DETAILED ACTION
The applicant’s response, from 27 April 2026, has been fully considered. Amendments to the claims, from 27 April 2026, were received and entered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
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 Status
Claim 5 is cancelled.
Claims 16-20 are newly added.
Claims 1-4 and 6-20 are currently pending and under examination herein.
Claims 1-4 and 6-20 are rejected.
Priority
Applicant claims foreign priority to EP19208777.3 filed 13 November 2019 and EP20174872.0 filed 15 May 2020. Applicant also claims priority as a 371 of PCT/EP2020/080623 filed 02 November 2020. A certified copy of EP19208777.3 was not found to be submitted. In this action, claims 1-4 and 6-20 are examined as though they had an effective filing date of 13 November 2019. In future actions, the effective filing date of one or more claims may change, due to amendments to the claims, or further analysis of the disclosure(s) of the priority application(s).
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 05/11/2022, 11/26/2024, and 07/21/2025 were in compliance with the provisions of 37 CFR 1.97. One reference (Patent Application 20190174739) was lined through on the IDS filed on 07/21/2025 as this reference was previously listed in the IDS filed on 05/11/2022. Accordingly, the information disclosure statements were considered by the examiner.
Drawings
The drawings filed 11 May 2022 are accepted.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: An electronic device configured to perform the steps of claim 1 in claim 14.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. In order to perform the steps of the method of claim 1, the electronic device is considered a generic computing system in communication with a sequencing device. Structure is indicated in the specification for the computing system and sequencing device (Paragraph 0201 of the published specification (US 20220386583 A1)). This is also a sufficient algorithm provided to perform the steps for the given the structure.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The previously issued 35 USC 112(b) rejection is withdrawn in response to the amendments to the claims. A new 112(b) rejection has been made in response to the amended claims.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 15 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 15 recites a non-transitory computer-readable medium having instructions encoded thereon that, when executed by a processing device, cause the processing device to carry out the method steps of claim 1. The method of claim 1 recites performing, in-situ using the sensor arrangement connected at a sensor interface, genotyping of the at least one relevant harmful organism from an environmental sample. While the specification provides support for sequencing devices/sensors, there is no structure currently recited by the claim that can fulfill the function of genotyping a sample, as this cannot be performed by a computer-readable medium. Therefore the metes and bounds of the claim are unclear rendering the claim indefinite.
Claim Rejections - 35 USC § 101
The previously issued 35 USC 101 rejection is withdrawn in response to applicant’s arguments (see response to arguments below).
Response to arguments – 35 USC 101
Applicant’s argument was found to be persuasive that the limitation of Claim 1, “processing the result signal, using the electronic device, for determining whether the one or more of the at least one relevant harmful organism is present in the environmental sample”, is an additional element and, in the context of an agricultural production system, constitutes a practical application. Therefore, the additional elements integrate the judicial exceptions into a practical application (Step 2A, Prong Two: YES).
Claim Rejections - 35 USC § 103
The previously issued 35 USC 103 rejection is withdrawn in response to applicant’s arguments (see response to arguments below the rejection). However, a new 35 USC 103 rejection has made based against the amended claims (see below).
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.
Claims 1-2, 4, and 7-20 are rejected under 35 U.S.C. 103 as being unpatentable over Cutter (US 20170258005 A1), in view of Kain et al. (US 20140127792 A1), and in further view of Shaffer (2019, Proceedings of the National Academy of Sciences, Vol. 116, No. 9: 3351-3353). Italicized text from reference art.
The applicable claims include:
Claim 1. A computer-implemented method comprising: (i) receiving, at an electronic device, a crop data indicative of the type of a crop; (ii) receiving, at the electronic device, a region data indicative of at least one harmful organism that may be present at or around the location of the crop; (iii) selecting from a database, using the electronic device, a sensor arrangement suitable for selectively genotyping at least one relevant harmful organism; wherein the at least one relevant harmful organism is among the at least one harmful organism, and wherein the selection is performed in response to the crop data and the region data; (iv) performing, in-situ using the sensor arrangement connected at a sensor interface, genotyping of the at least one relevant harmful organism from an environmental sample obtained from a crop site; (v) generating a result signal via the sensor arrangement at the sensor interface; and processing the result signal, using the electronic device, for determining whether the one or more of the at least one relevant harmful organism is present in the environmental sample.
Claim 2. The method according to claim 1, wherein the sensor arrangement is suitable for in-situ genotyping the at least one relevant harmful organism.
Claim 4. The method according to claim 1, wherein the method further comprises outputting, via a human-machine interface functionally coupled to the electronic device, information related to the sensor arrangement suitable for genotyping the at least one relevant harmful organism.
Claim 7. The method according to claim 1, wherein the method further comprises: generating a site result data, using the electronic device, by combining the processed result signal and the location data of the crop site where the environmental sample was collected; storing, in at least one database, the site result data; combining data from a plurality of the site result data to obtain a field map representative of the territorial spread of any of the one or more relevant organisms.
Claim 8. The method according to claim 7, wherein the method further comprises determining, by analyzing the field map via the electronic device, at least one site where another measurement or detection is required.
Claim 9. The method according to claim 1, wherein the method further comprises: determining using the electronic device, in response to any of the crop data, the region data, and the selected sensor arrangement; a sampling method for collecting the environmental sample.
Claim 10. The method according to claim 1, wherein the method further comprises: determining, in response to the result signal or the processed result signal, a treatment method for controlling at least one of the at least one relevant harmful organism present on the crop site.
Claim 11. The method according to claim 7, wherein the method further comprises: determining, by analyzing the field map via the electronic device, a treatment method for controlling at least one or more harmful organisms present on the crop site.
Claim 12. The method according to claim 11, comprising the step of providing, using the electronic device, the information on the treatment method as a recommendation to a user.
Claim 13. The method according to claim 11, wherein the method further comprises: performing a treatment in accordance to the treatment method to control the at least one of the at least one relevant harmful organism detected on the crop site.
Claim 14. An electronic device configured to perform the steps of claim 1.
Claim 15. A non-transitory computer-readable medium having instructions encoded thereon that, when executed by a processing device, cause the processing device to carry out the method steps of claim 1.
Claim 16. The method according to claim 1, wherein the database comprises selectivity data for each sensor, the selectivity data being indicative of the specific organism that each individual sensor can detect.
Claim 17. The method according to claim 1, wherein the sensor arrangement is selected such that the sensor arrangement can reliably selectively detect each harmful organism that is determined to be relevant.
Claim 18. The method according to claim 1, wherein the sensor arrangement includes a sequence-specific detection tool based on a hybridization of a probe DNA- or RNA-molecule with a sequence to be identified.
Claim 19. The method according to claim 1, wherein the sensor arrangement is at least partially based on nanopore technology, microarray technology, a graphene biosensor, a microfluidics device, or a fast PCR system.
Claim 20. The method according to claim 1, wherein the sensor arrangement is selected based on availability of the sensors, cost of the sensor or of the sensor arrangement that is to be used, or speed of sensing.
Regarding Claim 1, Cutter teaches (Claim 1.i) receiving, at a device, data indicative of the crop type (Paragraph 0028: the central analytics computing system receives information from a mobile-monitoring device, a static monitoring device, the pod, the mobile-deployment device, and/or other sources; Paragraph 0031: A network may be used to facilitate communication between the elements of system; Paragraph 0033: information regarding a field (e.g., crop type, crop density, planting orientation, location, crop history, etc.) may be stored in the data store). Cutter also teaches (Claim 1.ii) receiving, at the device, a region data indicative of a harmful organism (e.g. pest) that may be present at or around the location of the crop (Paragraph 0028: The information may indicate that a portion of an agricultural field, such as a first portion, is infested with a foreign species of plant, infested with insects, is showing signs of drought, requires fertilizer, etc.). Cutter also teaches (Claim 1.iii) a database of sensors and associated information (Page 6, Chart 1: The description column contains multiple sensors). Additionally, Cutter teaches the methods are computer based (Paragraph 0006: Determination may be carried out by a distributed computer network; Paragraph 0027: As illustrated, the central analytics computing system is one computer, but it may be multiple computers).
Regarding Claim 7, Cutter teaches generating a site result data by combining the processed result signal and the location data of the crop site where the environmental sample was collected; storing, in a database, the site result data; combining data from a plurality of the site result data to obtain a field map representative of the spread of any of the relevant organisms (Paragraph 0033: information regarding a field (e.g., crop type, crop density, planting orientation, location, crop history, etc.) may be stored in the data store; Paragraph 0090: data may be stored using a directory service, a web portal, a mailbox service, an instant messaging store, or a compiled networking service for managing preloaded and/or updated maps (the distinction between preloaded and updated maps is interrupted as the information gathered from the samples are added to/build the map) of agricultural fields; Paragraph 0006: In a particular aspect, drones, static monitoring devices, and agricultural equipment gather data on agricultural fields, or portions thereof. For example, moisture data, photographs, wind speed, temperature, etc., may be gathered (i.e. additional information is coming from additional samples). This information is then used to determine whether a portion(s) of the monitored field has a potential health problem (health problems include the detection of a harmful organism); Paragraph 0028: In aspects of the technology, the central analytics computing system uses this information to make determinations about which portions of an agricultural field to monitor and/or treat). Information that includes sampling to detect the presence of a harmful organism from different locations indicate spread. In addition to cutter describing updating a map with spatially explicit pest presence information, see rejection with Santos et al. below.
Regarding Claim 8, Cutter teaches determining, by analyzing the field map via the device, a site where another measurement or detection is required (Paragraph 0035: the monitoring engine may make a determination that a portion of a field should be further monitored). See Regarding Claim 7 for how this determination is related to the field map.
Regarding Claim 9, Cutter teaches determining in response to the crop data, the region data, or the selected sensor arrangement; a sampling method (Paragraph 0054: instructions related to how the information should be captured are sent to the one or more devices capturing the information. Instructions may include a number of data points (e.g., images, soil samples, etc.) to collect, time of day to collect information, location to collect information, etc.). Location data (i.e. region data) was received by the device (See regarding claim 1). Because the location data is received and samples are collected from multiple locations (see regarding claims 7), instructions involving where to collect samples is interpreted incorporating the region data in the determining the sampling method. Instructions are interrupted as equivalent to a method.
Regarding Claim 11, Cutter teaches determining, by analyzing the field map, a treatment method for controlling harmful organisms present on the crop site. (Paragraph 0006: This information is then used to determine whether a portion(s) of the monitored field has a potential health problem (health problems are spatially explicit and include the detection of a pest); Paragraph 0028: the central analytics computing system uses this information to make determinations about which portions of an agricultural field to monitor and/or treat; Paragraph 0039: The action determination engine may determine to deploy pesticide, continue monitoring the field, and/or deploy another remedy. The determination of the remedy may be based on the health problem and/or user preference). See Regarding Claim 7 for how this determination is related to the field map. Also see Regarding Claim 10 for recommending a treatment.
Regarding Claim 12, Cutter teaches providing, using the device, the information on the treatment method as a recommendation to a user. (Paragraph 0028: The information regarding what portion of the agricultural field requires treatment, as well as the type of treatment, may be sent to a mobile-deployment device). Figure 1 shows the information coming from the network to a mobile-deployment device (118). Figure 10A shows the network is also in communication with numerous display devices. Therefore it would be obvious to the display the treatment.
Regarding Claim 13, Cutter teaches performing a treatment in accordance to the treatment method to control the at least one of the at least one relevant harmful organism detected on the crop site (Paragraph 0119: The identified portions, or treatment instructions, may be sent to the controller to treat certain portions of the field; Paragraph 0006: Treatment may be carried out by delivering a treatment profile to a drone, which drone may carry out the treatment profile by treating an area of the field (such as by, for example, spraying a portion of a field with an herbicide)).
Regarding Claim 14, Cutter teaches an electronic device configured to perform the steps of claim 1 (Paragraph 0021: FIG. 1 illustrates a networked system for monitoring, analyzing, and treating agricultural fields. As illustrated, the system includes pods, sensors, and unmanned devices (e.g., drones) to gather and communicate information related to agricultural fields). See Regarding Claim 1 for the steps of claim 1.
Regarding Claim 15, Cutter teaches a non-transitory computer-readable medium having instructions encoded thereon that, when executed by a processing device, cause the processing device to carry out the method steps of claim 1 (Paragraph 0093: The software, firmware, or similar sequence of computer instructions may be encoded and stored upon a computer readable storage medium). See Regarding Claim 1 for the steps of claim 1. Additionally, the system as implemented on describes devices can be interpreted as utilizing generic computing devices, which inherently contain non-transitory computer-readable medium and at least one processor.
Cutter does not teach selecting from a database, using the electronic device, a sensor arrangement suitable for selectively genotyping at least one relevant harmful organism; wherein the at least one relevant harmful organism is among the at least one harmful organism, and wherein the selection is performed in response to the crop data and the region data (Claim 1.iii). Cutter also does not teach performing, in-situ using the sensor arrangement connected at a sensor interface, genotyping of the at least one relevant harmful organism from an environmental sample obtained from a crop site (Claim 1.iv). Cutter also does not teach generating a result signal via the sensor arrangement at the sensor interface; and processing the result signal, using the electronic device, for determining whether the one or more of the at least one relevant harmful organism is present in the environmental sample (Claim 1.v). Cutter also does not teach the sensor arrangement is suitable for in-situ genotyping the at least one relevant harmful organism (Claim 2). Cutter also does not teach outputting, via a human-machine interface functionally coupled to the electronic device, information related to the sensor arrangement (Claim 4). Cutter also does not teach determining, in response to the result signal or the processed result signal, a treatment method for controlling at least one of the at least one relevant harmful organism present on the crop site (Claim 10). Cutter also does not teach the database comprises selectivity data for each sensor, the selectivity data being indicative of the specific organism that each individual sensor can detect (Claim 16). Cutter also does not teach the sensor arrangement is selected such that the sensor arrangement can reliably selectively detect each harmful organism that is determined to be relevant (Claim 17). Cutter also does not teach the sensor arrangement includes a sequence-specific detection tool based on a hybridization of a probe DNA- or RNA-molecule with a sequence to be identified (Claim 18). Cutter also does not teach the sensor arrangement is at least partially based on nanopore technology, microarray technology, a graphene biosensor, a microfluidics device, or a fast PCR system (Claim 19). Cutter also does not teach the sensor arrangement is selected based on availability of the sensors, cost of the sensor or of the sensor arrangement that is to be used, or speed of sensing (Claim 20).
Regarding Claim 1, Kain et al. teach (Claim 1.iii) selecting from a database, using the electronic device, a sensor arrangement suitable for selectively genotyping at least one relevant harmful organism; wherein the at least one relevant harmful organism is among the at least one harmful organism, and wherein the selection is performed in response to the crop data and the region data (Paragraph 0037: The controller may provide a user interface that guides an operator through a series of setup options. For example, upon receiving a sample the operator may specify information about the sample (desired assay types, priority information, sample preparation information, patient information, organism, date or time of sample collection, location of sample collection, circumstances of sample collection, suspected sample characteristics, etc.) and may select from available sequencing devices that may be appropriate. Accordingly, even though the controller may be configured to match the sample to the sequencing device according to a rules-based protocol, the operator may also add conditions or parameters that override the protocol). The selection between multiple options considering the numerous data considers makes it obvious that a database contains the options related to the sections (also see Cutter teaching of a database of sensors in Claim 1.iii). The sequencing devices indicated by the art are considered synonymous the sensor arrangements suitable for selectively genotyping at least one relevant harmful organism
Regarding Claim 16, Kain et al. teach the database comprises selectivity data for each sensor indicative of the specific organism that each sensor can detect (Paragraph 0037: the operator may specify information about the sample (desired assay types, priority information, sample preparation information, patient information, organism, date or time of sample collection, location of sample collection, circumstances of sample collection, suspected sample characteristics, etc.) and may select from available sequencing devices that may be appropriate). The organism of the sample is known and used to select a sensor that is appropriate. This is interpreted as equivalent to selecting a sensor based on sensitivity data because if the sensor could not detect the organism, it would not be appropriate.
Regarding Claim 17, Kain et al. teach the sensor arrangement is selected such that it can reliably selectively detect each harmful organism that is determined to be relevant (Paragraph 0037: the operator may specify information about the sample (desired assay types, priority information, sample preparation information, patient information, organism, date or time of sample collection, location of sample collection, circumstances of sample collection, suspected sample characteristics, etc.) and may select from available sequencing devices that may be appropriate). The organism of the sample is known and used to select a sensor that is appropriate. This is interpreted as equivalent to selecting a sensor based on sensitivity data. This is used to identify a relevant harmful organism (Paragraph 0040: In one example, a sequencing run may determine is a sample is positive for salmonella DNA. The runs may proceed until identification is possible). Additionally, a device that determines an identity of an organism based on a conserved genetic sequence is capable of being used for any organism as the components of the sequence (i.e. nucleotide base) are the same across all organisms (also see teachings of Shaffer for teachings on the use of the CO1 barcoding region).
Regarding Claim 18, Kain et al. teach the sensor arrangement includes a sequence-specific detection tool based on a hybridization of a probe DNA- or RNA-molecule with a sequence to be identified (Paragraph 0045: In the depicted embodiment, the biological sample may be loaded into the sample processing device as a sample slide that is detected to generate sequence data. For example, reagents that interact with the biological sample may fluoresce at particular wavelengths in response to an excitation beam generated by a detection module and thereby return radiation for imaging. For instance, the fluorescent components may be generated by fluorescently tagged nucleic acids that hybridize to complementary molecules of the components or to fluorescently tagged nucleotides that are incorporated into an oligonucleotide using a polymerase). Fluorescently tagged nucleic acids (a probe) that hybridize to complementary molecules is interpreted as based on hybridization.
Regarding Claim 19, Kain et al. teach the sensor arrangement is at least partially based on nanopore technology, microarray technology, a graphene biosensor, a microfluidics device, or a fast PCR system (Paragraph 0038: Some embodiments can utilize nanopore sequencing).
Regarding Claim 20, Kain et al. teach the sensor arrangement is selected based on availability of the sensors, cost of the sensor or of the sensor arrangement that is to be used, or speed of sensing (Paragraph 0006: The techniques relate to a controller or processor-based device that assigns biological samples to sequencing devices based on parameters associated with the sample (e.g., type of assay to be performed, a priority designation) and parameters associated with the sequencing device (e.g., estimated availability, sequencing capabilities).
Kain et al. does not teach performing, in-situ using the sensor arrangement connected at a sensor interface, genotyping of the at least one relevant harmful organism from an environmental sample obtained from a crop site (Claim 1.iv). Kain et al. also does not teach generating a result signal via the sensor arrangement at the sensor interface; and processing the result signal, using the electronic device, for determining whether the one or more of the at least one relevant harmful organism is present in the environmental sample (Claim 1.v). Kain et al. also does not teach the sensor arrangement is suitable for in-situ genotyping the at least one relevant harmful organism (Claim 2). Kain et al. also does not teach outputting, via a human-machine interface functionally coupled to the electronic device, information related to the sensor arrangement (Claim 4). Kain et al. also does not teach determining, in response to the result signal or the processed result signal, a treatment method for controlling at least one of the at least one relevant harmful organism present on the crop site (Claim 10).
Regarding Claim 1, Shaffer teaches (Claim 1.iv) performing, in-situ using the sensor arrangement connected at a sensor interface, genotyping of the at least one relevant harmful organism from an environmental sample obtained from a crop site (Page 1, Column 1, Paragraph 1: Their plan was unprecedented: sequence the whole genome of the plant material to detect all potential viruses—and do so in a single day on a farm; Page 2, Column 2, Paragraph 5: They confirmed plants that tested positive through MinION for cassava viruses were also found to be positive through PCR; Page 2, Column 2, Paragraph 6: by the time they finished in Kenya, they had whittled the process down to 2 to 3 hours; Page 3, Column 1, Paragraph 1: The data analysis of the genome is conducted by using another Oxford Nanopore Technologies device, a book-sized computer called MinIT, a module that plugs into MinION and can be controlled via laptop or tablet). Shaffer also teaches (Claim 1.v) generating a result signal via the sensor arrangement at the sensor interface; and processing the result signal, using the electronic device, for determining whether the one or more of the at least one relevant harmful organism is present in the environmental sample. (Page 2, Column 2, Paragraph 5: They confirmed plants that tested positive through MinION for cassava viruses; Page 3, Column 1, Paragraph 1: The data analysis of the genome is conducted by using another Oxford Nanopore Technologies device, a book-sized computer called MinIT, a module that plugs into MinION and can be controlled via laptop or tablet). A positive results indicates a signal must have been generated via the sensor arrangement and processed given the sensor in combination with an interface was used for the test.
Regarding Claim 2, Shaffer teaches the sensor arrangement is suitable for in-situ genotyping the at least one relevant harmful organism (Page 2, Column 2, Paragraph 5: They confirmed plants that tested positive through MinION for cassava viruses were also found to be positive through PCR; Page 2, Column 2, Paragraph 6: by the time they finished in Kenya, they had whittled the process down to 2 to 3 hours; Page 3, Column 1, Paragraph 1: The data analysis of the genome is conducted by using another Oxford Nanopore Technologies device, a book-sized computer called MinIT, a module that plugs into MinION and can be controlled via laptop or tablet). The sensor is interpreted as suitable because it was successfully used for in-situ genotyping to detect the pest.
Regarding Claim 4, Shaffer teaches outputting, via an interface coupled to the device, information related to the sensor arrangement (Page 2, Column 2, Paragraph 5: They confirmed plants that tested positive through MinION for cassava viruses were also found to be positive through PCR; Page 2, Column 2, Paragraph 6: by the time they finished in Kenya, they had whittled the process down to 2 to 3 hours; Page 3, Column 1, Paragraph 1: The data analysis of the genome is conducted by using another Oxford Nanopore Technologies device, a book-sized computer called MinIT, a module that plugs into MinION and can be controlled via laptop or tablet). The laptop or tablet connected to the sensor is interpreted as that human-machine interface functionally coupled to the electronic device, which provides the result and is used to control the sensor.
Regarding Claim 10, Shaffer teaches determining, in response to the result signal or the processed result signal, a treatment method for controlling the relevant harmful organism present (Page 3, Column 1, Paragraph 2: First, the researchers checked the status of those healthy plants. “We were hoping that we wouldn’t find virus, but we did,” says Boykin. Whether the plant has symptoms or not, if the virus is present, even in low levels, farmers will need to replant with fully virus-free cuttings). The virus was detected by a genotyping sensor (See Claim 1.iv and i.v). Replanting is interpreted as the determined treatment.
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to combine the methods of Cutter, Kain et al., and Shaffer. Cutter teaches pathogens are important to detect/identify in agriculture systems (Paragraph 0002: drought, floods, fungus, disease, pests, weeds, and erosion are common challenges present in the practice of agriculture; Paragraph 0003: infestations that begin in one area of a field or property can quickly spread if not detected and treated in a timely fashion). Cutter teaches field management involves sample management (Paragraph 0054: Instructions may include a number of data points (e.g., images, soil samples, etc.) to collect, time of day to collect information, location to collect information, etc.). Kain et al. teach their methods are applicable to managing biological samples (Paragraph 0005: The present disclosure provides significant improvements in the field of nucleic acid sequencing, especially with regard to biological sample management methods). This includes samples related to the identification of pathogens (Paragraph 0040: for example, if it becomes apparent from sequencing data that the first sample contained a fast acting pathogen that should be rapidly diagnosed in the other samples. In one example, a sequencing run may determine is a sample is positive for salmonella DNA. The runs may proceed until identification is possible). Shaffer teaches methods to rapidly identify pathogens in agricultural fields (Page 3351, Column 1, Paragraph 2: But within a few hours, a group of researchers, part of the Cassava Virus Action Project, determined what viruses infected the cassava crops on the farm and, more importantly, alerted farmers they would need to plant new crops that are resistant to the viruses they found; Page 3351, Column 2, Paragraph 1: We’re able to show the farmer in a single day, what their crops are infected with). Therefore, it would have been obvious to someone of ordinary skill in the art at the time of the effective filling date to combine the methods from the references indicated above. Furthermore, one of ordinary skill in the art would predict that the methods taught by Cutter, Kain et al., and Shaffer could be readily combined a reasonable expectation of success because Shaffer demonstrates how DNA sequencing techniques (as from Kain et al.) function effectively for identifying pathogens in agricultural fields (as from Cutter). Accordingly, 1-2, 4, and 7-20 taken as a whole would have been prima facie obvious before the effective filing date and are rejected under 35 U.S.C. 103.
Claims 1-4 and 7-20 are rejected under 35 U.S.C. 103 as being unpatentable over Cutter, as applied to Claims 1-2, 4, and 7-20 above, in view of Kain et al., as applied to Claims 1-2, 4, and 7-20 above, and in further view of Shaffer, as applied to Claims 1-2, 4, and 7-20 above, and Cho et al. (2008, Journal of Asia-Pacific Entomology, Vol. 11: 117–121). Italicized text from reference art.
The applicable claims include:
Claims 1-2, 4, and 7-20 are displayed above
Claim 3. The method according to claim 1, wherein the method is applied for detecting a DNA-sequence that is indicative of a pesticide resistance, and wherein the sensor arrangement is configured to detect the DNA-sequence that is indicative of the pesticide resistance.
Regarding Claims 1-2, 4, and 7-20, the limitations are taught by Cutter, Kain et al., and Shaffer as indicating above.
Cutter, Kain et al., and Shaffer do not teach the limitations of claim 3.
Regarding Claim 3, Cho et al. teach detecting a DNA-sequence that is indicative of a pesticide resistance, and wherein the sensor arrangement is configured to detect the DNA-sequence that is indicative of the pesticide resistance. (Page 118, Column 2, Paragraph 3: A partial sodium channel sequence was determined for three H. virescens strains. DNA preparations from 109 individual moths were used to amplify the IS6 and IIS6 regions of hscp. A comparison of the aligned nucleotide sequences of the hscp locus of the Woodrow strain, the PTJ strain, and the Dalzell strain revealed two synonymous mutations). The detection of kdr resistance genes in a crop pest can be accomplished by any sequencing method including as used by Kain et al. and Shaffer (see reason to combine).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to combine the methods of Cho et al. with Cutter, Kain et al., and Shaffer. Cho et al. teach methods for improving agricultural pest management, as in deciding to use an insecticide, (as from Cutter and Shaffer) using genetic sequencing (as from Kain et al. and Shaffer) by evaluating the effectiveness of its primary management strategy (Page 1, Column 1, Paragraph 1: Since 1980, pyrethroid has been used to control tobacco budworm, but this pest has subsequently developed resistance to pyrethroid. Resistance to insecticides is usually conferred by genes controlling penetration, detoxification, or sensitivity of the targeted protein; Page 120; Column 1, Paragraph 3: In this study, a new Hpy allele was found in the Woodrow and Dalzell strains. Because this mutation is strongly associated with the mutation of L1029H in IIS6 region, the new Hpy3-1 allele may be linked to pyrethroid resistance). Therefore, it would have been obvious to someone of ordinary skill in the art at the time of the effective filling date to combine the methods from the references indicated above. Furthermore, one of ordinary skill in the art would predict that the methods taught by Cho et al., Cutter, Kain et al., and Shaffer could be readily combined with a reasonable expectation of success because the genes identified by the sequencing techniques of Cho et al. could also be identified by the sequencing techniques of Kain et al. and Shaffer, as there are no structural characteristics of the genes that would prevent them from being sequenced by a particular sequencing method. Accordingly, 1-4 and 7-20 taken as a whole would have been prima facie obvious before the effective filing date and are rejected under 35 U.S.C. 103.
Claims 1-2, 4, and 6-20 are rejected under 35 U.S.C. 103 as being unpatentable over Cutter, as applied to Claims 1-2, 4, and 7-20 above, in view of Kain et al., as applied to Claims 1-2, 4, and 7-20 above, and in further view of Shaffer, as applied to Claims 1-2, 4, and 7-20 above, and Santos et al. (2011, Molecular Ecology Resources, Vol. 11: 56-59). Italicized text from reference art.
The applicable claims include:
Claims 1-2, 4, and 7-20 are displayed above
Claim 6. The method according to claim 1, wherein the method further comprises processing the result signal, using the electronic device, for also determining whether an at least one benign organism is present in the environmental sample.
Regarding Claims 1-2, 4, and 7-20, the limitations are taught by Cutter, Kain et al., and Shaffer as indicating above.
Cutter, Kain et al., and Shaffer do not teach the limitations of claim 6.
Regarding Claim 6, Santos et al. teach processing the result signal, using the device, for also determining whether an at least one benign organism is present in the environmental sample (Page 52, Column 1, Paragraph 2: Seventy-nine of the 1415 tortricid larvae (5.6%) were found to be parasitized (Table 3), with parasitism being detected in 27 sites). The detection of parasitoids (a beneficial) used CO1 DNA barcoding. CO1 barding can be accomplished by any sequencing method including as used by Shaffer or Kain et al.
Regarding Claim 7, Santos et al. teaches generating a map of multiple sampling locations where pests had spread (Page 48, Column 1, Figure 1: Geographical distribution of the study sites in the different island and mainland areas of Macaronesia. Circles indicate the location of the sites, and the numbers inside brackets correspond to the number of studied sites from each area (this data includes the number of pests)).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to combine the methods of Santos et al. with Cutter, Kain et al., and Shaffer. Santos et al. teach their methods improve agricultural pest management (as from Cutter and Shaffer) based on using sequencing to identifying of pests (as from Kain et al. and Shaffer) (Page 47, Column 1, Paragraph 3: DNA barcoding, could help the study of host–parasitoid interactions; Page 47, Column 2, Paragraph 1: DNA barcoding has proven to be useful and accurate in a number of studies covering a range of different taxa and has already been used to study host–parasitoid interactions; Page 47, Column 1, Paragraph 2: well-studied host–parasitoid associations usually related to biological control). Therefore, it would have been obvious to someone of ordinary skill in the art at the time of the effective filling date to combine the methods from the references indicated above. Furthermore, one of ordinary skill in the art would predict that the methods taught by Santos et al., Cutter, Kain et al., and Shaffer could be readily combined with a reasonable expectation of success because the CO1 barcoding region of the genome utilized by the sequencing techniques of Santos et al. could also be identified by the sequencing techniques of Kain et al. and Shaffer, as there are no structural characteristics of the genes that would prevent them from being sequenced by a particular sequencing method. Accordingly, 1-2, 4, and 6-20 taken as a whole would have been prima facie obvious before the effective filing date and are rejected under 35 U.S.C. 103.
Response to Arguments – 35 USC 103
The applicant’s argument – Bilodeau and Roe fail to teach or suggest, inter alia, the following features of amended independent claim 1 (emphasis added): selecting from a database, using the electronic device, a sensor arrangement suitable for selectively genotyping at least one relevant harmful organism – was found to be persuasive. Therefore the previously issued rejection is withdrawn. However, a new rejection is presented above which teaches the limitation (this action is non-final).
Double Patenting
The previous provisional double patenting rejection is withdrawn due to amendments to the claims. A new provisional double patenting rejection is made based on the amended claims (see below).
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1 and 10 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 2 of copending Application No. 18036122 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other.
The reference patent application (Application No. 18036122) contains the following claims that anticipate the instant application claims:
Reference claim 1 is directed to a computer-implemented method for determining at least one treatment parameter selected from the group including at least one method for a treatment parameter in an agricultural field (instant claim 10). Reference claim 1 is also directed to initiating taking at least one sample of at least one organism which existed or is existing or is expected to exist, in the agricultural field, conducting genetic analysis using the at least one sample of the at least one organism, obtaining therefrom genetic information of the at least one organism (instant claim 1), wherein the genetic analysis is based on at least one of the technologies selected from the group (instant claim 1). Reference claim 1 is also directed to receiving the genetic information of the at least one organism which existed or is existing or is expected to exist in the agricultural field (instant claim 1). Reference claim 1 is also directed to the genetic analysis of the at least one organism is conducted using a portable device operated in the agricultural field (instant claim 1).
Reference claim 2, which is dependent on refence claim 1, is directed to the method further comprising the receiving genetic information of the at least one organism which existed or is existing or is expected to exist in the agricultural field includes agricultural crop data comprising information about an agricultural crop species grown (instant claim 1) or geographical data relating to a location of the agricultural field (instant claim 1).
All limitations of instant claims 1 and 10 are therefore anticipated by reference claims 1 and 2. This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Conclusion
No Claims are allowed.
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/B.H.E./Examiner, Art Unit 1687
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687
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