residue can have an effect on the development of seeds planted in a field. When residue is closely proximate (or touching) a seed in a furrow, it can affect the thermal and moisture transfer from the soil to the seed. Therefore, residue can affect the uniformity and rate with which seeds germinate. Similarly, seeds can be affected by chemicals released from residue as the residue deteriorates. Further, residue that is on the surface of the field, or near the surface of the field (such as within the top two inches of the soil) can inhibit soil warming by reflecting light. Thus, even if the residue is not adjacent to a seed, or touching a seed, it can still affect the rate of seed germination. In addition, residue can present a physical barrier to root growth or emergence (depending on whether the residue is below or above the seed), and it can draw or otherwise increase the incidents of disease and insects. The non-uniform emergence of seeds related to the affects of residue leads to competition between adjacent plants, and can affect yield by as much as 5-10%. 
     The present description thus proceeds with respect to a planting machine that has an image sensor mounted (such as behind a furrow opener and ahead of a furrow closer) and which captures images of an area proximate the furrow. A system then identifies residue characteristics, and seed characteristics, in the images. For instance, the system can identify seed and residue distribution and the location of residue relative to the location of seeds. The system generates an action signal based upon the seed and residue characteristics identified in the images. The action signal can be used, for instance, to control communication with another system, to control different settings on the planting machine, to manipulate residue or seed in the furrow or proximate the furrow, among other things. 
       FIGS. 1A-C  show examples of images of agricultural surfaces having been operated on by an agricultural machine. Generally,  FIGS. 1A-C  show a sensor output (e.g., an image taken by a camera) indicative of the level of residue relative to a furrow opened by a planter. Image  6  in  FIG. 1A  includes agricultural surface  8 , furrow  10  and residue  12 . 
     As can be seen in  FIG. 1A , there is heavy residue and no seeds are visible, because they are covered by residue. Thus, the residue will significantly affect soil warming and the thermal and moisture transfer from the soil to the seed. Similarly, the residue may present a physical barrier to root growth and emergence and may increase the affects of insects, chemicals, and diseases on the seed. 
     In  FIG. 1B , there is little residue and the furrow quality is high.  FIG. 1B  shows seed  11  in furrow  10  and that there is little residue  12  proximate seed  11 , on the soil surface, or in the top several inches of soil. Thus, residue  12  will have less of an impact on the development of seed  11  than the residue shown in  FIG. 1A . 
     In  FIG. 1C  there is heavy residue  12  on the soil surface, but relatively little residue  12  in the furrow  10 .  FIG. 1C  also shows that there are some small pieces of residue  12  close to, but not contacting, seed  11 . Therefore, the residue  12  shown in  FIG. 1C  will have more of an impact on the development of seed  11  than that shown in  FIG. 1B , but less than that shown in  FIG. 1A . 
       FIG. 2  is a top view of one example of an agricultural machine  100 . Agricultural machine  100  illustratively includes planter  101  and towing vehicle  103 . Planter  101  includes a toolbar  102  that is part of a frame  104 .  FIG. 1  also shows that a plurality of row units  106  are mounted to toolbar  102 . Planter  101  can be towed by towing vehicle  103 , such as a tractor. Towing vehicle  103  can include a propulsion system, such as an engine, housed in engine compartment  105 , ground engaging elements  109 , such as wheels or tracks, an operator compartment  107 , such as a cab, which can include a number of machine control mechanisms, user input mechanisms, as well as displays and other user interfaces. Towing vehicle  103  can be linked to planter  101  in a variety of ways, including, but not limited to, mechanically, electrically, hydraulically, pneumatically, etc. Through such linkage, an operator can control vehicle  103  to provide power to planter  101  and/or control the operation of planter  101 , from the operator compartment  107  for example. 
     Planter  101  can also include a material reservoir such as tank  111 , that carries material that can be transmitted to row units  106  for application on the field. The material may be seed, fertilizer, or other material. 
       FIG. 3  is a side view showing one example of a row unit  106 .  FIG. 3  shows that each row unit  106  illustratively has a frame  108 . Frame  108  is illustratively connected to toolbar  102  by a linkage generally shown at  110 . Linkage  110  is illustratively mounted to toolbar  102  so that linkage  110  can move upwardly and downwardly (relative to toolbar  102 ). 
     Row unit  106  also illustratively includes a row cleaner  118 , a furrow opener  120 , a set of gauge wheels  122 , a set of closing wheels  124 , and a seed hopper  112  that stores seed. The seed is provided from hopper  112  to a seed metering subsystem  114  that is driven by a meter motor  115  and that meters the seed and provides the metered seed to a seed delivery system  116 . Seed delivery subsystem  116  is driven by a delivery motor  117  and delivers the seed from the seed metering subsystem  114  to the furrow or trench generated by furrow opener  120  on row unit  106 . In one example, seed metering subsystem  114  uses a rotatable member, such as a disc or concave-shaped rotating member, and an air pressure differential to retain seed on the disc and move it from a seed pool of seeds (provided from hopper  112 ) to the seed delivery subsystem  116 . Other types of meters can be used as well. Delivery subsystem  116  can be a continuous member, such as a brush belt, a flighted belt, or another continuous member that obtains seed from metering subsystem  114  and delivers it to the furrow. Subsystems  114  and  116  can have one or more seed sensors  119  that detect seeds as they pass by sensor(s)  119 . In the example shown in  FIG. 3 , seed sensor  119  is configured to sense seeds in seed delivery subsystem  116 . However, seed sensors can be in seed metering subsystem  114  or in both subsystems  114  and  116  or elsewhere. The speeds of motors  115  and  117  can be varied to vary the spacing between the seeds, or the location of the seeds, in the furrow. 
     Row unit  106  can also include an additional hopper (not shown). The additional hopper can be used to provide additional material, such as fertilizer or another chemical. 
     In operation, as row unit  106  moves in the direction generally indicated by arrow  128 , row cleaner  118  generally cleans the row ahead of the opener  120  to remove debris, such as plant residue from the previous growing season, and the opener  120  opens a furrow in the soil. Gauge wheels  122  illustratively control a depth of the furrow by controlling a depth of engagement that opener  120  has with the soil. Seed is metered by seed metering subsystem  114  and delivered to the furrow by seed delivery subsystem  116 . Closing wheels  124  close the trench over the seed. A downforce generator  131  can also be provided to controllably exert downforce to keep the row unit in desired engagement with the soil. Though not shown in  FIG. 3 , row unit  106  can include a substance delivery system that can deliver a variety of substances, such as fertilizer (e.g., liquid fertilizer, granular fertilizer, etc.), to the furrow before it is closed by closing wheels  124 . 
     Row cleaner  118  can also have a height control system and a down force control system. The height control system and down force control system for row cleaner  118  are shown and described below with respect to  FIG. 5 . 
     As shown in  FIG. 3 , row unit  106  also includes image sensor  132  and supplemental lighting subsystem (e.g., illumination source)  134 , mounted to frame  108 . Image sensor  132  and/or illumination source  134  can be pivotally or otherwise adjustably mounted to row unit  106  such that the position and/or orientation of either or both of sensor  132  and illumination source  134  can be adjusted. For example, adjustment can be made by the operator or automatically by a control system and actuator to, for instance, change a point of view of image sensor  132 , adjust the angle of illumination source  134 , etc. 
     Though shown mounted to row unit  106  between opener  120  and closing wheels  124  it is to be understood that image sensor system  132  and illumination source  134  can be mounted to various locations on row unit  106 . Furthermore, additional sensing systems can be mounted to various locations on row unit  106 , agricultural machine  100  and/or the towing vehicle. For instance, a first sensor system can be placed in front of opener  120 , a second sensor system can be placed as shown in  FIG. 3 , and a third sensor system can be placed behind closing wheels  124 . Additionally, it is to be understood that row unit  106 , agricultural machine  100  and/or the towing vehicle can include various other sensors, as will be discussed further below. It is noted that these are just examples, and numerous other arrangements are contemplated herein. Additionally, it should be understood that each row unit  106  on planter  101  can include a respective image sensor system  132  and illumination source  134 . 
       FIG. 4  is a side view showing one example of an image sensor  132  and illumination source  134  in more detail.  FIG. 4  also has gauge wheel  122  removed to show gauge wheel arm  136 , arm contact member  138 , furrow  140  and seed(s)  142 . As can be seen, as row unit  106  travels over the agricultural surface in the direction of travel as indicated by  128 , row cleaners  118  remove residue, opener  120  opens furrow  140 , into which seed(s)  142  are placed, and soil is placed over seeds  142  by closing wheels  124 . Gauge wheel arm  136  is mounted (e.g., pivotally mounted) to frame  108  and gauge wheel  122  (not shown in  FIG. 4 ). The position of gauge wheel arm  136  controls the position of gauge wheel  122  which in turn controls a depth of furrow  140  by controlling a depth of engagement of opener  120  with the agricultural surface (e.g., the depth of engagement into the soil). The position of gauge wheel arm  136  is controlled by the position of arm contact member  138  which can be controlled manually by an operator, and/or automatically, such as by a control system and corresponding actuator. 
     Illumination source  134  illuminates an area proximate the furrow and image sensor  132  detects an image indicative of characteristics relative to the residue and seeds in furrow  140  and on the agricultural surface and generates an image signal indicative of the image. Illumination system  134  provides illumination to enhance visibility of furrow  140  by image sensor  132 . In one example, image sensor  132  is an optical sensor, such as a visible light camera or a multi-spectral camera that captures an image of furrow  140  and the surrounding agricultural surface, though image sensor  132  can include any number of other image sensors, as well. 
     The characteristics detected by sensor  132  can include, but are not limited to, seed depth, furrow depth, seed orientation, seed position, furrow shape, furrow width, seed location, seed count, residue location, residue level, residue distribution, residue position, residue spacing, residue sizing, residue cover percentage (the percentage of the agricultural surface covered by residue), seed spacing, seed distribution, seed centering, substance (e.g., fertilizer) application, seed to soil contact, as well as a variety of other characteristics. Additional image sensors  132  and illumination sources  134  can be placed behind closing wheels  124  and/or in front of opener  120  to, for example, provide closed loop control, detect characteristics relative to residue on the agricultural surface prior to opening of the furrow, detect characteristics relative to residue on the closed furrow, as well as a variety of other characteristics. 
     The sensor signals (e.g., image(s)) generated by image sensor  132  can be processed to extract the various characteristics (e.g., as values), using any number of suitable techniques, including, but not limited to, contrast enhancement, segmentation, thresholding, color modeling (e.g., RGB), edge detection, black/white analysis, machine learning, neural network processing, pixel testing, pixel clustering, shape detection, as well as various other techniques. These extracted values can then be used, such as by aggregation or other algorithmic data processing, to determine a number of different metrics indicative of an impact of the residue on seed development. This metric can be stored and/or displayed in numerous ways to the operator, including in a time history distribution. Additionally, or alternatively, this metric can be used to control the operation of the agricultural machine  100 . The various operations and control of agricultural machine  100  can include controlling the row cleaner  118  (such as the height and down force of row cleaner  118 ), seed placement in furrow  140 , the application of substances to the field, among other things. Some examples of control of the agricultural machine  100  are discussed in greater detail herein. 
       FIG. 5  is a block diagram of one example of an agricultural machine architecture  200  having an agricultural machine  100  configured to perform a planting operation on an agricultural surface, such as a field. Some items are similar to those shown in previous FIGS. and they are similarly numbered. It will be noted that the items shown on agricultural machine  100  in  FIG. 5  can be on planter  101  or towing vehicle  103 , or distributed with some items on planter  101  and some on towing vehicle  103 , or elsewhere. They are shown together on machine  100  for the sake of example only. 
       FIG. 5  shows that agricultural machine  100  can include one or more processors or servers  160 , communication system  162 , data store  164 , one or more sensors  166 , image processing system  168 , control system  170 , controllable subsystem  172 , operator interface mechanisms  174 , and other items  176 . An operator  178  can interact with operator interface mechanisms  174  to control and manipulate agricultural machine  100 . Therefore, operator interface mechanisms  174  can include pedals, steering wheel, joysticks, linkages, levers, buttons, a display device, a touch sensitive display device, or any of a wide variety of different visual, audible and haptic mechanisms. 
       FIG. 5  also shows that agricultural machine  100  can communicate over a network  180  with one or more remote computing systems  182  that can be accessed by remote users  184 . Therefore, network  180  can be a wide area network, a local area network, a near field communication network, a cellular communication network, or any of a wide variety of different types of networks or combinations of networks. Communication system  162  can facilitate the communication of items on agricultural machine  100  with one another, and can also facilitate communication over network  180 . Therefore, communication system  162  can include any of a variety of different items, such as a controller area network (CAN) bus along with CAN bus control circuitry, or other communication systems that are used to communicate within agricultural machine  100  or over network  180 . 
     In the example shown in  FIG. 5 , sensors  166  can include one or more geographic position sensors  186 . Sensors  186  can be disposed on individual row units  106  or at other places on agricultural machine  100 . Geographic position sensors  186  can include such things as a Global Navigation Satellite System (GNSS) receiver, a cellular triangulation sensor, a dead reckoning system, among others. Seed sensors  119  can be any of a wide variety of seed sensors that sense the seed presence in metering subsystem  114  and/or seed delivery subsystem  116 . Examples of different image sensors  132  are described above. Sensors  166  can also include a wide variety of other sensors  188 . 
     Data store  164  can include seed/residue characteristic-to-action mappings  190 , seed/residue characteristic-to-action model  192 , and data store  164  can store other items  194 . Image processing system  168  can include pre-processing system  196  which, itself, can include contrast enhancement system  198 , segmentation system  202 , thresholding system  204 , and other items  206 . Image processing system  168  can also include seed identifier  208 , seed locator  210 , residue identifier  212 , residue locator  214  and other items  216 . Control system  170  includes seed/residue characteristic identifier system  218 , machine learning system  220 , control action identifier  222 , action signal generator  224 , and other items  226 . Action signal generator  224  can include cleaner downforce controller  228 , height controller  230 , operator interface controller  232 , seed meter motor controller  234 , delivery system motor controller  236 , communication system controller  238 , and other items  240 . Controllable subsystems  172  include supplemental illumination subsystem  134 , row cleaning subsystem  242 , seed metering subsystem  114 , seed delivery subsystem  116 , substance delivery subsystem  244 , steering subsystem  246 , propulsion subsystem  248 , and other items  250 . Row cleaning subsystem  242  can, itself, include downforce system  252 , height control system  254 , and other items  256 . 
     Before describing the overall operation of architecture machine  100  in more detail, a brief description of some of the items in machine  100 , and their operation, will now be provided. Image processing system  168  receives images from image sensors  132  and processes them to identify certain characteristics in the images. Pre-processing system  196  pre-processes the image. A variety of different techniques can be used to pre-process the image. For instance, contrast enhancement system  198  can enhance the image contrast. Segmentation system  202  can segment the image based upon colors or in other ways. Thresholding system  204  can be used to pre-process the image as well. Seed identifier  208  identifies seeds within the image and seed locator  210  locates the seeds (e.g., locate the seeds within the image and identifies a geographic location of the seeds on the ground) based upon the location of the seeds within the image, and based upon a sensor signal from a geographic position sensor  186 . Residue identifier  212  identifies residue in the image and residue locator  214  locates the residue. The seed identifier  208 , seed locator  210 , residue identifier  212  and residue locator  214  can be implemented using any of a wide variety of different types of image processing techniques. Such techniques can include artificial neural networks, Bayesian networks, machine learned models, and other implementations. 
     Based upon the seeds identified in the images and their location, as well as the residue identified in the images, and the residue location. control system  170  can identify seed and residue characteristics and generate action signals to carry out actions based upon the identified characteristics. Seed/residue characteristic identifier system  218  identifies the seed/residue characteristics from the seeds and seed locations and residue and residue locations identified by image processing system  168 . The seed/residue characteristic identifier system can identify a wide variety of different types of characteristics, the residue distribution both on the surface of the field and throughout a top pre-defined number of inches or centimeters (such as the top two inches) of the soil, the separation between seeds and residue, a correlation of the seed and residue distributions, and other characteristics. The characteristic(s) can be used to quantify the impact of residue on the seed development, among other characteristics. Again, system  218  can be implemented as an artificial neural network, a Bayesian network, a characteristic identification model, or any of a wide variety of different types of systems. 
     Machine learning system  220  can be used to perform machine learning on system  218  to improve its operation in identifying seed/residue characteristics. The machine learning can be performed based on user inputs as described below, or in other ways. 
     Control action identifier  222  then identifies the control action to take based upon the identified seed/residue characteristics. In order to do so, control action identifier  222  can access the characteristic-to-action mappings  190  and/or the characteristic-to-action model in data store  164 . Mappings  190  may map the identified seed/residue characteristics to one or more actions that are to be taken in response to those characteristics. For instance, if the residue distribution is too heavy, then the level of residue indicated by the residue distribution may be mapped to a control action to increase the down pressure on row cleaner  118 . This is just one example of a mapping and others are described below. 
     Model  192  may receive, as an input, the identified seed/residue characteristics and generate, as an output, an action indicator identifying actions to be taken. Based upon the identified action, action signal generator  224  generates an action signal to perform the identified action. 
     Cleaner downforce controller  228  controls the downforce system  252  in row cleaning subsystem  244  to control the downforce on the row cleaners  118 . Height controller  230  generates control signals to control the height control system  254  of row cleaning subsystem  242  in order to change the height of row cleaner  118  relative to the frame of row unit  106  or the ground. Operator interface controller  232  can control operator interface mechanisms  174  to generate outputs for operator  178 . The outputs may identify the seed/residue characteristics, the action to be taken in response to those characteristics, and/or other information. Communication system controller  238  can generate control signals to control communication system  162  to communicate with remote computer systems  182  over network  180 , based upon the seed/residue characteristics and the control actions identified. Seed meter motor controller  234  can generate control signals to control the meter motor  115  in seed metering subsystem  114  to adjust the position of the seed in furrow  140 , based upon the seed/residue characteristics. For instance, the speed of the meter motor  115  can be varied so that the seed is placed in the furrow between pieces of residue, or at a position where the seed development will be less affected than at other positions. 
     Delivery system motor controller  236  can control delivery motor  117  to vary the speed of seed delivery subsystem  116 . This variation can be performed to adjust the location at which the seed is deposited into the furrow  140 , again based upon the residue located or residue distribution, or other seed/residue characteristics. 
     Control system  170  can also generate control system signals to control substance delivery subsystem  244  in order to control the delivery of other substances (such as fertilizer, herbicides, or chemicals that increase the speed at which residue deteriorates) into the furrow or elsewhere in the field. Control system  170  can also generate control signals to control steering subsystem  246  to guide the heading of agricultural machine  100 . Control system  170  can also control propulsion subsystem  248  to control the propulsion speed of agricultural machine  100 . These are just examples of how control system  170  can control agricultural machine  100  based upon the identified seed/residue characteristics. 
       FIG. 6  is a block diagram showing one example of seed/residue characteristic identifier system  218 . System  218  illustratively includes seed/residue separation identifier  260 , seed distribution identifier  262 , residue distribution identifier  264 , distribution correlation system  266 , impact quantification system  268 , and other items  270 . Seed/residue separation identifier  260  obtains the locations of the seeds and residue particles from seed locator  210  and residue locator  214  and generates a separation indicator indicating the separation between the seeds and residue. In one example, the separation indicator may identify an average separation distance by which seed is separated from its closest residue particle. In another example, seed/residue separation identifier  260  generates indicators that indicate a level of residue coverage within a given separation distance of seeds. In another example, seed/residue separation identifier  260  generates an indicator that indicates how far the seeds are separated from residue in the vertical direction, such as by considering the location of residue in the top two inches of soil in the furrow and the location of the seed in the furrow. These are only examples of separation indicators that can be generated by seed/residue separation identifier  260 . These and/or other indicators can be generated as well. 
     Seed distribution identifier  262  generates a seed distribution output indicative of a distribution of seeds within the furrow. The seed distribution output may identify average seed separation, or a different representative of the separation or distribution if seeds within the furrow. Similarly, the distributions of seeds in multiple furrows across the planter can be combined or aggregated into an aggregate seed distribution indicator that indicates the aggregate distribution of seeds across the planter. 
     Residue distribution identifier  264  generates a residue distribution indicator indicating the distribution of residue. The residue distribution indicator may be similar to the seed distribution output. For instance, reside distribution identifier  264  can generate an output indicative of the average spacing of residue, the aggregate coverage of residue over a predetermined area, the size of residue particles, the location of residue particles in the top predetermined number of inches or centimeters of soil, or other residue distribution indicators. 
     Distribution correlation system  266  correlates the seed distribution generated by seed distribution identifier  262  and the residue distribution identified by residue distribution identifier  264 . For example, where the residue distribution identifier  264  identifies the separation between particles of residue along different axes in the field, or in the furrow, and where seed distribution identifier  262  identifies the spacing among seeds, the two distributions can be correlated to identifying a representative separation or correspondence between the particles of residue and the seeds. Other correlations can be identified as well. 
     Based upon the seed/residue separation, the seed distribution, the residue distribution, and/or the correlated distributions, impact quantification system  268  generates a quantity indicator that quantifies the impact that the residue is likely to have on the development of the seeds. Impact quantification system  268  may be implemented as an artificial neural network, a quantification model that accepts as inputs the output indicators from identifiers  260 ,  262 , and  264 , and from distribution correlation system  266  and generates a quantification output. The quantification output may be an identifier that identifies a level of impact (such as a numerical indicator ranging over a pre-defined range such as 1-10), or a more elaborate quantification identifier which identifies the impact of the residue on different aspects of the development of the seed (such as the affect on germination, emergence, post-emergence development, etc.). 
     Impact quantification system  268 , as well as the other items in seed/residue characteristic identifier system  218  can be implemented as using a neural network, a Bayesian network, a different type of classifier, a model, or in another way. The implementations of seed/residue characteristic identifier system  218  can be generated and/or trained using machine learning or in other ways. 
       FIGS. 7A and 7B  (collectively referred to herein as  FIG. 7 ) show one example of a flow diagram illustrating the operation of agricultural machine  100 , in identifying seed/residue characteristics and generating action signals to perform actions based upon the identified seed/residue characteristics. In one example, one or more image sensors  132  are deployed on planting machines. In one example, the image sensors are deployed behind the furrow opener  118  and ahead of the furrow closer  124 . Deploying the image sensors in this way is indicated by block  280  in the flow diagram of  FIG. 7 . In one example, the image sensor  132  includes a visible light camera  282 . In another example, the image sensor  132  includes a multi-spectral camera  284  or another image sensor  286 . Also, in one example, the supplemental illumination system  134  is provided as an additional light source  288  on the planter. The image sensors  132  can be deployed in other ways as well, as indicated by block  290 . 
     The present discussion will proceed with respect to a single image sensor  132  capturing an image. However, it will be noted that similar processing can be performed where multiple image sensors  132  are capturing multiple images (e.g., ahead of the opener  118  and/or behind the closer  124 , and across several rows or row units  106 ). 
     Image sensor  132  illustratively captures an image, as indicated by block  292  in the flow diagram of  FIG. 7 . The image, or a representation of the image, is provided by sensor  132  to image processing system  268  where pre-processing system  196  performs image pre-processing on the captured image. Performing pre-processing is indicated by block  294  in the flow diagram of  FIG. 7 . The image pre-processing can take a variety of different forms. Contrast enhancement system  198  can perform contrast enhancement, as indicated by block  296 . Segmentation system  202  can perform image segmentation, as indicated by block  298 . Thresholding system  204  can perform thresholding, as indicated by block  300 , and other items  206  can perform other types of pre-processing, as indicated by block  302 . 
     Image processing system  168  then performs image processing with respect to the seed and residue in the image, as indicated by block  304 . Seed identifier  208  can identify seeds in the image, as indicated by block  306 . Residue identifier  212  can identify residue particles in the image, as indicated by block  308 . Seed locator  210  and residue locator  214  identify the locations of seeds and residue particles in the image, as indicated by block  310 . The seed and residue locations can be relative locations, such as the seed locations relative to the residue particle locations, or they can be absolute locations, such as geographic positions of the seed and residue in the field. Identifying an absolute location can be done by correlating the geographic position sensor signal from geographic position sensor  186 , to the image that is captured from the field, and to thus derive the location of items within the image. In one example, the locations of the seeds and residue particles identified in the image are located within the image and the relative location of each seed, relative to each of the identified residue particles, and the relative location of each residue particle, relative to each seed, is identified. The seed/residue image processing can be performed in other ways as well, as indicated by block  312 . 
     Seed/residue characteristic identifier system  218  then identifies characteristics of the seeds and residue, based upon the outputs from image processing system  168  (such as the seeds identified and located as well as the residue particles identified and located). Identifying characteristics of the seeds and residue is indicated by block  314  in the flow diagram of  FIG. 7 . Seed distribution identifier  262  can identify the seed distribution in the image, as indicated by block  316 . Residue distribution identifier  264  can identify the distribution of residue particles within the image, on the surface, in the furrow, and/or throughout the top X number of inches or centimeters of soil (e.g., the top 2 inches), as indicated by block  318 . Seed/residue separation identifier  260  can identify the separation between the seeds and residue particles in the image, as indicated by block  320 . Distribution correlation system  266  can correlate the seed and residue distributions and locations, as indicated by block  322 . Impact quantification system  268  then generates an output quantifying the impact of the residue particles on seed development, as indicated by block  324 . The characteristics of the seeds and residue particles in the image can be identified in other ways, across images, through aggregations, or in other ways, as indicated by block  326 . 
     Seed/residue characteristic identifier system  218  generates an output indicative of the seed/residue characteristics, as indicated by block  328  in the flow diagram of  FIG. 7 . Based upon the seed/residue characteristics, control action identifier  222  identifies actions to be taken based upon those characteristics, as indicated by block  330 . Control action identifier  222  can access data store  164 , based upon the identified seed/residue characteristics. For instance, control action identifier  222  can access seed/residue characteristic-to-action mappings  190  which map different seed/residue characteristics to actions that are to be taken. Accessing the characteristic-to-action mappings  190  is indicated by block  332  in the flow diagram of  FIG. 7 . 
     In another example, control action identifier  222  can access a seed/residue characteristic-to-action model  192  that takes, as an input, the identified seed/residue characteristics and generates, as an output, an action indicator identifying an action to be taken in response to the identified seed/residue characteristics. Accessing a characteristic-to-action model is indicated by block  334  in the flow diagram of  FIG. 7 . Control action identifier  222  can identify actions to take, based upon the seed/residue characteristics, as well as others, as indicated by block  336 . 
     Action signal generator  224  then generates an action signal to control a controllable subsystem  172  or another item on agricultural machine  100  to perform the identified action that was identified by control action identifier  222 . Generating an action signal to control a controllable subsystem to perform the identified action is indicated by block  338  in the flow diagram of  FIG. 7 . 
     The actions to be performed can be any of a variety of different actions based upon the seed/residue characteristics identified, based upon the particular machines being used, based upon weather conditions, or based upon the quantified impact of the residue on seed development, and/or based upon a wide variety of other criteria. For example, seed meter motor controller  234  and/or delivery system motor controller  236  can generate control signals to control meter motor  115  and/or delivery motor  117  to control the placement of seed in the furrow, relative to identified residue particles. As an example, the residue particles can be identified in or near the furrow prior to the seed being placed in the furrow, and motors  115  and  117  can be controlled to expedite seed delivery or delay seed delivery, in order to deliver the seed earlier or later in the furrow, at a position that avoids close proximity to identified residue particles. Controlling seed placement by controlling seed meter motor  115  and/or delivery system motor  117  is indicated by block  340  in the flow diagram of  FIG. 7 . 
     In another example, action signal generator  224  can generate an action signal to control a residue manipulator that manipulates residue within the furrow, such as a residue clearing mechanism or another manipulator. Generating a control signal to manipulate residue in the furrow is indicated by block  342  in the flow diagram of  FIG. 7 . 
     When a downforce system  252  is deployed to control the downforce on cleaning system  118 , cleaner downforce controller  228  can generate control signals to control the downforce generated by downforce system  252 . Controlling the cleaner downforce is indicated by block  344  in the flow diagram of  FIG. 7 . 
     Height controller  230  can also generate control signals to control height control system  254  which, in turn, controls the height of cleaning system  118  relative to the frame of the row unit or relative to the ground or relative to another point. Controlling the height of the row cleaner relative to the frame, relative to the ground, etc., is indicated by block  346  in the flow diagram of  FIG. 7 . 
     In another example, operator interface controller  232  controls operator interface mechanisms  174  to communicate with operator  178 . The communication can be in the form of an alert, a representative image showing residue and seed, a qualitative or quantitative indicator showing the quality of the seed/residue characteristics or the quantification of the impact that the residue particles will have on seed development, recommendations based on identified seed/residue characteristics, or other things. The communications to the operator may also indicate automatic control actions that have been automatically performed in response to the seed/residue characteristics. For instance, the communication may be an indication to operator  178  that indicates that the height or downforce on row cleaner  118  has been adjusted. Controlling the operator interface mechanisms  174  to communicate with operator  178  is indicated by block  348  in the flow diagram of  FIG. 7 . 
     Where the agricultural machine  100  is implemented with a substance delivery subsystem  244  that delivers another subsystem, action signal generator  224  can generate control signals to control subsystem  244  to control substance delivery (such as to control the delivery of fertilizer, herbicide, a chemical that enhances residue deterioration, and/or other substances). Generating control signals to control substance delivery is indicated by block  350  in the flow diagram of  FIG. 7 . Other action signals can be generated to control other controllable subsystems as well, as indicated by block  352 . 
     At some point, it may be that operator  178  provides an input that can be used by machine learning system  220  to perform machine learning on any of the items in image processing system  168 , data store  164 , or control system  170 . For instance, operator  178  may reverse the action or amplify the action that was automatically taken. Similarly, operator  178  may take a recommended action that is recommended by the control system  170  through an operator interface message or dismiss that recommendation. All of this information can be detected by user interface mechanisms  174  and provided to machine learning system  220 . Detecting any user interactions is indicated by block  354  in the flow diagram of  FIG. 7  and performing machine learning is indicated by block  356 . 
     Communication system controller  232  can also control communication system  162  to transmit any desired information about the seed/residue characteristics, the actions taken, the control signals generated, etc., to remote computing systems  182  over network  180 . Sending results to the remote computing systems  182  is indicated by block  358  in the flow diagram of  FIG. 7 . 
     Capturing images, processing them, and generating control signals can be continued until the operation being performed by agricultural machine  100  is complete. Continuing the processing until the operation is complete is indicated by block  360  in the flow diagram of  FIG. 7 . 
     It can thus be seen that the present description identifies characteristics of seed and residue in images and uses those characteristics to quantify the impact of residue on seed development. The present description also generates control signals based upon the characteristics and quantified impact. 
     The present discussion has mentioned processors and servers. In one example, the processors and servers include computer processors with associated memory and timing circuitry, not separately shown. They are functional parts of the systems or devices to which they belong and are activated by and facilitate the functionality of the other components or items in those systems. 
       FIG. 8  is a block diagram of agricultural machine  100 , shown in  FIGS. 1-5 , except that it communicates with elements in a remote server architecture  700 . In an example, remote server architecture  700  can provide computation, software, data access, and storage services that do not require end-user knowledge of the physical location or configuration of the system that delivers the services. In various examples, remote servers can deliver the services over a wide area network, such as the internet, using appropriate protocols. For instance, remote servers can deliver applications over a wide area network and they can be accessed through a web browser or any other computing component. Software or components shown in  FIGS. 1-5  as well as the corresponding data, can be stored on servers at a remote location. The computing resources in a remote server environment can be consolidated at a remote data center location or they can be dispersed. Remote server infrastructures can deliver services through shared data centers, even though they appear as a single point of access for the user. Thus, the components and functions described herein can be provided from a remote server at a remote location using a remote server architecture. Alternatively, they can be provided from a conventional server, or they can be installed on client devices directly, or in other ways. 
     In the example shown in  FIG. 8 , some items are similar to those shown in  FIG. 5  and they are similarly numbered.  FIG. 8  specifically shows that remote computing system  182 , image processing system  168 , and/or control system  170  can be located at a remote server location  702 . Therefore, agricultural machine  100  and operator  178  access those systems through remote server location  702 . 
       FIG. 8  also depicts another example in which remote user  184  uses a user device  706  to access remote computing system(s) in remote server location  702 . Also,  FIG. 8  shows an example of a remote server architecture in which it is also contemplated that some elements of  FIG. 5  are disposed at remote server location  702  while others are not. By way of example, data store  164 , which can comprise a third-party system, can be disposed at a location separate from location  702  and accessed through the remote server at location  702 . Regardless of where they are located, they can be accessed directly by agricultural machine  100  and/or operator  178 , as well as by remote user  184  (via user device  706 ) through a network (either a wide area network or a local area network), they can be hosted at a remote site by a service, or they can be provided as a service, or accessed by a connection service that resides in a remote location. Also, the data can be stored in substantially any location and intermittently accessed by, or forwarded to, interested parties. For instance, physical carriers can be used instead of, or in addition to, electromagnetic wave carriers. In such an example, where cell coverage is poor or nonexistent, another mobile machine (such as a fuel truck) can have an automated information collection system. As the agricultural machine  100  comes close to the fuel truck for fueling, the system automatically collects the information from the agricultural machine  100  using any type of ad-hoc wireless connection. The collected information can then be forwarded to the main network as the fuel truck reaches a location where there is cellular coverage (or other wireless coverage). For instance, the fuel truck may enter a covered location when traveling to fuel other machines or when at a main fuel storage location. All of these architectures are contemplated herein. Further, the information can be stored on the agricultural machine  100  until the agricultural machine  100  enters a covered location. The agricultural machine  100 , itself, can then send the information to the main network. 
     It will also be noted that the elements of  FIG. 5 , or portions of them, can be disposed on a wide variety of different devices. Some of those devices include servers, desktop computers, laptop computers, tablet computers, or other mobile devices, such as palm top computers, cell phones, smart phones, multimedia players, personal digital assistants, etc. 
       FIG. 9  is a simplified block diagram of one illustrative example of a handheld or mobile computing device that can be used as a user&#39;s or client&#39;s handheld device  16 , in which the present system (or parts of it) can be deployed. For instance, a mobile device can be deployed in the operator compartment of agricultural machine  100  for use in generating, processing, or displaying data.  FIGS. 10-11  are examples of handheld or mobile devices. 
       FIG. 9  provides a general block diagram of the components of a client device  16  that can run some components shown in  FIG. 5 , that interacts with them, or both. In the device  16 , a communications link  13  is provided that allows the handheld device to communicate with other computing devices and in some examples provides a channel for receiving information automatically, such as by scanning. Examples of communications link  13  include allowing communication through one or more communication protocols, such as wireless services used to provide cellular access to a network, as well as protocols that provide local wireless connections to networks. 
     In other examples, applications can be received on a removable Secure Digital (SD) card that is connected to an interface  15 . Interface  15  and communication links  13  communicate with a processor  17  (which can also embody processor(s)/server(s) from  FIG. 5 ) along a bus  19  that is also connected to memory  21  and input/output (I/O) components  23 , as well as clock  25  and location system  27 . 
     VO components  23 , in one example, are provided to facilitate input and output operations. I/O components  23  for various examples of the device  16  can include input components such as buttons, touch sensors, optical sensors, microphones, touch screens, proximity sensors, accelerometers, orientation sensors and output components such as a display device, a speaker, and or a printer port. Other I/O components  23  can be used as well. 
     Clock  25  illustratively comprises a real time clock component that outputs a time and date. It can also, illustratively, provide timing functions for processor  17 . 
     Location system  27  illustratively includes a component that outputs a current geographical location of device  16 . This can include, for instance, a global positioning system (GPS) receiver, a LORAN system, a dead reckoning system, a cellular triangulation system, or other positioning system. It can also include, for example, mapping software or navigation software that generates desired maps, navigation routes and other geographic functions. 
     Memory  21  stores operating system  29 , network settings  31 , applications  33 , application configuration settings  35 , data store  37 , communication drivers  39 , and communication configuration settings  41 . Memory  21  can include all types of tangible volatile and non-volatile computer-readable memory devices. It can also include computer storage media (described below). Memory  21  stores computer readable instructions that, when executed by processor  17 , cause the processor to perform computer-implemented steps or functions according to the instructions. Processor  17  can be activated by other components to facilitate their functionality as well. 
       FIG. 10  shows one example in which device  16  is a tablet computer  800 . In  FIG. 10 , computer  800  is shown with user interface display screen  802 . Screen  802  can be a touch screen or a pen-enabled interface that receives inputs from a pen or stylus. It can also use an on-screen virtual keyboard. Of course, it might also be attached to a keyboard or other user input device through a suitable attachment mechanism, such as a wireless link or USB port, for instance. Computer  800  can also illustratively receive voice inputs as well. 
       FIG. 11  is similar to  FIG. 10  except that the phone is a smart phone  71 . Smart phone  71  has a touch sensitive display  73  that displays icons or tiles or other user input mechanisms  75 . Mechanisms  75  can be used by a user to run applications, make calls, perform data transfer operations, etc. In general, smart phone  71  is built on a mobile operating system and offers more advanced computing capability and connectivity than a feature phone. 
     Note that other forms of the devices  16  are possible. 
       FIG. 12  is one example of a computing environment in which elements of  FIG. 5 , or parts of it, (for example) can be deployed. With reference to  FIG. 12 , an example system for implementing some embodiments includes a general-purpose computing device in the form of a computer  910  programmed to generate as described above. Components of computer  910  may include, but are not limited to, a processing unit  920  (which can comprise processor(s)/server(s) from previous FIGS.), a system memory  930 , and a system bus  921  that couples various system components including the system memory to the processing unit  920 . The system bus  921  may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. Memory and programs described with respect to  FIG. 5  can be deployed in corresponding portions of  FIG. 12 . 
     Computer  910  typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer  910  and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media is different from, and does not include, a modulated data signal or carrier wave. It includes hardware storage media including both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computer  910 . Communication media may embody computer readable instructions, data structures, program modules or other data in a transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. 
     The system memory  930  includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM)  931  and random access memory (RAM)  932 . A basic input/output system  933  (BIOS), containing the basic routines that help to transfer information between elements within computer  910 , such as during start-up, is typically stored in ROM  931 . RAM  932  typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit  920 . By way of example, and not limitation,  FIG. 12  illustrates operating system  934 , application programs  935 , other program modules  936 , and program data  937 . 
     The computer  910  may also include other removable/non-removable volatile/nonvolatile computer storage media. By way of example only,  FIG. 12  illustrates a hard disk drive  941  that reads from or writes to non-removable, nonvolatile magnetic media, nonvolatile magnetic disk  952 , an optical disk drive  955 , and nonvolatile optical disk  956 . The hard disk drive  941  is typically connected to the system bus  921  through a non-removable memory interface such as interface  940 , and optical disk drive  955  are typically connected to the system bus  921  by a removable memory interface, such as interface  950 . 
     Alternatively, or in addition, the functionality described herein can be performed, at least in part, by one or more hardware logic components. For example, and without limitation, illustrative types of hardware logic components that can be used include Field-programmable Gate Arrays (FPGAs), Application-specific Integrated Circuits (e.g., ASICs), Application-specific Standard Products (e.g., ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), etc. 
     The drives and their associated computer storage media discussed above and illustrated in  FIG. 12 , provide storage of computer readable instructions, data structures, program modules and other data for the computer  910 . In  FIG. 12 , for example, hard disk drive  941  is illustrated as storing operating system  944 , application programs  945 , other program modules  946 , and program data  947 . Note that these components can either be the same as or different from operating system  934 , application programs  935 , other program modules  936 , and program data  937 . 
     A user may enter commands and information into the computer  910  through input devices such as a keyboard  962 , a microphone  963 , and a pointing device  961 , such as a mouse, trackball or touch pad. Other input devices (not shown) may include a joystick, game pad, satellite dish, scanner, or the like. These and other input devices are often connected to the processing unit  920  through a user input interface  960  that is coupled to the system bus but may be connected by other interface and bus structures. A visual display  991  or other type of display device is also connected to the system bus  921  via an interface, such as a video interface  990 . In addition to the monitor, computers may also include other peripheral output devices such as speakers  997  and printer  996 , which may be connected through an output peripheral interface  995 . 
     The computer  910  is operated in a networked environment using logical connections (such as a controller area network—CAN, local area network—LAN, or wide area network—WAN) to one or more remote computers, such as a remote computer  980 . 
     When used in a LAN networking environment, the computer  910  is connected to the LAN  971  through a network interface or adapter  970 . When used in a WAN networking environment, the computer  910  typically includes a modem  972  or other means for establishing communications over the WAN  973 , such as the Internet. In a networked environment, program modules may be stored in a remote memory storage device.  FIG. 12  illustrates, for example, that remote application programs  985  can reside on remote computer  980 . 
     It is noted while agricultural planting machines have been particularly discussed with respect to the examples described herein, other machines can also be implemented with said examples. Thus, the present disclosure is not limited to use of the systems and processes discussed with merely planting machines. They can be used with other machines as well, some of which are mentioned above. 
     Also, a number of user interface displays have been discussed. They can take a wide variety of different forms and can have a wide variety of different user actuatable input mechanisms disposed thereon. For instance, the user actuatable input mechanisms can be text boxes, check boxes, icons, links, drop-down menus, search boxes, etc. They can also be actuated in a wide variety of different ways. For instance, they can be actuated using a point and click device (such as a track ball or mouse). They can be actuated using hardware buttons, switches, a joystick or keyboard, thumb switches or thumb pads, etc. They can also be actuated using a virtual keyboard or other virtual actuators. In addition, where the screen on which they are displayed is a touch sensitive screen, they can be actuated using touch gestures. Also, where the device that displays them has speech recognition components, they can be actuated using speech commands. 
     A number of data stores have also been discussed. It will be noted the data stores can each be broken into multiple data stores. All can be local to the systems accessing them, all can be remote, or some can be local while others are remote. All of these configurations are contemplated herein. 
     Also, the figures show a number of blocks with functionality ascribed to each block. It will be noted that fewer blocks can be used so the functionality is performed by fewer components. Also, more blocks can be used with the functionality distributed among more components. 
     It will be noted that the above discussion has described a variety of different systems, components and/or logic. It will be appreciated that such systems, components and/or logic can be comprised of hardware items (such as processors and associated memory, or other processing components, some of which are described below) that perform the functions associated with those systems, components and/or logic. In addition, the systems, components and/or logic can be comprised of software that is loaded into a memory and is subsequently executed by a processor or server, or other computing component, as described below. The systems, components and/or logic can also be comprised of different combinations of hardware, software, firmware, etc., some examples of which are described below. These are only some examples of different structures that can be used to form the systems, components and/or logic described above. Other structures can be used as well. 
     It should also be noted that the different examples described herein can be combined in different ways. That is, parts of one or more examples can be combined with parts of one or more other examples. All of this is contemplated herein. 
     Example 1 is a control system for controlling an agricultural machine, the control system comprising: 
     an image processing system that obtains a representation of an image captured by an image sensor and that identifies residue and a seed on an agricultural surface in the captured image; 
     a seed/residue characteristic identifier system that identifies a characteristic of the identified residue; 
     an impact quantification system that generates a quantification indicator indicative of an impact of the identified residue on development of the seed based on the identified characteristic of the identified residue; and 
     an action signal generator that generates an action signal based on the quantification indicator. 
     Example 2 is the control system of any or all previous examples and further comprising: 
     a control action identifier configured to identify an action to be performed based on the quantification indicator, the action signal generator generating the action signal to perform the identified action. 
     Example 3 is the control system of any or all previous examples wherein the action identifier accesses a characteristic-to-action mapping to identify the action based on at least one of the identified characteristic of the identified residue and the quantification indicator. 
     Example 4 is the control system of any or all previous examples wherein the action identifier accesses a characteristic-to-action model to identify the action based on at least one of the identified characteristic of the identified residue and the quantification indicator. 
     Example 5 is the control system of any or all previous examples wherein the image processing system is configured to identify a location of the seed and the residue in the image and wherein the seed/residue characteristic comprises: 
     a seed/residue separation identifier that identifies a separation between seed and residue based on the location of the seed and residue and wherein the impact quantification system generates the quantification indicator based on the separation between the seed and the residue. 
     Example 6 is the control system of any or all previous examples wherein the seed/residue characteristic identifier system comprises: 
     a seed distribution identifier that identifies a distribution of seed based on the identified seed in the image; 
     a residue distribution identifier that identifies a distribution of residue based on the identified residue in the image; and 
     a distribution correlation system that correlates the distribution of seed to the distribution of residue and generates, as the identified characteristic, a correlation output indicative of the correlation of the distribution of seed to the distribution of residue. 
     Example 7 is the control system of any or all previous examples wherein the action signal generator comprises: 
     a height controller that generates, as the action signal, a height control signal that controls the height of a row cleaner on the agricultural machine relative to a frame of the agricultural machine based on the characteristic of the residue. 
     Example 8 is the control system of any or all previous examples wherein the action signal generator comprises: 
     a controller that generates, as the action signal, a seed placement signal that controls placement of seed on the agricultural surface based on the characteristic of the residue. 
     Example 9 is the control system of any or all previous examples wherein the action signal generator comprises: 
     a down force controller that generates, as the action signal, a down force control signal that controls the down force of a row cleaner on the agricultural machine based on the characteristic of the residue. 
     Example 10 is the control system of any or all previous examples wherein the action signal generator comprises: 
     a seed meter system controller that generates, as the action signal, a motor control signal that controls a seed meter motor based on the characteristic of the residue. 
     Example 11 is the control system of any or all previous examples wherein the action signal generator comprises: 
     a seed delivery system controller that generates, as the action signal, a motor control signal that controls a seed delivery motor based on the characteristic of the residue. 
     Example 12 is the control system of any or all previous examples wherein the action signal generator comprises: 
     an operator interface controller that generates, as the action signal, an operator interface control signal that controls an operator interface mechanism based on the characteristic of the residue. 
     Example 13 is the control system of any or all previous examples wherein the action signal generator comprises: 
     a communication system controller that generates, as the action signal, a communication system control signal that controls a communication system to send an indication of the quantification indicator and the characteristic of the residue to a remote computing system. 
     Example 14 is an agricultural machine, comprising: 
     a frame; 
     a row cleaner coupled to the frame; 
     a furrow opener coupled to the frame that opens a furrow in an agricultural surface over which the agricultural machine travels; 
     a seed delivery system that delivers seed to the furrow; 
     an image sensor configured to capture an image of the agricultural surface; 
     an image processing system that obtains a representation of an image captured by an image sensor and that identifies residue and a seed on an agricultural surface in the captured image; 
     a seed/residue characteristic identifier system that identifies a characteristic of the identified residue; 
     an impact quantification system that generates a quantification indicator indicative of an impact of the identified residue on development of the seed based on the identified characteristic of the identified residue; and 
     an action signal generator that generates an action signal based on the quantification indicator. 
     Example 15 is the agricultural machine of any or all previous examples and further comprising: 
     a control action identifier configured to identify an action to be performed based on the quantification indicator, by accessing characteristic-to-action information to identify the action based on at least one of the identified characteristic of the identified residue and the quantification indicator, the action signal generator generating the action signal to perform the identified action. 
     Example 16 is the agricultural machine of any or all previous examples wherein the image processing system is configured to identify a location of the seed and the residue in the image and wherein the seed/residue characteristic comprises: 
     a seed/residue separation identifier that identifies a separation between seed and residue based on the location of the seed and residue and wherein the impact quantification system generates the quantification indicator based on the separation between the seed and the residue. 
     Example 17 is the agricultural machine of any or all previous examples wherein the seed/residue characteristic identifier system comprises: 
     a seed distribution identifier that identifies a distribution of seed based on the identified seed in the image; 
     a residue distribution identifier that identifies a distribution of residue based on the identified residue in the image; and 
     a distribution correlation system that correlates the distribution of seed to the distribution of residue and generates, as the identified characteristic, a correlation output indicative of the correlation of the distribution of seed to the distribution of residue. 
     Example 18 is the agricultural machine of any or all previous examples wherein the action signal generator comprises: 
     a communication system controller that generates, as the action signal, a communication system control signal that controls a communication system to send an indication of the quantification indicator and the characteristic of the residue to a remote computing system. 
     Example 19 is a method of controlling an agricultural machine, the method comprising: 
     obtaining a representation of an image captured by an image sensor; 
     identifying residue and a seed on an agricultural surface in the captured image; 
     identifying a characteristic of the identified residue; 
     generating a quantification indicator indicative of an impact of the identified residue on development of the seed based on the identified characteristic of the identified residue; and 
     generating an action signal based on the quantification indicator. 
     Example 20 is the method of any or all previous examples wherein identifying residue and a seed comprises: 
     identifying a location of the seed and the residue in the image and wherein identifying the residue characteristic comprises identifying a separation between the seed and the residue based on the location of the seed and the residue and wherein generating a quantification indicator comprises generating the quantification indicator based on the separation between the seed and the residue. 
     Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.