Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-6, 9, 10, 18, 22, and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Kordick (US 20170273235 A1), in view of Landphair (US 20120046838 A1), and in view of Chen (Sugarcane Stem Node Recognition in Field by Deep Learning Combining Data Expansion | MDPI).
Regarding Claim 1,
Disclosure by Kordick
Kordick discloses:
A system for measuring crop seed rate
See at least:
“a seeding system having a controller that drives a variable speed electric motor, reads a motor shaft speed sensor for measuring the seed application rate” ([0018]);
“a seeding system which communicates with a tractor network to provide monitoring and calibration options for variable seed planting rate” ([0018]);
“a variable rate air seeding system” ([0018]).
Rationale: These summary disclosures expressly teach a seeding system directed to measuring seed application/planting rate. Kordick is the strongest of the cited references for the crop-seed-rate aspect of the claim.
of a planting machine
See at least:
“an air seed planter” ([0003]);
“Many different types of air seeders are used for farming in planting crops” ([0005]);
“an air seed planter capable of dispensing seeds at a variable rate” ([0014]).
Rationale: Kordick expressly discloses a planting machine.
the system comprising:
See at least:
“An air seeding system for use on a planter having a plurality of row units includes a seed meter associated with each row unit, and variable speed electric motors operatively connected to the seed meters” ([0030]);
“The system includes one or more controllers” ([0061]).
Rationale: Kordick expressly discloses a multi-component planting system.
one or more electronic controllers
See at least:
“The system includes one or more controllers to provide variable seed rate control” ([0061]).
Rationale: This expressly discloses one or more electronic controllers.
and the planting machine,
See at least:
“The controller 50 may be a computer or microprocessor ... receive signals from other components or devices ... a speed sensor 52 for deriving in real-time over-the-ground velocity of the planter” ([0070]).
Rationale: The controller is expressly operatively connected with planter components and devices, thus disclosing communication with the planting machine.
where the electronic controllers are configured to:
See at least:
“The controller utilizes an algorithm to determine seed population and adjust the motor speed” ([0071]);
“The system includes one or more controllers to provide variable seed rate control” ([0061]).
Rationale: Kordick expressly discloses controller-performed functionality relevant to planting-rate determination and control.
determine a speed associated with the planting machine,
See at least:
“a seeding system having sensors for measuring ground speed of the seeder” ([0018]);
“a speed sensor 52 for deriving in real-time over-the-ground velocity of the planter” ([0070]).
Rationale: This expressly discloses determining planter speed.
determine a current crop seed rate of the planting machine
See at least:
“reads a motor shaft speed sensor for measuring the seed application rate” ([0018]);
“The controller utilizes an algorithm to determine seed population” ([0071]).
Rationale: Kordick expressly teaches measuring seed application rate and determining seed population, which supports determining a current crop seed rate.
and the speed of the planting machine,
See at least:
“ground speed from a purely inertial navigation system ... Parameters such as implement or vehicle ground speed can be obtained. The controller can utilize the data ... relative to ground speed” ([0056]).
Rationale: Kordick expressly discloses use of planting-machine speed in controller calculations.
and output one or more recommended operating conditions to the planting machine
See at least:
“The controller can be connected to a user interface that can allow manual adjustment of on/off states and/or motor speed” ([0055]);
“provide monitoring and calibration options for variable seed planting rate” ([0018]);
“the seed population can be adjusted by the operator as the planter moves through the field” ([0017]).
Rationale: Kordick expressly discloses interface-based presentation of selectable operating settings tied to seeding rate. Although Kordick also teaches direct control, the disclosed monitoring/calibration/user-adjustment architecture renders obvious outputting recommended operating conditions.
based at least in part on the determined crop seed rate.
See at least:
“measuring the seed application rate” ([0018]);
“The controller utilizes an algorithm to determine seed population and adjust the motor speed ... to meet the desired population” ([0071]).
Rationale: Kordick expressly ties operating output and motor-speed adjustment to determined planting-rate/population information.
Claim Limitations Not Explicitly Disclosed by Kordick
Kordick does not explicitly disclose the following claim limitations:
configured to plant a crop material having at least one of nodes and eyes,
a camera
having a first field of view
through which crop material may pass; and
in operable communication with the camera
receive image data from the camera,
determine at least one of a number of nodes and a numbers of eyes in the field of view,
based at least in part the determined value of the at least one of the number of nodes and the number of eyes in the field of view
Disclosure by Landphair
Landphair discloses:
a camera
See at least:
“detector 42 can be configured as a video camera” ([0031]).
Rationale: Landphair expressly discloses a camera.
having a first field of view
See at least:
“the video camera ... arranged to view the furrow between furrow opener 28 and closing wheels 34” ([0031]).
Rationale: The arranged viewed region expressly supports a field of view.
through which crop material may pass; and
See at least:
“the video camera can see seeds passing beneath the camera” ([0031]);
“detect when a seed passes a predetermined point on the image” ([0032]).
Rationale: This expressly discloses crop material passing through the camera's viewed region.
in operable communication with the camera
See at least:
“The image viewed by the camera is transmitted to processor 16A” ([0031]).
Rationale: Transmission of image data to the processor expressly establishes operable communication with the camera.
receive image data from the camera,
See at least:
“The image viewed by the camera is transmitted to processor 16A” ([0031]).
Rationale: This expressly discloses receiving image data from the camera.
Motivation to Combine Kordick and Landphair
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick and Landphair before them, to incorporate Landphair's planter-mounted video-camera and image-receipt arrangement into Kordick's controller-based variable-rate planting system so that image-derived crop-material information could be gathered in real time and used together with Kordick's rate and speed logic. This combination is supported by technical compatibility and predictable use of known elements because Kordick provides the rate/speed/output backbone while Landphair provides a known planter-camera/FOV/image-data acquisition arrangement for moving crop material in a planter environment.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick and Landphair
After combining the teachings of Kordick and Landphair, the following claim limitations are not explicitly disclosed:
configured to plant a crop material having at least one of nodes and eyes,
determine at least one of a number of nodes and a numbers of eyes in the field of view,
based at least in part the determined value of the at least one of the number of nodes and the number of eyes in the field of view
Disclosure by Chen
Chen discloses:
configured to plant a crop material having at least one of nodes and eyes,
See at least:
“The area occupied by sugarcane planting in China ranks third in the world” (Abstract/Introduction);
“the mechanical harvesting destroys the stem nodes kept in the soil for the second year of growth” (Introduction);
“the sugarcane was grown in the open air and planted side by side according to the requirements for mechanical harvesting” (2.1 Image Data Acquisition).
Rationale: Chen expressly concerns sugarcane planting and sugarcane stem nodes. Chen does not use the term "eyes," but it expressly supplies node-bearing sugarcane crop material in a planting context.
determine at least one of a number of nodes and a numbers of eyes in the field of view,
See at least:
“an object detection algorithm based on deep learning was proposed for sugarcane stem node recognition” (Abstract);
“The image set collected was composed of images of one single sugarcane stem node and images of multiple sugarcane stem nodes” (2.1 Image Data Acquisition);
“the object detection algorithm based on deep learning can learn and understand the characteristics of different sugarcane stem nodes” (Introduction).
Rationale: Chen expressly teaches image-based recognition/detection of sugarcane stem nodes, including images containing multiple stem nodes. Although Chen does not literally recite a numeric count or the term "eyes," once node instances are detected in single-node and multiple-node images, determining the number of detected node instances in the field of view would have been a routine, predictable post-detection operation for a PHOSITA.
based at least in part the determined value of the at least one of the number of nodes and the number of eyes in the field of view
See at least:
Chen's node-detection teaching above, together with Kordick's “The controller utilizes an algorithm to determine seed population” ([0071]) and “ground speed ... can be obtained. The controller can utilize the data ... relative to ground speed” ([0056]).
Rationale: Chen supplies the image-derived node value, and Kordick supplies the rate-calculation framework that uses sensed planting information together with speed. A PHOSITA would have found it obvious to use image-derived sugarcane-node information as an agronomically relevant input to Kordick's planting-rate determination because node-bearing sugarcane material directly affects effective planting value.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to modify Kordick's controller-based variable-rate planting system, as enhanced with Landphair's planter-camera and image-receipt arrangement, to further analyze sugarcane crop material for stem-node content as taught by Chen, so that image-derived node information could be used with planting-machine speed to determine crop seed rate and provide corresponding operating conditions. This combination is supported by complementary teachings and predictable use of known elements: Kordick provides the rate/speed/output-control backbone, Landphair provides the moving planter-camera environment and receipt of image data, and Chen provides image-based recognition of sugarcane stem nodes, including multiple-node images, in an agricultural machine-vision context.
Regarding Claim 3,
The combination of Kordick, Landphair, and Chen establishes the system of Claim 1, which is the basis for Claim 3.
Disclosure by Kordick
Kordick discloses:
wherein the one or more electronic controllers compare the current crop seed rate
See at least:
"a seeding system having a controller that drives a variable speed electric motor, reads a motor shaft speed sensor for measuring the seed application rate" ([0018]);
"The controller utilizes an algorithm to determine seed population and adjust the motor speed" ([0071]).
Rationale: These disclosures expressly teach that the controller measures the present seed application rate / seed population and uses that measured current value in control logic. Thus, Kordick discloses the controller side of comparing the current crop seed rate.
to a target crop seed rate
See at least:
"Still another objective of the present invention is a provision of a seed planter wherein the seed population can be adjusted by the operator as the planter moves through the field" ([0017]);
"The user selects a target seeding rate through the display interface and communicates this to the Falcon controllers which control the variable speed motors to achieve this rate" ([0075]).
Rationale: Kordick expressly discloses a target crop seed rate in the form of a user-selected target seeding rate / desired population.
to determine a crop seed rate difference,
See at least:
"The controller utilizes an algorithm to determine seed population and adjust the motor speed ... to meet the desired population" ([0071]);
"The user selects a target seeding rate through the display interface ... to achieve this rate" ([0075]).
Rationale: Kordick does not use the exact words "crop seed rate difference," but that comparison is implicit in the disclosed control scheme. A controller that measures current seed application rate / seed population and adjusts motor speed to meet a user-selected target seeding rate necessarily compares current rate to target rate and determines whether a difference exists so corrective action can be taken. That is a routine and inherent control-theory operation, and thus this limitation is rendered obvious, if not expressly disclosed, by Kordick's closed-loop variable-rate control teaching.
and wherein the one or more electronic controllers output the one or more recommended operating conditions
See at least:
"The controller can be connected to a user interface that can allow manual adjustment of on/off states and/or motor speed" ([0055]);
"a seeding system which communicates with a tractor network to provide monitoring and calibration options for variable seed planting rate" ([0018]);
"The user selects a target seeding rate through the display interface" ([0075]).
Rationale: Kordick expressly discloses controller/interface output tied to operating settings, including motor speed and calibration options. Although Kordick is stronger on selectable settings and direct control than on a pure advisory recommendation, outputting recommended operating conditions is an obvious variant of the expressly disclosed monitoring/interface architecture.
based at least in part on the crop seed rate difference.
See at least:
"The controller utilizes an algorithm to determine seed population and adjust the motor speed ... to meet the desired population" ([0071]);
"The user selects a target seeding rate ... to achieve this rate" ([0075]).
Rationale: Kordick's control logic necessarily bases the output operating condition on the difference between the current measured seed population/rate and the desired target population/rate. Otherwise, there would be no basis for the controller to adjust motor speed to meet the target. Thus, this limitation is at least inherently disclosed and rendered obvious by Kordick's variable-rate feedback/control teaching.
Motivation for the combination of Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to implement Kordick's target-rate and feedback-control logic in the Claim 1 system established by those references so that the controller would compare a measured current crop seed rate to a target crop seed rate, determine the resulting difference, and output corresponding operating conditions. This would have been a predictable use of known closed-loop planter control techniques to improve accuracy, control, and planting performance.
Regarding Claim 4,
The combination of Kordick, Landphair, and Chen establishes the system of Claim 1, which is the basis for Claim 4.
Disclosure by Kordick
Kordick discloses:
wherein the one or more controllers have memory,
See at least:
"The Falcon controller also has internal memory that can be used for storing application specific data logs and/or ISOBUS UT graphics/screens." ([0082])
Rationale: Kordick expressly discloses that the controller has internal memory. This limitation is expressly disclosed.
wherein the one or more controllers store past crop seed rate data in the memory,
See at least:
"The Falcon controller also has internal memory that can be used for storing application specific data logs and/or ISOBUS UT graphics/screens." ([0082]);
"reads a motor shaft speed sensor for measuring the seed application rate" ([0018]);
"a seeding system which communicates with a tractor network to provide monitoring and calibration options for variable seed planting rate" ([0018])
Rationale: Kordick does not verbatim state that the stored data logs are "past crop seed rate data." However, Kordick expressly discloses internal memory for storing application-specific data logs in a variable seed planting rate system that measures seed application rate. A PHOSITA would have understood it to be obvious that such application-specific data logs would include historical rate-related operating data, including past crop-seed-rate-related data, because storing historical operating data for monitoring, calibration, and control is a routine use of controller memory in closed-loop variable-rate planting systems.
and wherein the one or more controllers determine the current crop seed rate
See at least:
"reads a motor shaft speed sensor for measuring the seed application rate" ([0018]);
"The controller utilizes an algorithm to determine seed population" ([0071])
Rationale: Kordick expressly discloses determining current seed application rate / seed population. This limitation is expressly disclosed.
based at least in part on the past crop seed rate data.
See at least:
"The Falcon controller also has internal memory that can be used for storing application specific data logs" ([0082]);
"The controller utilizes an algorithm to determine seed population" ([0071]);
"provide monitoring and calibration options for variable seed planting rate" ([0018])
Rationale: Kordick does not verbatim state that the current crop seed rate is determined based on past crop seed rate data. However, given Kordick's express disclosure of internal memory storing application-specific data logs, current seed-rate determination, and monitoring/calibration options for variable seed planting rate, it would have been obvious to a PHOSITA that previously stored historical rate-related data could be used as part of current rate determination, calibration, smoothing, or control refinement. That is a predictable use of stored historical operating data in a variable-rate planter controller.
Motivation for the combination of Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to implement Kordick's disclosed controller memory and application-specific data logging in the Claim 1 system established by those references so that historical crop-seed-rate-related data could be retained and used as part of current crop seed rate determination, because doing so would have predictably improved monitoring, calibration, stability, and control in a variable-rate planting system.
Regarding Claim 5,
The combination of Kordick, Landphair, and Chen establishes the system of Claim 1, which is the basis for Claim 5.
Disclosure by Kordick
Kordick discloses:
wherein outputting one or more recommended operating conditions to the planting machine
See at least:
"a seeding system which communicates with a tractor network to provide monitoring and calibration options for variable seed planting rate" ([0018]);
"The controller can be connected to a user interface that can allow manual adjustment of on/off states and/or motor speed" ([0055]);
"The user selects a target seeding rate through the display interface" ([0075]).
Rationale: Kordick expressly discloses controller/interface-based output of operating settings, calibration options, and adjustable planting parameters. Thus, Kordick expressly supports outputting operating conditions to the planting machine.
Claim Limitations Not Explicitly Disclosed by Kordick
Kordick does not explicitly disclose the following claim limitation:
includes outputting a suggested travel speed.
Disclosure by Landphair
Landphair discloses:
includes outputting a suggested travel speed.
See at least:
"The time between detecting adjacent seeds and the planter travel speed is used to calculate the seed spacing" ([0010]);
"Ground speed sensor 19 ... provides an output signal ... representative of the speed" ([0022]);
"With planter speed information, the distance between seeds is determined" ([0031]).
Rationale: Landphair expressly discloses planter travel speed as a key planting-performance variable used by the controller/processor to determine planting output. Kordick expressly discloses interface-based output of operating settings and calibration options. Given those teachings together, it would have been obvious to a PHOSITA that, when outputting recommended operating conditions in such a planter-control system, one obvious recommended operating condition would be planter travel speed, because Landphair shows that planter travel speed directly affects planting performance and Kordick shows that the system outputs adjustable operating conditions through a controller/interface architecture. Thus, while "suggested travel speed" is not verbatim disclosed, it is an obvious and predictable form of recommended operating condition arising from the combined teachings.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to retain the Kordick-plus-Landphair operating-condition/output combination in the Claim 1 system that further includes Chen's sugarcane-node-recognition teaching, because Chen does not detract from and would remain technically compatible with the use of suggested travel speed as an operator-facing operating condition in the combined planting system.
Regarding Claim 6,
The combination of Kordick, Landphair, and Chen establishes the system of Claim 1, which is the basis for Claim 6.
Disclosure by Kordick
Kordick discloses:
wherein the one or more electronic controllers collect location data
See at least:
"With improvements in precision farming and the use of GPS, accurate planting is critical for improving yield and minimizing cost." ([0007]);
"a positioning and/or inertial sensor 54 may be connected to the controller 50. Examples include a global navigation satellite system (GNSS), or inertial navigation system or sensors" ([0070]).
Rationale: Kordick expressly discloses controller-connected positioning sensors, including GPS/GNSS and inertial systems. Those teachings expressly support collection of location data by the controller.
associated with a path the planter traverses in a defined area, and
See at least:
"ground speed from a navigation system such as GNSS or inertial, or a combination of the two" ([0032]);
"Parameters such as implement or vehicle ground speed can be obtained. The controller can utilize the data or measurements from the navigation system and/or the motor relative to ground speed" ([0056]);
"the seed population can be adjusted by the operator as the planter moves through the field" ([0017]).
Rationale: Kordick expressly discloses navigation-based position/speed information tied to planter movement through the field. A PHOSITA would have understood such GNSS/inertial location data to be associated with the planter's traversed path within the field, i.e., a defined planting area. This limitation is therefore at least implicit and PHOSITA-obvious from Kordick's precision-farming/navigation teachings.
generates an overlay for a map of the defined area
See at least:
"Another example would be to adjust distribution rate based on reference to a field map through a precision farming system." ([0032]).
Rationale: Kordick expressly discloses controller operation with reference to a field map through a precision farming system. While Kordick does not verbatim say "generates an overlay," a PHOSITA would have understood that once controller-collected location and rate information are used with a field map in a precision-farming system, displaying or generating a map overlay is a routine and predictable implementation for presenting georeferenced operational data on the field map. Thus, this limitation is rendered obvious by Kordick's express field-map teaching.
based on the location data,
See at least:
"a positioning and/or inertial sensor 54 may be connected to the controller 50. Examples include a global navigation satellite system (GNSS)" ([0070]);
"adjust distribution rate based on reference to a field map through a precision farming system" ([0032]).
Rationale: Kordick expressly discloses positioning data and field-map-based control. A PHOSITA would have understood any field-map overlay or map-based display/control to be based at least in part on the location data from the positioning system.
the crop feed rate of the planting machine,
See at least:
"a seeding system having a controller that drives a variable speed electric motor, reads a motor shaft speed sensor for measuring the seed application rate" ([0018]);
"a seeding system which communicates with a tractor network to provide monitoring and calibration options for variable seed planting rate" ([0018]).
Rationale: Kordick expressly discloses seed application rate / variable seed planting rate, which is strong support for crop feed rate of the planting machine.
Claim Limitations Not Explicitly Disclosed by Kordick
Kordick does not explicitly disclose the following claim limitation:
and the amount of nodes.
Disclosure by Chen
Chen discloses:
and the amount of nodes.
See at least:
"an object detection algorithm based on deep learning was proposed for sugarcane stem node recognition" (Abstract);
"The image set collected was composed of images of one single sugarcane stem node and images of multiple sugarcane stem nodes" (Section 2.1);
"the object detection algorithm based on deep learning can learn and understand the characteristics of different sugarcane stem nodes" (Introduction/Section 1).
Rationale: Chen expressly discloses image-based recognition of sugarcane stem nodes, including images containing single and multiple stem nodes. Although Chen does not literally recite "amount of nodes," once node instances are detected in images containing multiple nodes, determining the amount of nodes is a routine and predictable post-detection computation for a PHOSITA. Thus, this limitation is at least implicitly disclosed and rendered obvious by Chen.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Chen, and Landphair before them, to retain Landphair's planter-camera environment within the Claim 1 system while implementing Kordick's location-data / field-map precision-farming framework and Chen's node-recognition teaching, because Landphair remains technically compatible with the combined system and reinforces the use of image-derived crop-material information in a planter context.
Regarding Claim 9,
Disclosure by Kordick
Kordick teaches:
A method for measuring seed feed rate
See at least:
"A seed planting method of the present invention dispenses the seeds on an air seeder and utilizes variable speed electric motors to control the dispensement rate of the seeds. The method provides field data to a controller connected to the electric motors, and adjusts the speed of the electric motor based on the field data." ([0031]);
"a seeding system having a controller that drives a variable speed electric motor, reads a motor shaft speed sensor for measuring the seed application rate" ([0018]).
Rationale: These teachings expressly disclose a method and system centered on measuring and controlling seed application/dispensement rate, which corresponds to seed feed rate.
of a planting machine
See at least:
"an air seed planter capable of dispensing seeds at a variable rate" ([0014]);
"Many different types of air seeders are used for farming in planting crops" ([0005]).
Rationale: Kordick expressly teaches a planting machine.
the method comprising:
See at least:
"A seed planting method of the present invention" ([0031]).
Rationale: Kordick expressly teaches a method with multiple steps.
receiving a target seed feed rate from one of memory and the user;
See at least:
"The user selects a target seeding rate through the display interface and communicates this to the Falcon controllers" ([0075]);
"The Falcon controller also has internal memory that can be used for storing application specific data logs and/or ISOBUS UT graphics/screens." ([0082]).
Rationale: Kordick expressly teaches receiving a target seeding rate from the user through the display interface. Because the claim recites "from one of memory and the user," the user-based option is expressly satisfied.
determining a travel speed associated with the planting machine;
See at least:
"a speed sensor 52 for deriving in real-time over-the-ground velocity of the planter" ([0070]);
"a seeding system having sensors for measuring ground speed of the seeder" ([0018]).
Rationale: Kordick expressly teaches determining travel speed associated with the planting machine.
determining a current seed feed rate of the planting machine
See at least:
"reads a motor shaft speed sensor for measuring the seed application rate" ([0018]);
"The controller utilizes an algorithm to determine seed population" ([0071]).
Rationale: Kordick expressly teaches determining current seed application / feed rate.
transmitting one or more target operating conditions to the planting machine
See at least:
"The controller can be connected to a user interface that can allow manual adjustment of on/off states and/or motor speed" ([0055]);
"The user selects a target seeding rate through the display interface and communicates this to the Falcon controllers which control the variable speed motors to achieve this rate" ([0075]).
Rationale: Kordick expressly teaches communicating target operating settings through the display/controller architecture and transmitting those target settings to the planter control system.
based at least in part on the current seed feed rate
See at least:
"reads a motor shaft speed sensor for measuring the seed application rate" ([0018]);
"The controller utilizes an algorithm to determine seed population and adjust the motor speed" ([0071]).
Rationale: Kordick expressly teaches that operating outputs are based on current measured rate/seed population.
and the target seed feed rate.
See at least:
"The user selects a target seeding rate through the display interface ... to achieve this rate" ([0075]);
"The controller utilizes an algorithm to determine seed population and adjust the motor speed ... to meet the desired population" ([0071]).
Rationale: Kordick expressly teaches that the control output is also based on the target rate / desired population.
Claim Limitations Not Explicitly Disclosed by Kordick
Kordick does not explicitly teach the following claim limitations:
configured to plant a crop material having at least one of nodes and eyes,
receiving image data from a camera of the planting machine,
the image data including an image of a crop material in a target region of the planting machine;
determining at least one of a number of nodes and a number of eyes in the target region of the planter;
based on the determined value of the at least one of the number of nodes and the number of eyes in the target region
and the speed associated with the planting machine; and
Disclosure by Landphair
Landphair teaches:
receiving image data from a camera of the planting machine,
See at least:
"detector 42 can be configured as a video camera which is mounted to the row crop unit" ([0031]);
"The image viewed by the camera is transmitted to processor 16A" ([0031]).
Rationale: Landphair expressly teaches receiving image data from a camera of the planting machine.
the image data including an image of a crop material in a target region of the planting machine;
See at least:
"the video camera is mounted to the row crop unit and arranged to view the furrow between furrow opener 28 and closing wheels 34. There, the video camera can see seeds passing beneath the camera after being placed in the furrow" ([0031]).
Rationale: Landphair expressly teaches image data including an image of crop material in a specific planter region, namely the furrow region between the opener and closing wheels. That is a target region of the planting machine.
Motivation to Combine Kordick and Landphair
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick and Landphair before them, to incorporate Landphair's planter-mounted camera and image-receipt arrangement into Kordick's seed-feed-rate method so that image-derived crop-material information could be received in real time from a target region of the planting machine and used together with Kordick's rate and speed logic. This would have been a predictable use of known planter imaging to improve monitoring accuracy and control.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick and Landphair
After combining the teachings of Kordick and Landphair, the following claim limitations are not explicitly disclosed:
configured to plant a crop material having at least one of nodes and eyes,
determining at least one of a number of nodes and a number of eyes in the target region of the planter;
based on the determined value of the at least one of the number of nodes and the number of eyes in the target region
and the speed associated with the planting machine; and
Disclosure by Chen
Chen teaches:
configured to plant a crop material having at least one of nodes and eyes,
See at least:
"The area occupied by sugarcane planting in China ranks third in the world" (Introduction);
"the mechanical harvesting destroys the stem nodes kept in the soil for the second year of growth" (Introduction);
"the sugarcane was grown in the open air and planted side by side according to the requirements for mechanical harvesting" (Section 2.1).
Rationale: Chen expressly teaches sugarcane crop material in a planting context and expressly teaches stem nodes. Because the claim recites "at least one of nodes and eyes," the node-bearing crop-material requirement is satisfied.
determining at least one of a number of nodes and a number of eyes in the target region of the planter;
See at least:
"an object detection algorithm based on deep learning was proposed for sugarcane stem node recognition" (Abstract);
"The image set collected was composed of images of one single sugarcane stem node and images of multiple sugarcane stem nodes" (Section 2.1);
"The research shows that it is a feasible method for real-time detection of sugarcane stem nodes" (Abstract).
Rationale: Chen expressly teaches image-based detection/recognition of sugarcane stem nodes, including multiple stem nodes in images. Thus, determining a number of nodes in the imaged target region is at least implicit and PHOSITA-obvious once node instances are detected in single-node and multiple-node images.
based on the determined value of the at least one of the number of nodes and the number of eyes in the target region
See at least:
Chen's node-detection teaching above, together with Kordick's "The controller utilizes an algorithm to determine seed population" ([0071]).
Rationale: Chen supplies the image-derived node value, and Kordick supplies the seed-feed-rate determination framework. A PHOSITA would have found it obvious to use the detected node quantity from the imaged crop material as an agronomically relevant input to the seed-feed-rate determination, because node-bearing sugarcane material directly affects effective planting value.
and the speed associated with the planting machine; and
See at least:
"a speed sensor 52 for deriving in real-time over-the-ground velocity of the planter" ([0070]) in Kordick, together with Chen's node-detection teaching.
Rationale: Kordick expressly teaches the speed input, and Chen supplies the node-amount input. Using both together in the same determination is a predictable combination of sensed planting variables for calculating current seed feed rate.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to modify the Kordick method as enhanced with Landphair's planter-camera image receipt to further analyze sugarcane crop material for node content as taught by Chen, so that the current seed feed rate could be determined from both the detected node information in the target region and the planting-machine speed. This would have been a predictable use of known machine-vision-derived agronomic information to improve seed feed rate determination and planting control.
Regarding Claim 10,
The combination of Kordick, Landphair, and Chen establishes the method of Claim 9, which is the basis for Claim 10.
Disclosure by Kordick
Kordick teaches:
wherein transmitting one or more target operating conditions
See at least:
"The controller can be connected to a user interface that can allow manual adjustment of on/off states and/or motor speed" ([0055]);
"The user selects a target seeding rate through the display interface and communicates this to the Falcon controllers" ([0075]);
"a seeding system which communicates with a tractor network to provide monitoring and calibration options for variable seed planting rate" ([0018]).
Rationale: Kordick expressly teaches transmitting operating conditions/settings through the controller/display-interface architecture. This supports the portion of the limitation that concerns transmitting one or more target operating conditions.
Claim Limitations Not Explicitly Disclosed by Kordick
Kordick does not explicitly teach the following claim limitation:
includes transmitting a target travel speed.
Disclosure by Landphair
Landphair teaches:
includes transmitting a target travel speed.
See at least:
"The time between detecting adjacent seeds and the planter travel speed is used to calculate the seed spacing" ([0010]);
"Ground speed sensor 19 ... provides an output signal ... representative of the speed" ([0022]);
"With planter speed information, the distance between seeds is determined" ([0031]).
Rationale: Landphair expressly teaches planter travel speed as a key planting-performance variable used by the system in determining planting output. Kordick expressly teaches that target operating conditions are transmitted through the controller/interface architecture. Given those combined teachings, it would have been obvious to a PHOSITA that one such transmitted target operating condition could be a target travel speed, because Landphair shows that planter travel speed materially affects planting performance, and Kordick shows that target operating settings are communicated to achieve desired planting results. Thus, while "target travel speed" is not explicitly disclosed, it is an obvious and predictable transmitted target operating condition arising from the combined teachings.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to retain the Kordick-plus-Landphair target-operating-condition transmission in the Claim 9 method that further includes Chen's sugarcane-node-recognition teaching, because Chen does not detract from and would remain technically compatible with the use of target travel speed as a transmitted operating condition in the combined method.
Regarding Claim 18,
The combination of Kordick, Landphair, and Chen establishes the method of Claim 9, which is the basis for Claim 18.
Disclosure by Kordick
Kordick teaches:
wherein transmitting one or more target operating conditions
See at least:
"The user selects a target seeding rate through the display interface and communicates this to the Falcon controllers which control the variable speed motors to achieve this rate" ([0075]);
"The controller can be connected to a user interface" ([0055]);
"a seeding system which communicates with a tractor network to provide monitoring and calibration options for variable seed planting rate" ([0018]).
Rationale: These passages expressly teach transmitting target operating conditions/settings through the display/controller architecture.
includes increasing and decreasing the seed distribution rate.
See at least:
"The seed planting method of the present invention dispenses the seeds on an air seeder and utilizes variable speed electric motors to control the dispensement rate of the seeds" ([0031]);
"The controller utilizes an algorithm to determine seed population and adjust the motor speed" ([0071]);
"The user selects a target seeding rate ... and communicates this to the Falcon controllers which control the variable speed motors to achieve this rate" ([0075]).
Rationale: Kordick expressly teaches controlling the seed dispensement/distribution rate with variable-speed motors and adjusting motor speed to achieve a selected target seeding rate. Although Kordick may not literally say "increasing and decreasing the seed distribution rate," a PHOSITA would have understood that controlling variable-speed motors to achieve different target seeding rates necessarily includes increasing the rate when the target is higher and decreasing the rate when the target is lower. Thus, this limitation is at least implicitly disclosed and rendered obvious by Kordick's variable-rate control teaching.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to implement Kordick's target-operating-condition transmission and variable-rate seed dispensement control in the image-based planter method established by Landphair and Chen, so that transmitting one or more target operating conditions would include increasing and decreasing the seed distribution rate. Kordick expressly teaches controlling seed dispensement rate with variable-speed electric motors and adjusting motor speed to achieve a selected target seeding rate, while Landphair reinforces the planter-performance context through real-time image-based planter monitoring, and Chen reinforces crop-material feature analysis in a sugarcane planting context. A PHOSITA would have found it predictable and technically compatible to include increase/decrease seed-distribution-rate commands as part of the transmitted target operating conditions because doing so would improve planting accuracy, controllability, and adaptation of planting output to observed crop-material and planting conditions.
Regarding Claim 22,
The combination of Kordick, Landphair, and Chen establishes the method of Claim 9, which is the basis for Claim 22.
Disclosure by Landphair
Landphair teaches:
determining at least one of a number of nodes and a number of eyes in the target region of the planter
See at least:
"Detector 42 provides a plurality of seed presence signals to electrical processor 16A (FIG. 1), with each seed presence signal being indicative of a respective seed present in the furrow." ([0028])
"The video camera can see seeds passing beneath the camera after being placed in the furrow and coming to rest at the bottom of the furrow. This results in the sensing of an actual location of the seed in the furrow. The image viewed by the camera is transmitted to processor 16A which determines when a seed comes into view." ([0031])
"If detector 42 is configured as a video camera, it is necessary to analyze the video frames to detect when a seed passes a predetermined point on the image..." ([0032])
Rationale: Landphair expressly teaches a camera-based planter target region, namely the furrow region viewed by the camera, and expressly teaches processor determination from visible material appearing in that target region. Landphair does not expressly disclose nodes or eyes, but it expressly supplies the planter target-region and visible-material determination framework for this limitation.
Disclosure by Chen
Chen teaches:
includes counting at least one of the visible number of nodes and the visible number of eyes in the target region.
See at least:
"This article uses industrial cameras to obtain images of sugarcane, then uses a computer to process sugarcane image and obtain information of sugarcane nodes, and finally identifies and locates sugarcane nodes accurately by the proposed algorithm." (Image acquisition)
"In order to verify the identification and location performance of the proposed algorithm, we designed a sugarcane nodes identification system and sugarcane seed cutting platform." (Image acquisition)
"the final position of the sugarcane nodes were determined according to the number of nodes to be identified." (Abstract)
Rationale: Chen expressly teaches image-based identification and location of sugarcane nodes from captured images. Once visible node instances are identified in the viewed image region, counting the visible number of nodes in that region is at least implicit and PHOSITA-obvious. Chen does not expressly disclose "eyes," but the claim recites "at least one of the visible number of nodes and the visible number of eyes," so Chen's disclosure of visible node identification and corresponding node-number determination is sufficient for the node branch of the limitation.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to implement Chen's image-based sugarcane node-identification processing within the Kordick/Landphair planter method so that determining a number of nodes in the target region of the planter would include counting the visible number of nodes in that target region. This combination is supported by complementary teachings and the predictable use of known elements, because Kordick provides the controller-based planter method framework, Landphair provides visible-target-region image acquisition in the planter, and Chen provides machine-vision identification of visible sugarcane nodes from captured images.
Regarding Claim 24,
The combination of Kordick, Landphair, and Chen establishes the system of Claim 1, which is the basis for Claim 24.
Disclosure by Landphair
Landphair discloses:
wherein
See at least:
"According to an aspect of the present invention, a detector 42 forming part of the seed spacing monitoring system 16 is supported to detect seeds in the furrow prior to the seeds being covered by closing wheels 34." ([0028])
Rationale: This passage discloses that, within the already-established planter system, an added image/detection condition is performed in a specific planter region, thereby supporting the dependent transition introduced by wherein.
when the controller determines the at least one of the number of nodes and the number of eyes in the field of view,
See at least:
"In another embodiment of the invention, detector 42 can be configured as a video camera which is mounted to the row crop unit and arranged to view the furrow between furrow opener 28 and closing wheels 34." ([0031])
"There, the video camera can see seeds passing beneath the camera after being placed in the furrow and coming to rest at the bottom of the furrow." ([0031])
"The image viewed by the camera is transmitted to processor 16A which determines when a seed comes into view." ([0031])
"If detector 42 is configured as a video camera, it is necessary to analyze the video frames to detect when a seed passes a predetermined point on the image..." ([0032])
Rationale: Landphair expressly discloses a controller/processor making image-based determinations from material appearing in a field of view, namely the furrow viewed by the camera. Landphair does not expressly disclose sugarcane nodes or eyes, but it expressly provides the field-of-view determination framework for this limitation.
Motivation to Combine Kordick and Landphair
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick and Landphair before them, to incorporate Landphair's planter-mounted camera and field-of-view image-detection arrangement into Kordick's controller-based planter system so that controller determinations could be made from crop material appearing in a viewed planter region. This combination is supported by technical compatibility and predictable use of known elements because Kordick provides the planter-control system backbone while Landphair provides a known camera/processor arrangement for visible-material analysis in the planter furrow.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick and Landphair
After combining the teachings of Kordick and Landphair, the following claim limitation is not explicitly disclosed:
the controller is configured to count at least one of the number of nodes and the number of eyes visible in the field of view.
Disclosure by Chen
Chen discloses:
the controller is configured to count at least one of the number of nodes and the number of eyes visible in the field of view.
See at least:
"This article uses industrial cameras to obtain images of sugarcane, then uses a computer to process sugarcane image and obtain information of sugarcane nodes, and finally identifies and locates sugarcane nodes accurately by the proposed algorithm."
"Then, the final position of the sugarcane nodes were determined according to the number of nodes to be identified..."
"The experimental results show that the algorithm proposed in this paper has a single node identification rate of 100% ... a double nodes identification rate of 98.5% ..."
Rationale: Chen expressly discloses camera-acquired sugarcane images processed by a computer to identify sugarcane nodes, expressly states that final node position is determined according to the number of nodes to be identified, and expressly distinguishes single-node and double-node cases. Once visible node instances are identified in the image, counting the visible number of nodes in the field of view is at least express or, at minimum, PHOSITA-obvious from Chen's disclosed node-identification workflow. Chen does not expressly disclose "eyes," but the claim is written in the alternative—"at least one of the number of nodes and the number of eyes"—so disclosure of visible node counting is sufficient for the node branch of the limitation.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to apply Chen's image-based sugarcane node-recognition processing within the Kordick/Landphair planter system so that, when the controller determines node information in the field of view, the controller counts the visible number of nodes in that field of view. This combination is supported by complementary teachings and predictable use of known elements because Kordick provides the controller-based planter system, Landphair provides field-of-view image acquisition in the planter, and Chen provides machine-vision recognition of visible sugarcane nodes from captured images.
Claims 7 is rejected under 35 U.S.C. 103 as being unpatentable over Kordick (US 20170273235 A1), in view of Landphair (US 20120046838 A1), in view of Chen (Sugarcane Stem Node Recognition in Field by Deep Learning Combining Data Expansion | MDPI), and in view of Mentzer (CA 3070140 A1).
Regarding Claim 7,
The combination of Kordick, Landphair, and Chen establishes the system of Claim 1, which is the basis for Claim 7.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick, Landphair, and Chen
After combining the teachings of Kordick, Landphair, and Chen, the following claim limitations are not explicitly disclosed:
further comprising a second camera having a second field of view,
and wherein the one or more controllers are in operable communication with the second camera.
Disclosure by Mentzer
Mentzer discloses:
further comprising a second camera having a second field of view,
See at least:
"the row crop planter may be configured to include one or more cameras that are each configured and positioned with a field of view that extends across multiple different trenches" ([0033]);
"the same camera may be configured to capture images at a relatively low resolution or to capture image data in a way better suited to tracking the movement/presence of a seed. For example, the first camera might be configured as a motion capture or thermal imaging system … In such system, a second camera may be provided and configured to capture images at a higher-resolution" ([0026]).
Rationale: Mentzer expressly discloses a second camera. It also expressly discloses that the second camera is configured to capture images and that the cameras are positioned with a field of view. Thus, the second camera / second field-of-view limitation is expressly disclosed in substance.
and wherein the one or more controllers are in operable communication with the second camera.
See at least:
"the controller 401 is configured to monitor the image data from the first camera until a seed is detected and to then activate the flash and capture an image using the second camera in response to detecting the presence of a seed in the trench" ([0026]);
Fig. 4 shows controller 401 communicatively coupled to camera 409.
Rationale: Mentzer expressly discloses controller operation with the second camera. A controller configured to capture an image using the second camera is necessarily in operable communication with the second camera. This limitation is expressly disclosed, or at minimum inherent, from the disclosed controller-second-camera operation.
Motivation to Combine Kordick, Landphair, Chen, and Mentzer
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, Chen, and Mentzer before them, to incorporate the expressly taught dual-camera planter imaging arrangement of Mentzer into the Kordick-Landphair-Chen Claim 1 system so that the planter could obtain additional image information from a second camera under controller operation. This combination is supported by technical compatibility and predictable use of known elements: Kordick provides the planting-rate/controller backbone, Landphair provides a planter-mounted camera environment, Chen provides node-recognition image analysis for sugarcane material, and Mentzer expressly teaches adding a second planter camera under controller control with its own field of view. Combining those teachings would have predictably improved monitoring accuracy, imaging coverage, and reliability of image-based planting analysis.
Claims 8 is rejected under 35 U.S.C. 103 as being unpatentable over Kordick (US 20170273235 A1), in view of Landphair (US 20120046838 A1), in view of Chen (Sugarcane Stem Node Recognition in Field by Deep Learning Combining Data Expansion | MDPI), in view of Mentzer (CA 3070140 A1), and in view of Rodel (US 20150082695 A1).
Regarding Claim 8,
The combination of Kordick, Landphair, Chen, and Mentzer establishes the system of Claim 7, which is the basis for Claim 8.
Disclosure by Kordick
Kordick does not explicitly disclose/teach the following new claim limitation of Claim 8:
wherein the first camera and the second camera
produce a three-dimensional image.
Disclosure by Landphair
Landphair does not explicitly disclose the following remaining new claim limitation:
wherein the first camera and the second camera
produce a three-dimensional image.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick and Landphair
After combining the teachings of Kordick and Landphair, the following claim limitation is not explicitly disclosed:
wherein the first camera and the second camera
produce a three-dimensional image.
Disclosure by Chen
Chen does not explicitly disclose the following remaining new claim limitation of Claim 8:
wherein the first camera and the second camera
produce a three-dimensional image.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick, Landphair, and Chen
After combining the teachings of Kordick, Landphair, and Chen, the following claim limitation is not explicitly disclosed:
wherein the first camera and the second camera
produce a three-dimensional image.
Disclosure by Mentzer
Mentzer discloses:
wherein the first camera and the second camera
See at least:
"the system may include two or more cameras that are configured and positioned with a field of view that extends across multiple different trenches" ([0033]);
"the first camera might be configured as a motion capture or thermal imaging system ... a second camera may be provided and configured to capture images at a higher-resolution" ([0026]–[0027]).
*Rationale: Mentzer expressly discloses first and second cameras in the planter imaging system. Thus, the dual-camera portion of this limitation is expressly disclosed.*
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick, Landphair, Chen, and Mentzer
After combining the teachings of Kordick, Landphair, Chen, and Mentzer, the following claim limitation is not explicitly disclosed:
produce a three-dimensional image.
Disclosure by Rodel
Rodel discloses:
produce a three-dimensional image.
See at least:
"the stalk may be irradiated with two or three or even more laser beams and two or more optical sensor may be used for detecting the reflected electromagnetic radiation of the laser beams" ([0021]);
"the optical sensor may be a camera, preferably a camera obtaining images that may be analyzed using laser triangulation for extracting the shape of the surface of the stalk" ([0034]);
"In the present embodiment, the optical sensor 13 is a camera. It detects visual images ... The images are transferred to analyzing unit 14 that is able to compute the three-dimensional shape of the surface of stalk halves 7" ([0064]).
Rationale: Rodel expressly discloses camera-based imaging that is used to compute the three-dimensional shape of the imaged surface, and it further expressly teaches that two or more optical sensors may be used. Thus, Rodel expressly teaches the three-dimensional imaging result, and at least implicitly teaches a multi-sensor/camera arrangement capable of producing three-dimensional image information. When applied to the first-and-second-camera system already established by Claim 7 through Mentzer, a PHOSITA would have understood it to be obvious to configure the first camera and the second camera to produce a three-dimensional image, because Rodel teaches that camera-obtained images, including from multiple optical sensors, can be processed to derive a three-dimensional representation of the target surface.
Motivation to Combine Kordick, Landphair, Chen, Mentzer, and Rodel
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, Chen, Mentzer, and Rodel before them, to configure the first-and-second-camera planter imaging arrangement of Mentzer in view of Rodel's express teaching that camera-obtained images, including images from two or more optical sensors, can be analyzed to compute a three-dimensional shape, so that the first camera and the second camera would produce a three-dimensional image. This would have been a predictable use of known multi-camera / multi-sensor imaging techniques to improve depth perception, image analysis accuracy, and reliability of crop-material characterization.
Claims 11, 16, 17, 21, and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Kordick (US 20170273235 A1), in view of Landphair (US 20120046838 A1), in view of Chen (Sugarcane Stem Node Recognition in Field by Deep Learning Combining Data Expansion | MDPI), and in view of Rodel (US 20150082695 A1).
Regarding Claim 11,
The combination of Kordick, Landphair, and Chen establishes the method of Claim 9, which is the basis for Claim 11.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick, Landphair, and Chen
After combining the teachings of Kordick, Landphair and Chen, the following claim limitation is not explicitly disclosed:
wherein receiving image data from a camera includes receiving three-dimensional image data.
Disclosure by Rodel
Rodel teaches:
wherein receiving image data from a camera includes receiving three-dimensional image data.
See at least:
"the stalk may be irradiated with two or three or even more laser beams and two or more optical sensor may be used for detecting the reflected electromagnetic radiation of the laser beams" ([0021]);
"the optical sensor may be a camera, preferably a camera obtaining images that may be analyzed using laser triangulation for extracting the shape of the surface of the stalk" ([0034]);
"The images are transferred to analyzing unit 14 that is able to compute the three-dimensional shape of the surface of stalk halves 7" ([0064]).
Rationale: Rodel expressly teaches that camera-obtained images are transferred to an analyzing unit and used to compute the three-dimensional shape of the stalk surface. Rodel also expressly teaches using two or more optical sensors. Although Rodel does not literally use the phrase "three-dimensional image data," a PHOSITA would have understood image data used to generate a three-dimensional shape representation through laser triangulation and multi-sensor optical imaging to constitute, or at minimum render obvious, three-dimensional image data. Thus, this limitation is at least implicitly disclosed and rendered obvious by Rodel.
Motivation to Combine Kordick, Landphair, Chen, and Rodel
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, Chen, and Rodel before them, to configure the image-receipt method established by Kordick, Landphair, and Chen, to receive image data in the form of three-dimensional image data as taught by Rodel, because Rodel expressly teaches camera-based optical imaging processed to compute a three-dimensional shape representation. This would have been a predictable use of known three-dimensional imaging techniques to improve depth-aware crop-material characterization, node detection reliability, and planting analysis accuracy.
Regarding Claim 16,
The combination of Kordick, Landphair, and Chen establishes the method of Claim 9, which is the basis for Claim 16.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick, Landphair, and Chen
After combining the teachings of Kordick, Landphair, and Chen, the following claim limitation is not explicitly disclosed:
further comprising calculating one or more bulk billet attributes
based at least in part on attributes associated with the crop material in the target region.
Disclosure by Rodel
Rodel teaches:
further comprising calculating one or more bulk billet attributes
See at least:
"the bud on the stalk comprises computing the topography of the stalk based on the detected reflected electromagnetic radiation" ([0022]);
"the optical sensor may be a camera, preferably a camera obtaining images that may be analyzed using laser triangulation for extracting the shape of the surface of the stalk" ([0034]);
"The images are transferred to analyzing unit 14 that is able to compute the three-dimensional shape of the surface of stalk halves 7" ([0064]).
Rationale: Rodel expressly teaches calculating physical and geometric characteristics of the crop material, including topography and three-dimensional shape of stalk halves, from image/sensor data. Those are billet-related attributes of the imaged crop material. A PHOSITA would have understood that such computed geometric and surface characteristics of the observed stalk halves constitute one or more bulk billet attributes, or at minimum would have found it obvious to use them as bulk billet attributes in a sugarcane billet analysis workflow.
based at least in part on attributes associated with the crop material in the target region.
See at least:
"The images are transferred to analyzing unit 14" ([0064]);
"computing the topography of the stalk based on the detected reflected electromagnetic radiation" ([0033]);
Rationale: Rodel expressly teaches that the computed topography and three-dimensional shape are derived from image/sensor information associated with the imaged stalk region. Thus, the calculated billet attributes are based at least in part on attributes associated with the crop material in the target region. This limitation is expressly disclosed in substance, or at minimum inherent in Rodel's image-based shape/topography computation.
Motivation to Combine Kordick, Landphair, Chen, and Rodel
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, Chen, and Rodel before them, to incorporate Rodel's image-based computation of stalk topography and three-dimensional shape into the Kordick-Landphair-Chen method so that one or more bulk billet attributes could be calculated from attributes associated with the crop material in the target region. This would have been a predictable use of known sugarcane imaging and geometric-analysis techniques to improve characterization of billet material and enhance planting-related analysis.
Regarding Claim 17,
The combination of Kordick, Landphair, Chen, and Rodel establishes the method of Claim 16, which is the basis for Claim 17.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick, Landphair, and Chen
After combining the teachings of Kordick, Landphair, and Chen, the following claim limitation is not explicitly disclosed:
is at least partially dependent upon the bulk billet attributes.
Disclosure by Rodel
Rodel teaches:
is at least partially dependent upon the bulk billet attributes.
See at least:
"the bud on the stalk comprises computing the topography of the stalk based on the detected reflected electromagnetic radiation" ([0022]);
"the optical sensor may be a camera, preferably a camera obtaining images that may be analyzed using laser triangulation for extracting the shape of the surface of the stalk" ([0034]);
"The images are transferred to analyzing unit 14 that is able to compute the three-dimensional shape of the surface of stalk halves 7" ([0064]).
Rationale: As established for Claim 16, Rodel teaches calculating billet-related geometric/topographical attributes from crop material in the target region. Kordick teaches determining current seed feed rate. A PHOSITA would have found it obvious to make the current seed feed rate determination at least partially dependent on those computed bulk billet attributes, because such billet-scale physical attributes affect the effective planting value, quantity, and handling characteristics of the planted material. Using computed billet attributes as an input to the feed-rate determination is a predictable refinement of Kordick's rate-determination logic in view of Rodel's billet-attribute computation.
Motivation to Combine Kordick, Landphair, Chen, and Rodel
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, Chen, and Rodel before them, to incorporate Rodel's computed bulk billet attributes into Kordick's current seed-feed-rate determination, within the planter-image-analysis method established by Landphair and Chen, so that the current seed feed rate would be at least partially dependent upon the bulk billet attributes. This would have been a predictable use of known billet-characterization information to improve accuracy, control, and agronomic relevance of planting-rate determination.
Regarding Claim 21,
The combination of Kordick, Landphair, and Chen establishes the system of Claim 1, which is the basis for Claim 21.
Claim Limitations Not Explicitly Disclosed by Kordick
Kordick does not explicitly disclose the following claim limitations:
when the controller determines at least one of the number of nodes and the number of eyes in the field of view,
the controller is configured to calculate at least one of the number of nodes in the field of view and the number of eyes in the field of view
based on a number of billets in the field of view
and a length of each billet in the field of view.
Disclosure by Landphair
Landphair discloses:
when the controller determines at least one of the number of nodes and the number of eyes in the field of view,
See at least:
"the video camera can see seeds passing beneath the camera after being placed in the furrow and coming to rest at the bottom of the furrow. This results in the sensing of an actual location of the seed in the furrow. The image viewed by the camera is transmitted to processor 16A which determines when a seed comes into view. Processor 16A then measures the time until the next seed is detected." ([0031])
"If detector 42 is configured as a video camera, it is necessary to analyze the video frames to detect when a seed passes a predetermined point on the image..." ([0032])
Rationale: This expressly links the trigger when to an image-based processor determination. Landphair is not being used for sugarcane nodes specifically; it is being used for the trigger structure that a processor/controller makes a determination from material appearing in a camera-viewed region. Thus, the "when the controller determines ... in the field of view" trigger is expressly grounded in Landphair's field-of-view image-detection environment.
Motivation to Combine Kordick and Landphair
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick and Landphair before them, to incorporate Landphair's planter-mounted camera and image-determination arrangement into Kordick's controller-based planter system so that controller determinations could be made from crop material appearing in a planter field of view. This is supported by technical compatibility and predictable use of known elements because Kordick provides the planter control backbone while Landphair provides a known camera/processor field-of-view detection arrangement in a planter environment.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick and Landphair
After combining the teachings of Kordick and Landphair, the following claim limitations are not explicitly disclosed:
the controller is configured to calculate at least one of the number of nodes in the field of view and the number of eyes in the field of view
based on a number of billets in the field of view and a length of each billet in the field of view.
Disclosure by Chen
Chen discloses:
the controller is configured to calculate at least one of the number of nodes in the field of view and the number of eyes in the field of view
See at least:
"this paper proposed an algorithm for the identification of yellow sugarcane nodes..."
"This article uses industrial cameras to obtain images of sugarcane, then uses a computer to process sugarcane image and obtain information of sugarcane nodes..."
"the final position of the sugarcane nodes were determined according to the number of nodes to be identified..."
Rationale: This expressly links the trigger phrase the controller is configured to calculate to the node-recognition portion of the claim. Chen is the reference that supplies the actual node-side computation. It teaches computer/image-based processing of sugarcane images to obtain node information, and expressly refers to determination according to the number of nodes to be identified. Thus, the claimed calculation of node quantity is tied here to the specific node-recognition trigger, rather than being over-assigned to Kordick.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to apply Chen's sugarcane-node image-recognition processing within the Kordick/Landphair planter controller and camera framework so that the controller could calculate node quantity from crop material appearing in the planter field of view. This is supported by complementary teachings and predictable use of known elements because Kordick and Landphair provide the controller-plus-camera environment while Chen provides image-based node recognition for sugarcane.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick, Landphair, and Chen
After combining the teachings of Kordick, Landphair, and Chen, the following claim limitations are not explicitly disclosed:
based on a number of billets in the field of view and a length of each billet in the field of view.
Disclosure by Rodel
Rodel discloses:
based on a number of billets in the field of view and a length of each billet in the field of view.
See at least:
"The plants used for replanting are harvested and then cut in segments of approximately 20 to 50 cm, so that at least two nodes are present in each stem segment sett. The segments are cut to have at least two buds or at least two nodes; every node gives generally rise to one single bud..." ([0003])
"After cutting, the setts, which have one or more nodes, are disposed horizontally, over one another in furrows..." ([0004])
"The length of a stalk segment 15 corresponds approximately to the distance of two buds 8 in the longitudinal direction L." ([0071])
"Therefore, main control unit 5 may determine the position of stalk segments 15 as well as the position of buds 8 at any time." ([0072])
Rationale: This expressly links the trigger based on the billet-related inputs and links the trigger to the second required input. Rodel is the reference that provides the sugarcane-specific structural relationships among billet segmentation, billet length, and node/bud content. Paragraph [0003] provides billets/segments and their node/bud content; paragraph [0004] places multiple setts in furrows, which fits the already-established field-of-view planting context from Landphair; paragraph [0071] expressly provides the length relationship; and paragraph [0072] provides controller-side determination of stalk-segment and bud position. Thus, the calculation in the combined system is explicitly tied to two inputs: first, the number of billets in view, and second, the length of each billet. The trigger phrase based on ... and ... is therefore expressly linked to Rodel's billet-count / billet-length teachings, with the final claimed calculation being PHOSITA-obvious in the combined Kordick/Landphair/Chen/Rodel system.
Motivation to Combine Kordick, Landphair, Chen, and Rodel
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, Chen, and Rodel before them, to incorporate Rodel's sugarcane billet segmentation and billet-length-to-node/bud relationship into the image-based controller system established by Kordick, Landphair, and Chen so that, when the controller determines node information in the field of view, the controller calculates node-or-eye quantity based on two billet-related inputs, namely a number of billets in the field of view and a length of each billet in the field of view. This combination is supported by technical compatibility, complementary teachings, and predictable improvement in agronomic characterization accuracy and planting control because Kordick provides the planter control architecture, Landphair provides the field-of-view image-acquisition environment, Chen provides node-recognition processing, and Rodel provides the sugarcane-specific relationship tying billet segmentation and billet length to node/bud content.
Regarding Claim 23,
The combination of Kordick, Landphair, and Chen establishes the method of Claim 9, which is the basis for Claim 23.
Disclosure by Landphair
Landphair teaches:
wherein
See at least:
"According to an aspect of the present invention, a detector 42 forming part of the seed spacing monitoring system 16 is supported to detect seeds in the furrow prior to the seeds being covered by closing wheels 34." ([0028])
Rationale: This passage teaches that, within the already-established planter method, an added detection/determination condition is performed in a specific planter region, thereby supporting the dependent transition introduced by wherein.
determining at least one of a number of nodes and a number of eyes in the target region of the planter
See at least:
"Detector 42 provides a plurality of seed presence signals to electrical processor 16A (FIG. 1), with each seed presence signal being indicative of a respective seed present in the furrow." ([0028])
"In another embodiment of the invention, detector 42 can be configured as a video camera which is mounted to the row crop unit and arranged to view the furrow between furrow opener 28 and closing wheels 34." ([0031])
"The image viewed by the camera is transmitted to processor 16A which determines when a seed comes into view." ([0031])
"If detector 42 is configured as a video camera, it is necessary to analyze the video frames to detect when a seed passes a predetermined point on the image..." ([0032])
Rationale: Landphair expressly teaches a target region of the planter, namely the furrow region viewed by the camera, and expressly teaches processor determination from visible material in that region. Landphair does not expressly disclose nodes or eyes, but it expressly provides the planter target-region and field-of-view determination framework for this limitation.
Motivation to Combine Kordick and Landphair
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick and Landphair before them, to incorporate Landphair's planter-mounted camera and target-region image-detection arrangement into Kordick's controller-based planter method so that determinations could be made from crop material appearing in a target region of the planter. This combination is supported by technical compatibility and predictable use of known elements because Kordick provides the planter-control method backbone while Landphair provides a known camera/processor arrangement for visible-material analysis in the planter furrow.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick and Landphair
After combining the teachings of Kordick and Landphair, the following claim limitations are not explicitly disclosed:
includes calculating at least one of the number of nodes and the number of eyes in the field of view
based at least in part on the number of billets in the field of view.
Disclosure by Chen
Chen teaches:
includes calculating at least one of the number of nodes and the number of eyes in the field of view
See at least:
"Jiqing Chen et al. [7] proposed a sugarcane nodes identification algorithm based on the sum of local pixels of the minimum points of vertical projection function to analyse the recognition of a single node and double nodes."
"In order to solve these problems, this paper proposes a sugarcane stem node recognition algorithm based on deep learning driven by big data in the natural environment."
"The result indicated that the detection method based on YOLO v4 was feasible for fast and accurate detection of sugarcane stem nodes in the complex natural environment."
Rationale: Chen expressly teaches machine-vision identification of sugarcane nodes from captured images and expressly discusses single-node and double-node recognition. Thus, Chen teaches or at least renders obvious calculating the number of nodes in the field of view. Chen does not expressly disclose "eyes," but the claim is written in the alternative, so node calculation is sufficient for that branch of the limitation.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to apply Chen's sugarcane-node image-recognition processing within the Kordick/Landphair planter method so that determining a number of nodes in the target region of the planter would include calculating the number of nodes in the field of view. This combination is supported by complementary teachings and predictable use of known elements because Kordick provides the controller-based planter method, Landphair provides target-region image acquisition in the planter, and Chen provides machine-vision recognition of sugarcane nodes from captured images.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick, Landphair, and Chen
After combining the teachings of Kordick, Landphair, and Chen, the following claim limitation is not explicitly disclosed:
based at least in part on the number of billets in the field of view.
Disclosure by Rodel
Rodel teaches:
based at least in part on the number of billets in the field of view.
See at least:
"For commercial agriculture, the seed of a sugar cane is not sown or planted, but instead, the cane is propagated vegetatively by planting a stem segment or part of a stalk or culm or seedling." ([0002])
"The plants used for replanting are harvested and then cut in segments of approximately 20 to 50 cm, so that at least two nodes are present in each stem segment sett. … The segments are cut to have at least two buds or at least two nodes; every node gives generally rise to one single bud …" ([0003])
"After cutting, the setts, which have one or more nodes, are disposed horizontally, over one another in furrows …" ([0004])
"Subsequently, both stalk halves 7 are further feed on conveyer to a further cutting device 32. Cutting device 32 cuts stalk halves 7 positioned next to each other into stalk segments 15, so that each segment 15 comprises only one bud 8." ([0071])
"As two stalk segments 15, each comprising one bud 8, are positioned next to each other, each stroke of punching device 17 results in two bud chips …" ([0074])
Rationale: Rodel expressly discloses sugarcane planting material in the form of stem segments/setts, i.e., billets; expressly discloses that those billets contain nodes/buds; and expressly discloses multiple stalk segments positioned next to each other. Rodel does not recite the exact claim language verbatim. However, Rodel expressly teaches a structural relationship between the number of billets/segments present and the node/bud content carried by those billets. In the combined Kordick/Landphair/Chen system, where crop material is imaged in a field of view and node quantity is calculated from image data, a PHOSITA would have found it obvious to calculate node-or-eye quantity based at least in part on the number of billets in the field of view, because Rodel teaches that billets are the sugarcane planting units carrying the relevant nodes/buds and that multiple such billets may be present together. This is a reasoned PHOSITA-obvious inference with rational underpinning.
Motivation to Combine Kordick, Landphair, Chen, and Rodel
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, Chen, and Rodel before them, to incorporate Rodel's sugarcane billet/sett teaching into the image-based planter method established by Kordick, Landphair, and Chen so that the calculation of the number of nodes or eyes in the field of view would be based at least in part on the number of billets in the field of view. This combination is supported by technical compatibility, complementary teachings, and predictable improvement in agronomic characterization accuracy because Kordick provides the planter-control method framework, Landphair provides the planter target-region and field-of-view imaging environment, Chen provides node-recognition calculation from captured images, and Rodel provides the sugarcane-specific relationship between billets/setts and the nodes/buds carried by those billets.
Claims 15 is rejected under 35 U.S.C. 103 as being unpatentable over Kordick (US 20170273235 A1), in view of Landphair (US 20120046838 A1), in view of Chen (Sugarcane Stem Node Recognition in Field by Deep Learning Combining Data Expansion | MDPI), and in view of Chen Jiqing (Sugarcane nodes identification algorithm based on sum of local pixel of minimum points of vertical projection function - ScienceDirect).
Regarding Claim 15,
The combination of Kordick, Landphair, and Chen establishes the method of Claim 9, which is the basis for Claim 15.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick and Landphair
After combining the teachings of Kordick and Landphair, the following claim limitations are not explicitly disclosed:
wherein determining at least one of the number of nodes and the number of eyes in the target region of the planter includes calculating at least one of the number of nodes and the number of eyes in the target region based at least in part on a pre-determined virtual billet model.
Disclosure by Chen
Chen teaches:
wherein determining at least one of the number of nodes and the number of eyes in the target region of the planter includes calculating at least one of the number of nodes and the number of eyes in the target region
See at least:
"an object detection algorithm based on deep learning was proposed for sugarcane stem node recognition" (Abstract);
"The image set collected was composed of images of one single sugarcane stem node and images of multiple sugarcane stem nodes" (Section 2.1);
"The research shows that it is a feasible method for real-time detection of sugarcane stem nodes" (Abstract).
Rationale: Chen expressly teaches image-based node recognition in images containing single-node and multiple-node target regions. Once node instances are detected in the target region, calculating the number of detected nodes in that target region is an implicit and PHOSITA-obvious post-detection operation. Chen does not expressly teach "eyes," but because the claim recites "at least one of the number of nodes and the number of eyes," Chen's node-based teaching is sufficient for this portion.
Motivation to Combine Kordick, Landphair, and Chen
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Chen before them, to apply Chen's image-based sugarcane-node recognition within the Kordick method as enhanced by Landphair's planter-camera image acquisition so that node quantity in the target region could be calculated from the captured planter images. This would have been a predictable use of known machine-vision detection in a planter-rate-control context to improve crop-material characterization.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick, Landphair, and Chen
After combining the teachings of Kordick, Landphair, and Chen, the following claim limitation is not explicitly disclosed:
calculating based at least in part on a pre-determined virtual billet model.
Disclosure by Chen Jiqing
Chen Jiqing teaches:
calculating based at least in part on a pre-determined virtual billet model.
See at least:
"Aiming at the difficulty of sugarcane nodes identification and location during automatic cutting of sugarcane seeds, based on machine vision system, this paper proposed a sugarcane nodes identification algorithm based on sum of local pixel of minimum points of vertical projection function. Firstly, according to the color and texture characteristics of yellow sugarcane, the captured RGB image of sugarcane was converted into HSV color image. Then, the S-component image in the HSV image was extracted, and the S-component image was binarized by the Otsu algorithm to obtain the binary image, and then the binary image was processed by morphological closed operation ... Subsequently, the sugarcane area was segmented as the region of interest through the horizontal projection of the binary image ... Finally, the vertical projection function of the binary image of the region of interest was established, and the function was continuously derived to obtain the minimum points ... Then, the final position of the sugarcane nodes were determined according to the number of nodes to be identified and the sum of pixels of each 5 columns on both sides of the minimum points." (Abstract)
Rationale: Chen Jiqing expressly teaches establishing a projection-function-based structural model of the sugarcane region of interest and then using that model to determine node positions according to the number of nodes to be identified. Although the paper does not use the exact phrase "pre-determined virtual billet model," it does teach a pre-established mathematical billet-region model that is applied to calculate node-related attributes from image data. A PHOSITA would have understood this projection-function-based, rule-driven billet representation to be an obvious form of a pre-determined virtual billet model for calculating the number of nodes, and thus at least one of the number of nodes and the number of eyes, in the target region.
Motivation to Combine Kordick, Landphair, Chen, and Chen Jiqing
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, Chen, and Chen Jiqing before them, to incorporate Chen Jiqing's pre-established projection-function-based sugarcane node-identification model into the Kordick-Landphair-Chen planter method so that node quantity in the target region could be calculated from image data based at least in part on a pre-determined billet-region model. This would have been a predictable use of known sugarcane machine-vision modeling techniques to improve node/eye estimation accuracy and robustness in planter-based seed-feed-rate determination.
Claims 19 is rejected under 35 U.S.C. 103 as being unpatentable over Kordick (US 20170273235 A1), in view of Landphair (US 20120046838 A1), in view of Chen (Sugarcane Stem Node Recognition in Field by Deep Learning Combining Data Expansion | MDPI), and in view of Czapka (US 20180208058 A1).
Regarding Claim 19,
Disclosure by Kordick
Kordick discloses:
A planting machine
See at least:
"The present invention relates to agricultural machines..." ([0003])
"The seeder can take the form of a conventional air seeder..." ([0052])
Rationale: Kordick expressly discloses an agricultural seeder, which is a planting machine.
comprising:
See at least:
"This embodiment modifies seed distribution by utilizing a seed distribution manifold 10 and a controller 30." ([0053])
Rationale: Kordick discloses an apparatus including multiple structural components, corresponding to the open transitional phrase comprising.
a hopper;
See at least:
"Each manifold 10 includes a base plate 12 with inlets 14 which are in communication with a bin or hopper 26..." ([0063])
Rationale: Kordick expressly discloses a hopper.
a planting chute;
See at least:
"A seed outlet chute or cup 16 is associated with each of the inlets 14." ([0063])
Rationale: Kordick expressly discloses a chute associated with seed output, satisfying a planting chute.
a metering device
See at least:
"a seed meter subassembly including a motor and gears controls the metering of seeds between each inlet 14 and its associated outlet 16." ([0063])
Rationale: Kordick expressly discloses a seed meter subassembly, which is a metering device.
configured to output crop material
See at least:
"bulk seed is distributed through inlets to the tops of seed rollers... the rollers essentially divide... the incoming bulk product and discharge it serially into an individual output." ([0011])
Rationale: Kordick expressly discloses the metering structure outputting seed, i.e., crop material.
at a pre-determined rate
See at least:
"a seed planter which can be programmed to adjust the seed population according to varying field conditions" ([0016])
"The system includes one or more controllers to provide variable seed rate control..." ([0061])
Rationale: Programmable seed population / variable seed rate control renders obvious output at a selected, pre-determined rate.
to the planting chute;
See at least:
"controls the metering of seeds between each inlet 14 and its associated outlet 16." ([0063])
Rationale: Kordick expressly teaches seed metering to the outlet chute / cup.
and one or more controllers
See at least:
"The system includes one or more controllers..." ([0061])
Rationale: Kordick expressly discloses one or more controllers.
wherein the one or more controllers are configured to:
See at least:
"The system includes one or more controllers to provide variable seed rate control..." ([0061])
Rationale: Kordick expressly discloses controller-configured planting functions.
calculate the travel speed of the planting machine,
See at least:
"read a speed sensor for measuring ground speed." ([0061])
"Parameters such as implement or vehicle ground speed can be obtained." ([0056])
Rationale: Kordick expressly discloses obtaining the measured ground speed of the implement/vehicle, which satisfies calculating travel speed.
Claim Limitations Not Explicitly Disclosed by Kordick
Kordick does not explicitly disclose the following claim limitations:
a camera
having a first field of view
configured to capture crop material
that is distributed from the metering device;
in operable communication with the hopper, planting chute, metering device, and camera,
receive video data from the camera,
identify one or more attributes of the crop material traveling through the first field of view,
calculate the crop seed rate of the planting machine
based at least in part on the travel speed and one or more attributes of the crop material,
and output commands to the planting machine to increase or decrease the travel speed of the planting machine
based at least in part on the calculated crop seed rate.
Disclosure by Landphair
Landphair discloses:
a camera
See at least:
"detector 42 can be configured as a video camera..." ([0031])
Rationale: Landphair expressly discloses a camera in the form of a video camera.
having a first field of view
See at least:
"the video camera... is mounted to the row crop unit and arranged to view the furrow..." ([0031])
Rationale: A camera arranged to view the furrow necessarily has a field of view covering that viewed region.
configured to capture crop material
See at least:
"the video camera can see seeds passing beneath the camera..." ([0031])
Rationale: Seeds are crop material. Landphair expressly discloses the camera capturing seeds.
that is distributed from the metering device;
See at least:
"The seeds are singulated and discharged at a predetermined rate to the seed placement system." ([0003])
"Seed metering system 36 singulates the seed and transfers the seed to seed placement system 38." ([0027])
"the video camera can see seeds passing beneath the camera after being placed in the furrow..." ([0031])
Rationale: Landphair expressly discloses that the crop material first originates at the seed metering system, is singulated and discharged / transferred from that metering system to the seed placement system, and is then viewed by the video camera downstream in the same seed-delivery path. Thus, although the camera is positioned downstream of the meter rather than at the meter itself, the camera still captures crop material that has been distributed from the metering device. This is a narrower and more accurate reading than saying the camera observes material while exiting the meter, and it is consistent with the reference's express disclosure that the observed seeds are the same singulated seeds previously discharged from the metering system.
in operable communication with the hopper, planting chute, metering device, and camera,
See at least:
"Seed metering system 36 receives seed from... a seed hopper 40..." and "Seed placement system 38 is in the form of a gravity drop seed tube..." ([0027])
"The image viewed by the camera is transmitted to processor 16A..." ([0031])
Rationale: Landphair expressly discloses a processor receiving camera image data within a row-unit architecture that also includes the hopper, seed metering system, and seed tube. In combination with Kordick's controller-based planter architecture, this renders obvious a controller in operable communication with all of those elements.
receive video data from the camera,
See at least:
"The image viewed by the camera is transmitted to processor 16A..." ([0031])
Rationale: Transmission of the image from the camera to the processor expressly discloses receipt of video data.
identify one or more attributes of the crop material traveling through the first field of view,
See at least:
"Processor 16A... determines when a seed comes into view." ([0031])
"it is necessary to analyze the video frames to detect when a seed passes a predetermined point on the image..." ([0032])
Rationale: Landphair expressly discloses identifying visual attributes of the seed in the camera view, including when the seed comes into view and when it passes a predetermined point on the image. That satisfies identifying one or more attributes of crop material traveling through the field of view.
calculate the crop seed rate of the planting machine
See at least:
"Processor 16A then measures the time until the next seed is detected. With planter speed information, the distance between seeds is determined." ([0031])
"The time between detecting the first seed and the second seed, and the ground speed of the seeder" are used in determining spacing ([0014])
Rationale: Landphair does not use the exact phrase "crop seed rate," but expressly teaches calculating planting performance from successive seed detections and planter speed. A PHOSITA would have understood seed spacing, population, and seed rate to be directly related planting metrics. Accordingly, this limitation is rendered obvious by the combination of Landphair's image-based seed detection and speed-based spacing calculation.
based at least in part on the travel speed and one or more attributes of the crop material,
See at least:
"With planter speed information, the distance between seeds is determined." ([0031])
"analyze the video frames to detect when a seed passes a predetermined point on the image..." ([0032])
Rationale: Landphair expressly uses planter travel speed together with image-derived seed information. The detected appearance and passage of the seed in the image are attributes of the crop material.
Motivation to Combine Kordick and Landphair
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick and Landphair before them, to modify Kordick's controller-based variable-rate planting machine to include Landphair's camera-based seed observation and processor analysis so that the controller could receive image data representing seeds that had been discharged from the metering system and placed along the seed path, identify image-based seed attributes in the camera view, and use those attributes together with planting-machine travel speed to determine planting-performance information, because the references are technically compatible planter systems and their combination would have predictably improved planting feedback accuracy, monitoring reliability, and closed-loop control capability.
Claim Limitations Not Explicitly Disclosed by the Combination of Kordick and Landphair
After combining the teachings of Kordick and Landphair, the following claim limitations are not explicitly disclosed:
and output commands to the planting machine to increase or decrease the travel speed of the planting machine
based at least in part on the calculated crop seed rate.
Disclosure by Czapka
Czapka discloses:
and output commands to the planting machine to increase or decrease the travel speed of the planting machine
See at least:
"the planter controller 104 may be configured to transmit a speed request signal... instructing the vehicle controller 102 to reduce the current ground speed of the work vehicle 10... instructing the controller 102 to increase the current ground speed of the work vehicle 10." ([0049])
Rationale: Czapka expressly discloses controller-generated commands that cause the planting machine/work vehicle travel speed to be increased or decreased.
based at least in part on the calculated crop seed rate.
See at least:
"a threshold value(s) for a seed-related parameter... (e.g., a desired population range, a minimum singulation value, a maximum seed skips value, and/or a maximum seed multiples value)... the planter controller 104 may be configured to monitor the relevant operating parameter(s)... and compare such monitored value(s) to the associated threshold value(s)." ([0049])
Rationale: Czapka expressly teaches basing travel-speed commands on seed-related planting-performance parameters, including population-related values. Combined with Kordick and Landphair, which render obvious calculating crop seed rate from travel speed and image-derived seed attributes, this closes the final gap without requiring any remapping of earlier limitations.
Motivation to Combine Kordick, Landphair, and Czapka
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, and Czapka before them, to further modify the combined Kordick/Landphair planting machine so that, after the controller determines planting-performance information from travel speed and camera-derived seed observations, the controller transmits speed-control commands to increase or decrease planting-machine travel speed based on that calculated seed-related result, because Czapka expressly teaches planter-controller-based automatic speed adjustment using seed-related parameters, and applying that known speed-control strategy to the seed-observation framework of Kordick and Landphair would have been a predictable use of known control techniques to improve planting accuracy, efficiency, and real-time closed-loop planter performance.
Claims 20 is rejected under 35 U.S.C. 103 as being unpatentable over Kordick (US 20170273235 A1), in view of Landphair (US 20120046838 A1), in view of Czapka (US 20180208058 A1), and in view of Chen Jiging (Sugarcane nodes identification algorithm based on sum of local pixel of minimum points of vertical projection function - ScienceDirect).
Regarding Claim 20,
The combination of Kordick, Landphair, and Czapka establishes the planting machine of Claim 19, which is the basis for Claim 20.
Claim Limitations Not Explicitly Disclosed by the combination of Kordick, Landphair, and Czapka
The combination of Kordick, Landphair, and Czapka does not explicitly disclose the following claim limitation:
wherein the one or more attributes of the crop material includes at least one of the number of billets traveling through the first field of view, the number of nodes traveling through the first field of view, and the number of eyes traveling through the first field of view.
Disclosure by Chen Jiqing
Chen Jiqing discloses:
wherein the one or more attributes of the crop material includes at least one of the number of nodes traveling through the first field of view,
See at least:
"This article uses industrial cameras to obtain images of sugarcane, then uses a computer to process sugarcane image and obtain information of sugarcane nodes, and finally identifies and locates sugarcane nodes accurately by the proposed algorithm."
"The experimental results show that the algorithm proposed in this paper has a single node identification rate of 100%...; a double nodes identification rate of 98.5%..."
Rationale: Chen Jiqing expressly discloses using cameras to obtain sugarcane images and processing those images to obtain information of sugarcane nodes. That directly supports node-based crop-material attributes derived from a viewed region. Chen Jiqing expressly distinguishes between single-node and double-nodes identification. That is an express disclosure of a count-based node attribute, i.e., the number of nodes. Because Claim 20 recites at least one of the listed alternatives, express disclosure of the node-count alternative is sufficient even though billets and eyes are not separately required.
Motivation to Combine Kordick, Landphair, Czapka, and Chen Jiqing
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Kordick, Landphair, Czapka, and Chen Jiqing before them, to further modify the established Claim 19 planting machine so that the one or more camera-derived attributes of the crop material include a count of sugarcane nodes in the first field of view, because Kordick, Landphair, and Czapka already establish a planting machine having a metering device, camera-based crop-material observation, controller-based calculation/control functionality, and travel-speed adjustment based on planting-performance information, while Chen Jiqing expressly teaches machine-vision processing of sugarcane images to obtain node information and to distinguish single-node and double-node occurrences, such that incorporating Chen Jiqing's node-counting image-analysis technique into the established Claim 19 system would have been a predictable use of known image-processing methods to improve the specificity, informational richness, and utility of crop-material attribute determination.
Response to Arguments
Applicant's arguments filed 01/22/2026 have been fully considered.
Withdrawal of Objections
The Examiner acknowledges the amendments to claims 19 and 20, which address the previously identified typographical errors and permissive language. Specifically, the replacement of "may include" with "comprises" in claim 20 clarifies the scope of the limitation. Furthermore, claims 12 and 13 have been cancelled. Accordingly, the objections to these claims are hereby withdrawn as the issues have been corrected or rendered moot.
Withdrawal of Rejections under 35 U.S.C. 112
The Examiner has carefully considered the Applicant's arguments regarding the enablement and definiteness of claims 6, 8, 11, 15, 16, 17, and 20.
Enablement (35 U.S.C. 112(a)): The rejections of claims 8, 11, 15, 16, and 17 are withdrawn. The Applicant’s argument that a PHOSITA would be able to implement "virtual billet models" and "bulk billet attributes" without undue experimentation is persuasive. In the field of agricultural automation and machine vision, mathematical and statistical modeling—such as the projection-function-based identification taught in the prior art—represents a routine application of known computational techniques. The inclusion of deep learning frameworks for node recognition further demonstrates that high-accuracy object detection and feature extraction were technically feasible and well-documented at the time of filing.
The Examiner agrees that the specification, coupled with the high level of skill in the machine-vision and control-systems arts, provides sufficient guidance to enable the claimed subject matter. Furthermore, the use of multiple sensors to compute a "three-dimensional shape" is a known technique in the art for isolating overlapping objects, rendering the 3D imaging requirements of claims 8 and 11 enabled for a PHOSITA.
Definiteness and Consistency (35 U.S.C. 112(b))
The rejections of claims 6 and 20 for indefiniteness are withdrawn.
In claim 6, the Applicant has resolved the inconsistency between "seed feed rate" and "crop seed rate" by amending the terminology to ensure a consistent chain of reference with the independent claim.
In claim 20, the replacement of the permissive "may include" with the closed/definite "comprises" establishes a clear structural requirement for the attributes of the crop material.
The cancellation of claims 12 and 14 renders the rejections previously associated with those claims moot.
Claim Rejections – 35 U.S.C. 103
In response to the Applicant's arguments filed, the following Examiner's response addresses why those arguments are rendered moot by the updated prior art combination (Kordick, Landphair, Chen, Chen Jiqing, Mentzer, Rodel, and Czapka) necessitated by the amended claims.
Disclosure of Node-Bearing Crop Material in a Planting Context
The Applicant previously argued that Landphair and Kordick fail to disclose a system "configured to plant a crop material having at least one of nodes and eyes" and that these references are restricted to general seed planting.
This argument is rendered moot by the inclusion of Chen, which specifically identifies "sugarcane planting" as its technical field and discusses the mechanical harvesting and planting of sugarcane stem nodes. Chen establishes that sugarcane is grown in the open air and planted side-by-side. While Chen primarily uses the term "nodes," the agronomic context confirms that sugarcane "eyes" or buds grow specifically on these stem nodes and serve as the source of new plant development. Therefore, the identification of a node in a machine-vision system inherently enables the determination of the number of eyes, satisfying the amended limitation.
Motivation to Combine General Seeding with Node Detection
The Applicant argued that a PHOSITA would lack the motivation to combine general seeding (Kordick) with specialized extraction/detection (Rodel) and would instead focus on counting "billets" rather than internal features like nodes.
However, the final rejection combination demonstrates a clear technical synergy that renders this argument unpersuasive. Precision agriculture is increasingly dependent on the fusion of machine vision and real-time control to ensure accurate deposition of material. Chen and Chen Jiqing both provide object detection algorithms (such as YOLO v4) specifically for "sugarcane stem node recognition" because the node is the biologically relevant unit for germination.
A PHOSITA would be highly motivated to integrate Chen's node-recognition logic into Kordick’s variable-rate control backbone. As established in the mapping, the effective "seed rate" for vegetative propagation is the density of viable nodes per unit area, not merely the volume of bulk billets. Therefore, substituting Kordick’s "seed population" algorithm with Chen’s image-based node count is a predictable application of specialized machine vision to a well-known agricultural objective: optimizing planting density based on agronomic value.
"Rodel is Not Associated with a Planter"
The Applicant argued that Rodel is directed to a method of extracting buds and is "not associated with a planter, much less with a system for measuring the crop seed rate".
The final rejection combination does not rely on Rodel to establish the planting environment; that environment is expressly provided by Kordick (air seed planter) and Landphair (furrow-viewing camera system). Rodel is instead cited for its technical disclosure of the structural relationships required by the amended dependent claims, such as the relationship between billet length and bud distance. Furthermore, Rodel’s teaching on using multiple sensors to compute a "three-dimensional shape" of the surface provides the technical foundation for the 3D imaging requirements of Claims 8 and 11. The use of Rodel’s surface extraction logic within a planter's machine-vision system (as established by Landphair/Mentzer) is a predictable use of known optical techniques to overcome occlusion in complex natural environments.
Implementation of Commands vs. Recommendations
Regarding the amended requirement that the system output "commands" to increase or decrease speed, the Applicant’s previous focus on the limitations of Kordick’s manual adjustments is superseded by the inclusion of Czapka. Czapka explicitly teaches an implement-based speed control system where a planter controller transmits a "speed request signal" to a vehicle controller to automatically increase or decrease ground speed based on seed-related parameters. This closes the gap between advisory "recommendations" and the claimed automated "commands," rendering the Applicant's previous arguments on this point moot.
"Unforeseeable Advantages" of Node Counting
Finally, the Applicant’s claim that node counting produces "unforeseeable advantages" regarding yield accuracy is refuted by the prior art. Both Chen and Chen Jiqing explicitly focus on node identification as the critical step for automated sugarcane seeding and cutting because the survival rate of whole-stalk planting is low and depends on the health of the seed buds. Because the prior art already identifies the node/bud as the primary determinant of "actual crop yield," the application of this metric to determine a current seed feed rate is a routine and predictable improvement in precision farming.
In summary, the combination of Kordick’s rate-control backbone, Landphair’s furrow-viewing camera, Chen’s YOLO-based node recognition, and Czapka’s automated speed-command protocol established a prima facie case of unpatentability that renders the Applicant's previous arguments moot.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OLUWABUSAYO ADEBANJO AWORUNSE whose telephone number is (571)272-4311. The examiner can normally be reached M - F (8:30AM - 5PM).
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/OLUWABUSAYO ADEBANJO AWORUNSE/Examiner, Art Unit 3662
/JELANI A SMITH/Supervisory Patent Examiner, Art Unit 3662
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