DETAILED ACTION
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 .
Status of Claims
This Office Action is in response to the application filed on 08/30/2023. Claims 1 - 20 are presently pending and are presented for examination.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/30/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1 – 2, 6 – 7, 12 - 15 are rejected under 35 U.S.C. 103 as being unpatentable over US20180325031A1 (hereinafter, “Rotole”), and further in view of US20230358707A1 (hereinafter, “Honeyman”), and further in view of US20230049727A1 (hereinafter, “Hamilton”).
6. Regarding claims 1 & 13, Rotole teaches a system for adjusting a roller assembly on a windrower implement to improve drying rate for a harvested crop, comprising ([0050], [0061] – [0064], [0068] Fig. 3): Rotole teaches actuators (176) that adjust the conditioner rollers (140 & 148) for gap-adjustments on the windrower (100) [0061] – [0064]. Rotole also teaches on improving a drying rate for the crops. As the crop material (136) passes through the conditioner rollers, the conditioning may promote the drying of the crop material (136) [0050], [0068].
7. Rotole further does not explicitly teach a sensor array that detects a condition of the harvested crop;
an implement controller that receives sensor data from the sensor array, the sensor data indicative of one or more crop characteristics, the implement controller comprising:
However, Honeyman in the same field of endeavor, teaches a sensor array that detects a condition of the harvested crop ([0027], [0034] Fig. 3 – 4); As the examiner, “sensor array” is being interpreted as a sensor that comprises an internal array of sensing elements. Honeyman teaches a measuring device (106) that generates an electric field (108). When this electric field response curve responds in certain ways to crop material, the properties of how the response curve has changed gives information on the moisture, the mass, and the properties of the crop material (102). As shown in figures 3 – 4, the measuring device may have a plurality of electrodes arranged in an array pattern.
an implement controller that receives sensor data from the sensor array, the sensor data indicative of one or more crop characteristics, the implement controller comprising ([0038] Fig. 5): A controller (517) is shown in figure 5 that is located on a windrower (510).
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole with the teachings of Honeyman, to change the ground speed of the tractor based on obtained data of crop conditions.
8. Rotole teaches a computer processor; and ([0089] Fig. 9) A processor (202) is incorporated into the system.
memory that stores instructions configured to, when processed by the computer processor, generate ([0088] Fig. 9): A memory (350) is incorporated into the system.
9. Rotole further does not explicitly teach crop condition data indicative of a condition of the harvested crop; and
However, Honeyman in the same field of endeavor, teaches teach crop condition data indicative of a condition of the harvested crop; and [0043] Honeyman teaches determining a property (condition) of the crop material that is being harvested.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole with the teachings of Hamilton, to gather data on harvested crops to further use this data to make adjustments.
10. Rotole teaches actuator adjustment data indicative of an adjustment to the roller assembly in the windrower implement… [0068] Rotole teaches adjusting rollers (148 & 150) by adjusting the gap between those two rollers based on the actuators (176, 178, 180) adjustment to the rollers (148 & 150). Therefore, we can call the actuators adjusting the rollers in a specific manner actuator adjustment data.
Rotole does not explicitly teach …to meet a predetermined crop condition based at least on the crop condition data and upon a target crop dry-down characteristic; and
However, Hamilton teaches …to meet a predetermined crop condition based at least on the crop condition data and upon a target crop dry-down characteristic; and [0037], [0042] Hamilton teaches an operating parameter may be changed to have a preselected condition (predetermined crop condition) in regards to moisture content based on predicted weather conditions. Honeyman has no recitation of when it comes to incorporating anything related to a “predetermined crop condition”. Hence why Hamilton is being used instead of Honeyman. These weather conditions affect crops so inherently, this preselected condition is also based on crop condition data due to the fact the sensors (19a – 19c) detect properties of harvested crop material such as moisture content which is affected by such weather conditions.
Rotole and Hamilton are analogous art because Rotole teaches on having multiple actuators adjust the rollers based on data those actuators contain in a windrower while Hamilton teaches on having the ability to have an operating parameter that can be changed to have a preselected condition in regards to harvested crops. A person of ordinary skill would have been motivated to combine Rotole with Hamilton because this combination gives practical and predictable benefits. Combining the actuator adjustment system of a windrower with a windrower that has an operating parameter that can be changed to have a preselected condition would give the windrower capabilities of adjusting the rollers using the actuator adjustment system based on confirmed preselected sensor data to reduce burden on an operator, improve crop quality, and have automated conditioning.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Rotole and Hamilton, to modify the teachings Rotole to include the teachings of Hamilton to further cut crops more efficiently and improve harvested crop quality.
11. Rotole teaches one or more actuators that adjust the roller assembly of the windrower implement based at least on the adjustment data [0068]. Rotole teaches adjusting rollers (148 & 150) by adjusting the gap between those two rollers based on the one or more actuators (176, 178, 180) adjustment to the rollers (148 & 150). Therefore, we can call the actuators adjusting the rollers to a specific position actuator adjustment data. The adjustment of these rollers is based on the adjustment data the actuators contain.
12. Regarding claims 2 & 15, Rotole does not explicitly teach the system of claim 1, the sensor array comprising a crop constituent sensor that detects and provides constituent data indicative of one or more of: moisture content, dry matter content, acid detergent fiber (ADF) content, neutral detergent fiber (NDF) content, lignin content, metabolized energy content, and crude protein content.
However, Hamilton in the same field of endeavor, teaches the system of claim 1, the sensor array comprising a crop constituent sensor that detects and provides constituent data indicative of one or more of: moisture content [0030], dry matter content, acid detergent fiber (ADF) content, neutral detergent fiber (NDF) content, lignin content, metabolized energy content, and crude protein content Hamilton teaches sensors (19a – 19c) that are configured to detect properties of harvested crop material (crop condition data) such as the mass of the harvested crops and the moisture content of the harvested crops.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole with the teachings of Hamilton, to gather data on harvested crops to further use this data to make adjustments.
13. Regarding claim 6, Rotole does not explicitly teach the system of claim 1, the sensor data comprising one or more of: crop moisture content; crop density; crop health; acid detergent fiber (ADF) content; neutral detergent fiber (NDF) content; lignin content; metabolized energy content; crude protein content; and stem to leaf ratio of target crop.
However, Hamilton in the same field of endeavor, teaches the system of claim 1, the sensor data comprising one or more of: crop moisture content [0030]; crop density; crop health; acid detergent fiber (ADF) content; neutral detergent fiber (NDF) content; lignin content; metabolized energy content; crude protein content; and stem to leaf ratio of target crop. Hamilton teaches sensors (19a – 19c) that are configured to detect properties of harvested crop material (crop condition data) such as the mass of the harvested crops and the moisture content of the harvested crops.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole with the teachings of Hamilton, to gather data on harvested crops to further use this data to make adjustments.
14. Regarding claims 7 & 14, Rotole teaches the system of claim 1, the one or more actuators configured to adjust one or more of:
a speed of one or more sets of rollers in the roller assembly;
a pressure exerted by the one or more sets of rollers on the target crop;
a distance between each roller in the one or more sets of rollers [0062], [0095];
and a number of active sets of rollers in the roller assembly. Rotole teaches on a gap-adjustment actuator (175) that can adjust the distance (gap-adjustment) between the first conditioner roller (148) and the second conditioner roller (150).
15. Regarding claim 12, Rotole teaches the system of claim 1, comprising a user interface configured to:
display one or more of: the target crop dry-down characteristic; the harvested crop condition, and actuator adjustment data; and
to receive user input indicative of one or more of: the target crop dry-down characteristic, and the actuator adjustment data [0104], [0107]. Rotole teaches on a user interface (360). This user interface (360) will contain and display data that relates to actuator adjustment data because this user interface contains presets of the conditioner rollers as well as the user being able to manually re-position the implement. All these adjustments that can be done from the user interface pertains to actuator adjustment data being displayed on the user interface (360). The user interface (360) may receive user input in regards to these adjustments and calibration.
Claim(s) 3 & 16 are rejected under 35 U.S.C. 103 as being unpatentable over US20180325031A1 (hereinafter, “Rotole”), and further in view of US20230358707A1 (hereinafter, “Honeyman”), and further in view of US20230049727A1 (hereinafter, “Hamilton”), and further in view of US20170089742A1 (hereinafter, “Bruns”).
17. Regarding claims 3 & 16, Rotole as modified by Hamilton does not explicitly teach the system of claim 1, the sensor array comprising a normalized difference vegetation index (NDVI) sensing array that detects and provides plant health data indicative of a health and/or density of vegetation of the harvested crop.
However, Honeyman teaches the system of claim 1, the sensor array comprising…sensing array ([0027], [0034] Fig. 3 – 4); Honeyman teaches a measuring device (106) that generates an electric field (108). When this electric field response curve responds in certain ways to crop material, the properties of how the response curve has changed gives information on the moisture, the mass, and the properties of the crop material (102). As shown in figures 3 – 4, the measuring device may have a plurality of electrodes arranged in an array pattern.
Rotole as modified by Hamilton and Honeyman does not explicitly teach …a normalized difference vegetation index (NDVI)…that detects and provides plant health data indicative of a health and/or density of vegetation of the harvested crop.
However, Bruns in the same field of endeavor, teaches …a normalized difference vegetation index (NDVI)…that detects and provides plant health data indicative of a health and/or density of vegetation of the harvested crop ([0203] Fig. 28). Bruns teaches on using normalized difference vegetation index (NDVI) data for the non-VIRVI data (1336) in figure 28. Sensors (2036) are used to determine plant health of the harvested crops. These sensors (2036) can obtain data using NVDI to gather data in regards to disease (1346) on the harvested crops which is considered plant health data.
Honeyman and Bruns are analogous art because Honeyman teaches on a measuring device that contains arrays of electrodes within to determine properties of the harvest crop while Bruns teaches on using NDVI to detect disease data on harvested crops. Both Honeyman and Bruns address crop detection properties. It would have been obvious to seek improving crop assessment and overall harvest quality using different but complimentary sensing qualities. Since each system provides different type of diagnostic information, Honeyman measuring physical properties and Bruns measuring for disease markers, combining would reasonably expect to provide a more comprehensive and accurate characterization of the harvested crop.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Honeyman and Bruns, to modify the teachings Rotole as modified by Hamilton to include the teachings of Honeyman and Bruns, to have a more accurate characterization of the harvested crops.
Claim(s) 4 & 17 are rejected under 35 U.S.C. 103 as being unpatentable over US20180325031A1 (hereinafter, “Rotole”), and further in view of US20230358707A1 (hereinafter, “Honeyman”), and further in view of US20230049727A1 (hereinafter, “Hamilton”), and further in view of US20240012092A1 (hereinafter, “Schildknecht”).
19. Regarding claims 4 & 17, Rotole as modified by Hamilton and Honeyman does not explicitly teach the system of claim 1, the sensor array comprising an imaging sensor that captures image data of the harvested crop.
However, Schildknecht teaches the system of claim 1, the sensor array comprising an imaging sensor that captures image data of the harvested crop ([0309] Fig. 4). Schildknecht teaches optical sensors that can be arranged in an array (174) pattern as shown in figure 4. Optical sensors are sensors that capture image data. These optical sensors can be used to capture image data of harvested crops in agriculture [0196] – [0197].
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole as modified by Hamilton and Honeyman with the teachings of Schildknecht, to more accurately determine physical markers indicating any type of health issue with the crops.
Claim(s) 5 is rejected under 35 U.S.C. 103 as being unpatentable over US20180325031A1 (hereinafter, “Rotole”), and further in view of US20230358707A1 (hereinafter, “Honeyman”), and further in view of US20230049727A1 (hereinafter, “Hamilton”), and further in view of US20240012092A1 (hereinafter, “Schildknecht”), and further in view of US20130028487A1 (hereinafter, “Stager”).
21. Regarding claim 5, Rotole as modified by Hamilton, Honeyman, and Schildknecht does not explicitly teach the system of claim 4, the stored instructions further configured to, when processed by the computer processor, identify a stem to leaf ratio based at least upon the image data.
However, Stager teaches the system of claim 4, the stored instructions further configured to, when processed by the computer processor, identify a stem to leaf ratio based at least upon the image data ([0031], [0050] Fig. 4). Stager doesn’t specifically identify a leaf-to-stem ratio. The fact that it classifies stems and leaves at the pixel level means it provides the technology needed to derive and identify such a ratio using image data from cameras [0025].
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole as modified by Hamilton and Honeyman with the teachings of Stager, to prevent leaf loss and optimize drying.
Claim(s) 8 – 10, 18 - 19 are rejected under 35 U.S.C. 103 as being unpatentable over US20180325031A1 (hereinafter, “Rotole”), and further in view of US20230358707A1 (hereinafter, “Honeyman”), and further in view of US20230049727A1 (hereinafter, “Hamilton”), and further in view of US20230320249A1 (hereinafter, “Vandike”).
23. Regarding claim 8, Rotole as modified by Hamilton and Honeyman does not explicitly teach the system of claim 1, the one or more actuators configured to adjust a height and/or tilt of a header in the windrower implement.
However, Vandike in the same field of endeavor, teaches system of claim 1, the one or more actuators configured to adjust a height and/or tilt of a header in the windrower implement [0156]. Vandike teaches on having actuators that can alter the position of the front attachment (header) relative to the ground. The front attachment may be raised to reduce engagement with the ground or take it out of engaging with the ground in its entirety. This constitutes as adjusting the height of the front attachment (header).
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole as modified by Hamilton and Honeyman with the teachings of Vandike, to adjust the header accordingly based on the user’s needs.
24. Regarding claims 9 & 18, Rotole as modified by Hamilton and Honeyman do not explicitly teach the system of claim 1, comprising a crop condition map generator that uses the crop condition data indicative of a condition of the harvested crop to generate a field map indicative of a crop condition at identified locations in a field comprising the harvested crop.
However, Vandike in the same field of endeavor, teaches the system of claim 1, comprising a crop condition map generator that uses the crop condition data indicative of a condition of the harvested crop to generate a field map indicative of a crop condition at identified locations in a field comprising the harvested crop [0036]. Vandike teaches on creating an information map that has characteristics of crops present on the field from one or more in-situ sensors (208) [0038]. These characteristics include crop properties such as crop height, crop moisture, crop density, and crop state. These characteristics are considered crop conditions. This map also indicates geographic locations on the map of these characteristics of the crops. Rotole itself mentions mapping as well (Rotole [0088]). Although not necessarily a crop condition map. Rotole does mention map data that relates to a geolocation data of one or more implements for a particular location within a field. Therefore, combining Rotole’s mapping with Vandike’s information map would’ve been obvious to do.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole as modified by Hamilton and Honeyman with the teachings of Vandike, to recall specific locations of certain crop characteristics on a field after harvesting.
25. Regarding claims 10 & 19, Rotole as modified by Hamilton and Honeyman do not explicitly teach the system of claim 1, comprising a user interface disposed at an operator position, the user interface displaying information indictive of the crop condition, a map illustrating crop condition, and/or a setting of the windrower implement.
However, Vandike in the same field of endeavor, teaches the system of claim 1, comprising a user interface disposed at an operator position, the user interface displaying information indictive of the crop condition, a map illustrating crop condition, and/or a setting of the windrower implement ([0036] Fig. 2). Vandike teaches on creating an information map that has characteristics of crops present on the field from one or more in-situ sensors (208) [0038]. These characteristics include crop properties such as crop height, crop moisture, crop density, and crop state. These characteristics are considered crop conditions. This map also indicates geographic locations on the map of these characteristics of the crops. A user/operator may interact with the functional map to perform editing operations.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole as modified by Hamilton and Honeyman with the teachings of Vandike, to recall back on data that was recorded through a map and also have the operator look at a map easily assign the agricultural machine to perform operations from that same map.
Claim(s) 11 is rejected under 35 U.S.C. 103 as being unpatentable over US20180325031A1 (hereinafter, “Rotole”), and further in view of US20230358707A1 (hereinafter, “Honeyman”), and further in view of US20230049727A1 (hereinafter, “Hamilton”), and further in view of US20170086381A1 (hereinafter, “Roell”).
27. Regarding claim 11, Rotole teaches …and the stored instructions configured to generate the actuator adjustment data…the actuator adjustment data configured to provide adjustments to the roller assembly that result in the target dry-down time for the harvested crop… ([0050], [0061] – [0064], [0068], [0081] Fig. 3) Rotole teaches actuators (176) that adjust the conditioner rollers (140 & 148) for gap-adjustments on the windrower (100) [0061] – [0064]. Rotole also teaches on improving a drying rate for the crops. As the crop material (136) passes through the conditioner rollers, the conditioning may promote the drying of the crop material (136) [0050], [0068]. A sixth sensor may also be included that can measure conditions of the crop material (136). This sixth sensor can measure conditions such as the type of crop being harvested, density, and areas within the field that are wet. Due to Rotole having a sixth sensor that can measure portions of a field that are wet, the actuator adjustment assembly can be adjusted based on the measurement of how wet a field is which encompasses detecting wet crops.
Rotole does not explicitly teach the system of claim 1, the target crop dry-down characteristic indicative of a threshold crop condition that is configured to provide a target dry-down time for the harvested crop,…based on a comparison between the identified crop condition and the target crop dry-down characteristic,…
However, Roell teaches the system of claim 1, the target crop dry-down characteristic indicative of a threshold crop condition that is configured to provide a target dry-down time for the harvested crop,…based on a comparison between the identified crop condition and the target crop dry-down characteristic,… [0018], [0023] Roell teaches on detecting crop moisture levels using a moisture sensor (13). This moisture sensor is used in order to determine if the moisture level (crop condition) of the crop is within a predetermined threshold (threshold) or not. Roell also mentions using a drydown algorithm. This drydown algorithm takes in various inputs such as condition data (moisture level) and predicts how fast or how effectively the crop will drydown. This prediction of how fast/effectively the crop will dry is considered the crop dry-down time.
Rotole and Roell are analogous art because Rotole teaches an actuator assembly that can be adjusted based on certain conditions and can detect wet levels from a sixth sensor while Roell teaches on measuring moisture levels and determining if those moisture levels meet a predetermined threshold and a drydown algorithm. One of ordinary skill would have the motivation to combine these because both contain moisture level detecting abilities. Inputting Roell’s threshold comparator and drydown algorithm into Rotole would give a result that will reduce time waiting for crops to dry, adjusting capabilities, and give predictive scheduling.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Roell, to modify the teachings of Rotole as modified by Hamilton and Honeyman to include the teachings of Roell, to further reduce the time of the harvest crops drying.
Claim(s) 20 is rejected under 35 U.S.C. 103 as being unpatentable over US20180325031A1 (hereinafter, “Rotole”), and further in view of US20230358707A1 (hereinafter, “Honeyman”), and further in view of US20230049727A1 (hereinafter, “Hamilton”), and further in view of US20240012092A1 (hereinafter, “Schildknecht”), and further in view of US20170089742A1 (hereinafter, “Bruns”).
29. Regarding claim 20, Rotole teaches a system for automatically adjusting a roller assembly on a windrower implement to improve drying rate for a harvested crop, comprising one or more of ([0050], [0061] – [0064], [0068] Fig. 3): Rotole teaches actuators (176) that adjust the conditioner rollers (140 & 148) for gap-adjustments on the windrower (100) [0061] – [0064]. Rotole also teaches on improving a drying rate for the crops. As the crop material (136) passes through the conditioner rollers, the conditioning may promote the drying of the crop material (136) [0050], [0068].
30. Rotole further does not explicitly teach a sensor array that detects a condition of the harvested crop, the sensor array comprising:
However, Honeyman in the same field of endeavor, teaches a sensor array that detects a condition of the harvested crop ([0027], [0034] Fig. 3 – 4): Honeyman teaches a measuring device (106) that generates an electric field (108). When this electric field response curve responds in certain ways to crop material, the properties of how the response curve has changed gives information on the moisture, the mass, and the properties of the crop material (102). As shown in figures 3 – 4, the measuring device may have a plurality of electrodes arranged in an array pattern.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole with the teachings of Honeyman, to gather data more accurately and precisely.
31. Rotole further does not explicitly teach a crop constituent sensor that detects one or more of: moisture content, dry matter content, acid detergent fiber (ADF) content, neutral detergent fiber (NDF) content, lignin content, metabolized energy content, and crude protein content;
However, Hamilton in the same field of endeavor, teaches a crop constituent sensor that detects one or more of: moisture content [0030], dry matter content, acid detergent fiber (ADF) content, neutral detergent fiber (NDF) content, lignin content, metabolized energy content, and crude protein content; Hamilton teaches sensors (19a – 19c) that are configured to detect properties of harvested crop material (crop condition data) such as the mass of the harvested crops and the moisture content of the harvested crops.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole with the teachings of Hamilton, to gather data on harvested crops to further use this data to make adjustments.
32. Rotole further does not explicitly teach a normalized difference vegetation index (NDVI) sensing array that detects and provides plant health data indicative of a health and/or density of vegetation of the harvested crop; and
However, Honeyman teaches the system of claim 1, the sensor array comprising…sensing array ([0027], [0034] Fig. 3 – 4); As the examiner, “sensor array” is being interpreted as a sensor that comprises an internal array of sensing elements. Honeyman teaches a measuring device (106) that generates an electric field (108). When this electric field response curve responds in certain ways to crop material, the properties of how the response curve has changed gives information on the moisture, the mass, and the properties of the crop material (102). As shown in figures 3 – 4, the measuring device may have a plurality of electrodes arranged in an array pattern.
Rotole as modified by Hamilton and Honeyman does not explicitly teach …a normalized difference vegetation index (NDVI)…that detects and provides plant health data indicative of a health and/or density of vegetation of the harvested crop.
However, Bruns in the same field of endeavor, teaches …a normalized difference vegetation index (NDVI)…that detects and provides plant health data indicative of a health and/or density of vegetation of the harvested crop ([0203] Fig. 28). Bruns teaches on using normalized difference vegetation index (NDVI) data for the non-VIRVI data (1336) in figure 28. Sensors (2036) are used to determine plant health of the harvested crops. These sensors (2036) can obtain data using NVDI to gather data in regards to disease (1346) on the harvested crops which is considered plant health data.
Honeyman and Bruns are analogous art because Honeyman teaches on a measuring device that contains arrays of electrodes within to determine properties of the harvest crop while Bruns teaches on using NDVI to detect disease data on harvested crops. Both Honeyman and Bruns address crop detection properties. It would have been obvious to seek improving crop assessment and overall harvest quality using different but complimentary sensing qualities. Since each system provides different type of diagnostic information, Honeyman measuring physical properties and Bruns measuring for disease markers, combining would reasonably expect to provide a more comprehensive and accurate characterization of the harvested crop.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Honeyman and Bruns, to modify the teachings Rotole as modified by Hamilton to include the teachings of Honeyman and Bruns, to have a more accurate characterization of the harvested crops.
33. Rotole further does not explicitly teach an imaging sensor that captures image data of the harvested crop;
However, Schildknecht teaches an imaging sensor that captures image data of the harvested crop ([0309] Fig. 4). Schildknecht teaches optical sensors that can be arranged in an array (174) pattern as shown in figure 4. Optical sensors are sensors that capture image data. These optical sensors can be used to capture image data of harvested crops in argriculture [0196] – [0197].
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole as modified by Hamilton and Honeyman with the teachings of Schildknecht, to more accurately determine physical markers indicating any type of health issue with the crops.
34. Rotole further does not explicitly teach an implement controller that receives sensor data from the sensor array, the sensor data indicative of one or more crop characteristics, the implement controller comprising:
However, Honeyman in the same field of endeavor, teaches an implement controller that receives sensor data from the sensor array, the sensor data indicative of one or more crop characteristics, the implement controller comprising: ([0038] Fig. 5): A controller (517) is shown in figure 5 that is located on a windrower (510).
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole with the teachings of Honeyman, to gather data more accurately and precisely.
35. Rotole teaches a computer processor; and ([0089] Fig. 9) A processor (202) is incorporated into the system.
memory that stores instructions configured to, when processed by the computer processor, generate ([0088] Fig. 9): A memory (350) is incorporated into the system.
36. Rotole does not explicitly teach crop condition data indicative of a condition of the harvested crop comprising one or more of:
constituents of the harvested crop;
health of the harvested crop; and
plant to stem ratio of the harvested crop;
However, Bruns in the same field of endeavor, teaches crop condition data indicative of a condition of the harvested crop comprising one or more of:
constituents of the harvested crop;
health of the harvested crop ([0203] Fig. 28); and
plant to stem ratio of the harvested crop; Bruns teaches on using normalized difference vegetation index (NDVI) data for the non-VIRVI data (1336) in figure 28. Sensors (2036) are used to determine plant health of the harvested crops. These sensors (2036) can obtain data using NVDI to gather data in regards to disease (1346) on the harvested crops which is considered plant health data.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of Rotole with the teachings of Bruns, to accurately assess crop health as it is being harvested.
37. Rotole further does not explicitly teach actuator adjustment data indicative of an adjustment to the roller assembly in the windrower implement to meet a predetermined crop condition based at least on the crop condition data and upon a target crop dry-down characteristic,
Rotole does not explicitly teach …to meet a predetermined crop condition based at least on the crop condition data and upon a target crop dry-down characteristic,
However, Hamilton teaches …to meet a predetermined crop condition based at least on the crop condition data and upon a target crop dry-down characteristic [0037], [0042], Hamilton teaches an operating parameter may be changed to have a preselected condition (predetermined crop condition) in regards to moisture content based on predicted weather conditions. Honeyman has no recitation of when it comes to incorporating anything related to a “predetermined crop condition”. Hence why Hamilton is being used instead of Honeyman. These weather conditions affect crops so inherently, this preselected condition is also based on crop condition data due to the fact the sensors (19a – 19c) detect properties of harvested crop material such as moisture content which is affected by such weather conditions.
Rotole and Hamilton are analogous art because Rotole teaches on having multiple actuators adjust the rollers based on data those actuators contain in a windrower while Hamilton teaches on having the ability to have an operating parameter that can be changed to have a preselected condition in regards to harvested crops. A person of ordinary skill would have been motivated to combine Rotole with Hamilton because this combination gives practical and predictable benefits. Combining the actuator adjustment system of a windrower with a windrower that has an operating parameter that can be changed to have a preselected condition would give the windrower capabilities of adjusting the rollers using the actuator adjustment system based on confirmed preselected sensor data to reduce burden on an operator, improve crop quality, and have automated conditioning.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Rotole and Hamilton, to modify the teachings Rotole to include the teachings of Hamilton to further cut crops more efficiently and improve harvested crop quality.
38. Rotole teaches wherein the adjustment comprises and adjustment to a distance between rollers in the roller assembly; and [0062], [0095] Rotole teaches on a gap-adjustment actuator (175) that can adjust the distance (gap-adjustment) between the first conditioner roller (148) and the second conditioner roller (150).
39. Rotole teaches one or more actuators that adjust the roller assembly of the windrower implement based at least on the adjustment data [0068]. Rotole teaches adjusting rollers (148 & 150) by adjusting the gap between those two rollers based on the one or more actuators (176, 178, 180) adjustment to the rollers (148 & 150). Therefore, we can call the actuators adjusting the rollers to a specific position actuator adjustment data. The adjustment of these rollers is based on the adjustment data the actuators contain.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID MESQUITI OVALLE JR. whose telephone number is (571)272-6229. The examiner can normally be reached Monday - Friday 7:30am - 5pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Erin Piateski can be reached on (571) 270-7429. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DAVID MESQUITI OVALLE/Examiner, Art Unit 3669
/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669