DETAILED ACTION
The following is a Final Office action. In response to Examiner’s communication of 5/19/25, Applicant, on 11/16/2025, presented arguments for consideration. Claims 1-20 are pending in this application and have been rejected below.
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 .
Response to Amendment
Applicant’s amendments are acknowledged.
The 35 USC 101 rejections of claims 1-20 regarding abstract ideas are maintained in light of Applicant’s explanations.
The 35 USC 103 rejections of claims 1-20 are applied in light of Applicant’s explanations.
Claim Rejections - 35 USC§ 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Here, under considerations of the broadest reasonable interpretation of the claimed invention, Examiner finds that the Applicant invented a method and system for evaluating a product based on a determined carbon footprint. Examiner formulates an abstract idea analysis, following the framework described in the MPEP, as follows:
Step 1: The claims are directed to a statutory category, namely a "method" (claims 14-20) and "system" (claims 1-14).
Step 2A - Prong 1: The claims are found to recite limitations that set forth the abstract idea(s), namely, regarding claim 1:
obtain farm information describing one or more farm characteristics of a farm wherein the farm includes at least a first field and a second field that are different fields of the farm, and wherein the first field produces a first product and the second field produces a second product;
obtain first field information describing one or more first field characteristics of the first field;
obtain second field information describing one or more second field characteristics of the second field;
obtain first product information describing one or more first product characteristics of the first product;
obtain second product information describing one or more second product characteristics of the second product;
utilize, by a carbon algorithm, at least one of (1) the one or more farm characteristics, (2) the one or more first field characteristics, and (3) the one or more first product characteristics to determine a first carbon emission value for the first field;
utilize, by the carbon algorithm, at least one of (1) the one or more farm characteristics, (2) the one or more first field characteristics, and (3) the one or more first product characteristics to determine a first carbon sequestration value for the first field;
utilize, by the carbon algorithm, the first carbon emission value and the first carbon sequestration value to generate a first carbon footprint value for the first field, wherein the first carbon footprint value indicates the carbon impact for producing the first product at the first field;
utilize, by the carbon algorithm, at least one of (1) the one or more farm characteristics, (2) the one or more second field characteristics, and (3) the one or more second product characteristics to determine a second carbon emission value for the second field;
utilize, by the carbon algorithm, at least one of (1) the one or more farm characteristics, (2) the one or more second field characteristics, and (3) the one or more second product characteristics to determine a second carbon sequestration value for the second field;
utilize, by the carbon algorithm, the second carbon emission value and the second carbon sequestration value to generate a second carbon footprint value for the second field, wherein the second carbon footprint value indicates the carbon impact for producing the second product at the second field;
suggesting… one or more actions that when implemented improve the first carbon footprint value for the first field or the second carbon footprint value for the second field.
Independent claims 8 and 14 recite substantially similar claim language.
Dependent claims 2-7, 9-13, and 15-20 recite the same or similar abstract idea(s) as independent claims 1, 8, and 14 with merely a further narrowing of the abstract idea(s) to particular data characterization and/or additional data analyses performed as part of the abstract idea.
The limitations in claims 1-20 above falling well-within the groupings of subject matter identified by the courts as being abstract concepts, specifically the claims are found to correspond to the category of:
Mathematical Concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations; as the claims recite defining a revenue distribution function that include mathematical formulas, functions, and/or calculations including evaluating a product based on a determined carbon footprint through formulas and expressions.
"Certain methods of organizing human activity- fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)" as the limitations identified above are directed to evaluating a product based on a determined carbon footprint and thus is a method of organizing human activity including at least commercial or business interactions or relations and/or a management of user personal behavior; and/or
"Mental processes - concepts performed in the human mind (including an observation, evaluation, judgement, opinion)" as the limitations identified above include mere data observations, evaluations, judgements, and/or opinions, e.g. including user observation and evaluation of a product based on a determined carbon footprint, which is capable of being performed mentally and/or using pen and paper.
Step 2A - Prong 2: Claims 1-20 are found to clearly be directed to the abstract idea identified above because the claims, as a whole, fail to integrate the claimed judicial exception into a practical application, specifically the claims recite the additional elements of:
" suggesting, on a computer display " (claim 1, 14), however the aforementioned elements directed to the receiving of user input/selection of data to view via a dashboard and displaying corresponding data via the dashboard merely amount to generic GUI elements of a general purpose computer used to "apply" the abstract idea (MPEP 2106.05(f)) and/or is merely an attempt at limiting the abstract idea of analysis and review/visualization of evaluating a product based on a determined carbon footprint to a particular field of use/technological environment of a GUI dashboard (MPEP 2106.05(h)) and therefore the GUI dashboard input and display of data fails to integrate the abstract idea into a practical application;
" An evaluation platform, comprising: a memory; a processor coupled to the memory, the processor, when executing instructions stored in the memory, configured to: / An evaluation platform, comprising: a memory; a processor coupled to the memory, the processor, when executing program instructions, configured to: " (claims 1, 8, and 14) however the aforementioned elements merely amount to generic components of a general purpose computer used to "apply" the abstract idea (MPEP 2106.0S(f)) and thus fails to integrate the recited abstract idea into a practical application, furthermore the high-level recitation of receiving data from a generic "evaluation platform" is at most an attempt to limit the abstract to a particular field of use (MPEP 2106.0S(h), e.g.: "For instance, a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation. See, e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to power grid data); Intellectual Ventures I LLC v. Erie lndem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags).") and/or merely insignificant extra-solution activity (MPE 2106.05(g)) and thus further fails to integrate the abstract idea into a practical application;
" wherein receiving the selection of the one or more products is based on a quick response (QR) code associated with each of the one or more products," (claim 13), however the receiving of data from these various sources is merely insignificant extra-solution activity, e.g. data gathering, and/or merely an attempt at limiting the abstract idea to a particular field of use and thus fails to integrate the recited abstract idea into a practical application (e.g. MPEP 2106.0S(h): "Examiners should keep in mind that this consideration overlaps with other considerations, particularly insignificant extra-solution activity (see MPEP § 2106.05{g)). For instance, a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation. See, e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to power grid data); Intellectual Ventures I LLC v. Erie lndem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017} (limiting use of abstract idea to use with XML tags).");
Step 2B: Claims 1-20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements as described above with respect to Step 2A Prong 2 merely amount to a general purpose computer that attempts to apply the abstract idea in a technological environment (MPEP 2106.0S(f)), including merely limiting the abstract idea to a particular field of use of evaluating a product based on a determined carbon footprint by an "evaluation platform" and a GUI "computer display", as explained above, and/or performs insignificant extra-solution activity, e.g. data gathering or output, (MPEP 2106.0S(g)), as identified above, which is further found under step 2B to be merely well-understood, routine, and conventional activities as evidenced by MPEP 2106.0S(d)(II) (describing conventional activities that include transmitting and receiving data over a network, electronic recordkeeping, storing and retrieving information from memory, electronically scanning or extracting data from a physical document, and a web browser's back and forward button functionality). Therefore, similarly the combination and arrangement of the above identified additional elements when analyzed under Step 2B also fails to necessitate a conclusion that the claims amount to significantly more than the abstract idea directed to evaluating a product based on a determined carbon footprint.
Claims 1-20 are accordingly rejected under 35 USC§ 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea(s)) without significantly more.
Note: The analysis above applies to all statutory categories of invention. As such, the presentment of any claim otherwise styled as a machine or manufacture, for example, would be subject to the same analysis.
For further authority and guidance, see:
MPEP § 2106
https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility
Claim Rejections - 35 USC § 103
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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication Number 2022/0138703 to Asntekar et al. (hereafter referred to as Asntekar) in view of U.S. Patent Application Publication Number 2015/0100358 to Klavins (hereafter referred to as Klavins) and in further view of U.S. Patent Application Publication Number 2017/0351978 to Bellowe (hereafter referred to as Bellowe).
As per claim 1, Asntekar teaches:
An evaluation platform, comprising: a memory; a processor coupled to the memory, the processor, when executing instructions stored in the memory, configured to: (Paragraph Number [0047] teaches the CO2E sequestration server 130 may include a presentation processor 141 that is coupled to a parcel database 151. The presentation processor 141 comprises a user interface (UX) component 142, a search engine component 143, and a user database 144. Paragraph Number [0048] teaches the CO2E sequestration server 130 may further comprise an agricultural metrics processor 152, a crop simulation processor 153, a CO2E detection processor 155, and a remote sense processor 156, all of which are coupled to the parcel database 151. The CO2E sequestration server 130 may further comprise a CO2E management processor 154 that is coupled to the CO2E detection processor 155, the remote sense processor 157, and the crop simulation processor 153).
obtain farm information describing one or more farm characteristics of a farm (Paragraph Number [0069] teaches deciphering the history and potential of a parcel is critical to understanding the parcel's ultimate regenerative potential and economic value; however, this type of information is typically not available outside of hard-to-come-by operator data, and without access to this data, those interested in assigning CO2E sequestration potential and value to a parcel are typically limited to public soil maps and state-level productivity rankings, which are inadequate for representing actual field conditions. In addition, one skilled in the art will appreciate that most states don't have a consistent productivity score that allows for comparison of parcels across states, and that state productivity scores are based on historical information of weather and soil. In contrast, the metrics and valuations provided for by the present invention are 1) consistent and 2) based upon topography, soil, and crop simulations that are validated by remote sensing in test fields).
wherein the farm includes at least a first field and a second field that are different fields of the farm, (Paragraph Number [0069] teaches deciphering the history and potential of a parcel is critical to understanding the parcel's ultimate regenerative potential and economic value; however, this type of information is typically not available outside of hard-to-come-by operator data, and without access to this data, those interested in assigning CO2E sequestration potential and value to a parcel are typically limited to public soil maps and state-level productivity rankings, which are inadequate for representing actual field conditions. In addition, one skilled in the art will appreciate that most states don't have a consistent productivity score that allows for comparison of parcels across states, and that state productivity scores are based on historical information of weather and soil. In contrast, the metrics and valuations provided for by the present invention are 1) consistent and 2) based upon topography, soil, and crop simulations that are validated by remote sensing in test fields).
obtain first field information describing one or more first field characteristics of the first field (Paragraph Number [0069] teaches deciphering the history and potential of a parcel is critical to understanding the parcel's ultimate regenerative potential and economic value; however, this type of information is typically not available outside of hard-to-come-by operator data, and without access to this data, those interested in assigning CO2E sequestration potential and value to a parcel are typically limited to public soil maps and state-level productivity rankings, which are inadequate for representing actual field conditions. In addition, one skilled in the art will appreciate that most states don't have a consistent productivity score that allows for comparison of parcels across states, and that state productivity scores are based on historical information of weather and soil. In contrast, the metrics and valuations provided for by the present invention are 1) consistent and 2) based upon topography, soil, and crop simulations that are validated by remote sensing in test fields).
obtain second field information describing one or more second field characteristics of the second field (Paragraph Number [0069] teaches deciphering the history and potential of a parcel is critical to understanding the parcel's ultimate regenerative potential and economic value; however, this type of information is typically not available outside of hard-to-come-by operator data, and without access to this data, those interested in assigning CO2E sequestration potential and value to a parcel are typically limited to public soil maps and state-level productivity rankings, which are inadequate for representing actual field conditions. In addition, one skilled in the art will appreciate that most states don't have a consistent productivity score that allows for comparison of parcels across states, and that state productivity scores are based on historical information of weather and soil. In contrast, the metrics and valuations provided for by the present invention are 1) consistent and 2) based upon topography, soil, and crop simulations that are validated by remote sensing in test fields).
obtain second field information describing one or more second field characteristics of the second field (Paragraph Number [0069] teaches deciphering the history and potential of a parcel is critical to understanding the parcel's ultimate regenerative potential and economic value; however, this type of information is typically not available outside of hard-to-come-by operator data, and without access to this data, those interested in assigning CO2E sequestration potential and value to a parcel are typically limited to public soil maps and state-level productivity rankings, which are inadequate for representing actual field conditions. In addition, one skilled in the art will appreciate that most states don't have a consistent productivity score that allows for comparison of parcels across states, and that state productivity scores are based on historical information of weather and soil. In contrast, the metrics and valuations provided for by the present invention are 1) consistent and 2) based upon topography, soil, and crop simulations that are validated by remote sensing in test fields).
utilize, by a carbon algorithm, at least one of (1) the one or more farm characteristics, (2) the one or more first field characteristics, and (3) the one or more first product characteristics to determine a first carbon emission value for the first field (Paragraph Number [0034] teaches the various human activities that emit, or release, greenhouse gases into the air. For example, driving a car burns fossil fuels which releases CO2 as a byproduct. In agricultural parcels, emissions occur directly from the soil as a result of soil management, from performing necessary farming activities (e.g., driving tractors, which burn fossil fuels, releasing CO2), and from manufacturing nitrogen fertilizer (which also burns fossil fuels, releasing CO2). Paragraph Number [0080] teaches the CO2E determination processor 155 determines CO2E sequestration for each of the parcels by calculating greenhouse gas emissions under the baseline management scenario from emissions corresponding to one of the plurality of regenerative practices scenarios (e.g., best practices or better practices scenarios) and converting these emissions into units of CO2E. Paragraph Number [0104] teaches the CO2E determination processor 155 retrieves outputs corresponding to carbon dioxide flux from the soil (one component of the greenhouse gas emissions for each parcel) from the parcel database 151 (See Example in Paragraph Numbers [0111]-[0116])).
utilize, by the carbon algorithm, at least one of (1) the one or more farm characteristics, (2) the one or more first field characteristics, and (3) the one or more first product characteristics to determine a first carbon sequestration value for the first field (Paragraph Number [0035] teaches the amount of additional carbon is retained in the soil. In some cases, the amount of carbon in the soil increases over time and such is referred to as the amount of carbon that is being sequestered. If the amount of carbon in the soil is decreasing over time (i.e., being released into the atmosphere as CO2), then such is referred to as a greenhouse gas emission. In any given calculation for a field, carbon is either being sequestered or emitted. Paragraph Number [0080] teaches the CO2E determination processor 155 determines CO2E sequestration for each of the parcels by calculating greenhouse gas emissions under the baseline management scenario from emissions corresponding to one of the plurality of regenerative practices scenarios (e.g., best practices or better practices scenarios) and converting these emissions into units of CO2E. Accordingly, the value of CO2E sequestration reflects the amount of CO2E that can be sequestered in the soil by implementing one or more regenerative management practices over baseline management practices. The CO2E sequestration values are stored in the parcel database 318 along with their corresponding management practices scenarios).
utilize, by the carbon algorithm, the first carbon emission value and the first carbon sequestration value to generate a first carbon footprint value for the first field, wherein the first carbon footprint value indicates the carbon impact for producing the first product at the first field (Paragraph Number [0037] teaches a single number expressed in CO2e that represents the aggregation of both greenhouse gas emissions and carbon sequestration occurring in a single field (or prescribed region, etc.). Since both greenhouse gas emissions and carbon sequestration may be converted to CO2e, a field's net total greenhouse gas emissions (i.e., greenhouse gas emissions minus carbon sequestration) is referred to as it's carbon footprint. Paragraph Number [0116] teaches the annual carbon dioxide emissions under the baseline management practices scenario determined at block 614 are subtracted from the annual carbon dioxide emissions under the best management practices scenario to yield each parcel's regenerative carbon footprint potential value, which is stored in the parcel database 151. Flow then proceeds to block 630. Paragraph Number [0148] teaches each parcel's regenerative carbon footprint determined at block 904 are assigned to a percentile bin relative to all other regenerative carbon footprint values corresponding to remaining parcels in the prescribed region. In one embodiment, the percentile bins range from 0 (i.e., implying no regenerative potential) to 100 (i.e., implying more regenerative potential than all other parcels in the prescribed region) in increments of one percent. Other embodiments contemplate binning in increments of five percent and 10 percent).
utilize, by the carbon algorithm, at least one of (1) the one or more farm characteristics, (2) the one or more second field characteristics, and (3) the one or more second product characteristics to determine a second carbon emission value for the second field (Paragraph Number [0034] teaches the various human activities that emit, or release, greenhouse gases into the air. For example, driving a car burns fossil fuels which releases CO2 as a byproduct. In agricultural parcels, emissions occur directly from the soil as a result of soil management, from performing necessary farming activities (e.g., driving tractors, which burn fossil fuels, releasing CO2), and from manufacturing nitrogen fertilizer (which also burns fossil fuels, releasing CO2). Paragraph Number [0080] teaches the CO2E determination processor 155 determines CO2E sequestration for each of the parcels by calculating greenhouse gas emissions under the baseline management scenario from emissions corresponding to one of the plurality of regenerative practices scenarios (e.g., best practices or better practices scenarios) and converting these emissions into units of CO2E. Paragraph Number [0104] teaches the CO2E determination processor 155 retrieves outputs corresponding to carbon dioxide flux from the soil (one component of the greenhouse gas emissions for each parcel) from the parcel database 151 (See Example in Paragraph Numbers [0111]-[0116])).
utilize, by the carbon algorithm, at least one of (1) the one or more farm characteristics, (2) the one or more second field characteristics, and (3) the one or more second product characteristics to determine a second carbon sequestration value for the second field (Paragraph Number [0035] teaches the amount of additional carbon is retained in the soil. In some cases, the amount of carbon in the soil increases over time and such is referred to as the amount of carbon that is being sequestered. If the amount of carbon in the soil is decreasing over time (i.e., being released into the atmosphere as CO2), then such is referred to as a greenhouse gas emission. In any given calculation for a field, carbon is either being sequestered or emitted. Paragraph Number [0080] teaches the CO2E determination processor 155 determines CO2E sequestration for each of the parcels by calculating greenhouse gas emissions under the baseline management scenario from emissions corresponding to one of the plurality of regenerative practices scenarios (e.g., best practices or better practices scenarios) and converting these emissions into units of CO2E. Accordingly, the value of CO2E sequestration reflects the amount of CO2E that can be sequestered in the soil by implementing one or more regenerative management practices over baseline management practices. The CO2E sequestration values are stored in the parcel database 318 along with their corresponding management practices scenarios).
utilize, by the carbon algorithm, the second carbon emission value and the second carbon sequestration value to generate a second carbon footprint value for the second field, wherein the second carbon footprint value indicates the carbon impact for producing the second product at the second field (Paragraph Number [0037] teaches a single number expressed in CO2e that represents the aggregation of both greenhouse gas emissions and carbon sequestration occurring in a single field (or prescribed region, etc.). Since both greenhouse gas emissions and carbon sequestration may be converted to CO2e, a field's net total greenhouse gas emissions (i.e., greenhouse gas emissions minus carbon sequestration) is referred to as it's carbon footprint. Paragraph Number [0116] teaches the annual carbon dioxide emissions under the baseline management practices scenario determined at block 614 are subtracted from the annual carbon dioxide emissions under the best management practices scenario to yield each parcel's regenerative carbon footprint potential value, which is stored in the parcel database 151. Flow then proceeds to block 630. Paragraph Number [0148] teaches each parcel's regenerative carbon footprint determined at block 904 are assigned to a percentile bin relative to all other regenerative carbon footprint values corresponding to remaining parcels in the prescribed region. In one embodiment, the percentile bins range from 0 (i.e., implying no regenerative potential) to 100 (i.e., implying more regenerative potential than all other parcels in the prescribed region) in increments of one percent. Other embodiments contemplate binning in increments of five percent and 10 percent).
Asntekar teaches evaluating a product based on a determined carbon footprint, but does not explicitly teach specific products that are produced at a farm which is taught by the following citations from Klavins:
and wherein the first field produces a first product and the second field produces a second product (Paragraph Number [0095] teaches the user definable grid has further application in improving harvesting agricultural products. The system allows for maintaining the Agricultural Pedigree for grower's field's product by grid designation of the user defined grid. This information can also yield a selective harvesting of the field based upon distinctions in the Agricultural Pedigree via grid designation. Paragraph Number [0107] teaches a first farmer, also accessing device 2 via the open communications network, has such agricultural product in her field, and so she attempts to offer to fill a portion of the shipper's need. The device 2, locates the agricultural pedigree for that product for that farmer, and further applies the sustainability rating filter set by the shipper and the MRL filter set by the country of destination, and concludes that this farmer's agricultural product will meet the criteria set, and proceeds to facilitate the making of the sale between the farmer and the shipper. Paragraph Number [0118] teaches a grower desires to harvest his seed-based agricultural product in a manner that allows him to harvest that portion of his agricultural product which is ready for harvesting, but to leave in the field that portion which must mature further before harvesting. Utilizing the device 2, the grower maintains an agricultural pedigree for the agricultural product grown on his farm. In this example, the device 2 includes the capability for the grower to define one or more of his own grid designation units, which user definable grid designation unit may be his entire farm or one or more sub portions, such as one or more fields, within his farm. By combining the agricultural pedigree of the device 2 with the user definable grid, designation unit, the grower can use any combination of historical data, real time data, predictive modeling and combinations thereof to ascertain which section within the grid designation unit contains agricultural product ready for harvesting).
obtain first product information describing one or more first product characteristics of the first product (Paragraph Number [0095] teaches the user definable grid has further application in improving harvesting agricultural products. The system allows for maintaining the Agricultural Pedigree for grower's field's product by grid designation of the user defined grid. This information can also yield a selective harvesting of the field based upon distinctions in the Agricultural Pedigree via grid designation. Paragraph Number [0107] teaches a first farmer, also accessing device 2 via the open communications network, has such agricultural product in her field, and so she attempts to offer to fill a portion of the shipper's need. The device 2, locates the agricultural pedigree for that product for that farmer, and further applies the sustainability rating filter set by the shipper and the MRL filter set by the country of destination, and concludes that this farmer's agricultural product will meet the criteria set, and proceeds to facilitate the making of the sale between the farmer and the shipper. Paragraph Number [0118] teaches a grower desires to harvest his seed-based agricultural product in a manner that allows him to harvest that portion of his agricultural product which is ready for harvesting, but to leave in the field that portion which must mature further before harvesting. Utilizing the device 2, the grower maintains an agricultural pedigree for the agricultural product grown on his farm. In this example, the device 2 includes the capability for the grower to define one or more of his own grid designation units, which user definable grid designation unit may be his entire farm or one or more sub portions, such as one or more fields, within his farm. By combining the agricultural pedigree of the device 2 with the user definable grid, designation unit, the grower can use any combination of historical data, real time data, predictive modeling and combinations thereof to ascertain which section within the grid designation unit contains agricultural product ready for harvesting).
obtain second product information describing one or more second product characteristics of the second product (Paragraph Number [0095] teaches the user definable grid has further application in improving harvesting agricultural products. The system allows for maintaining the Agricultural Pedigree for grower's field's product by grid designation of the user defined grid. This information can also yield a selective harvesting of the field based upon distinctions in the Agricultural Pedigree via grid designation. Paragraph Number [0107] teaches a first farmer, also accessing device 2 via the open communications network, has such agricultural product in her field, and so she attempts to offer to fill a portion of the shipper's need. The device 2, locates the agricultural pedigree for that product for that farmer, and further applies the sustainability rating filter set by the shipper and the MRL filter set by the country of destination, and concludes that this farmer's agricultural product will meet the criteria set, and proceeds to facilitate the making of the sale between the farmer and the shipper. Paragraph Number [0118] teaches a grower desires to harvest his seed-based agricultural product in a manner that allows him to harvest that portion of his agricultural product which is ready for harvesting, but to leave in the field that portion which must mature further before harvesting. Utilizing the device 2, the grower maintains an agricultural pedigree for the agricultural product grown on his farm. In this example, the device 2 includes the capability for the grower to define one or more of his own grid designation units, which user definable grid designation unit may be his entire farm or one or more sub portions, such as one or more fields, within his farm. By combining the agricultural pedigree of the device 2 with the user definable grid, designation unit, the grower can use any combination of historical data, real time data, predictive modeling and combinations thereof to ascertain which section within the grid designation unit contains agricultural product ready for harvesting).
Both Asntekar and Klavins are directed to carbon emission detection and reduction. Asntekar discloses evaluating a product based on a determined carbon footprint. Klavins improves upon Asntekar by disclosing specific products that are produced at a farm. One of ordinary skill in the art would be motivated to further include specific products that are produced at a farm, to efficiently determine how specific carbon emissions and sequestrations are related to a particular product allowing a person to make a more environmentally minded selection. Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of evaluating a product based on a determined carbon footprint in Asntekar to further utilize specific products that are produced at a farm as disclosed in Klavins, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Asntekar teaches evaluating a product based on a determined carbon footprint, but does not explicitly teach suggesting one or more actions that improve a first carbon footprint value which is taught by the following citations from Bellowe:
suggesting, on a computer display, one or more actions that when implemented improve the first carbon footprint value for the first field or the second carbon footprint value for the second field. (Paragraph Number [0131] teaches the user profile 1801 can store information about the user, such as user's carbon footprint activity 1802 and/or user's interaction 1805 with the application GUI 1803 including the user's response to recommendations to change behavior impacting the carbon footprint and/or user’s responses to rewards and/or incentives. In at least one embodiment, the user carbon footprint activity 1804 can be tracked and recorded in the user profile. In at least one embodiment, reports and/or incentives can be provided to the user for engaging in ecologically friendly activities 1808).
Both the combination of Asntekar and Klavins and Bellowe are directed to carbon emission detection and reduction. The combination of Asntekar and Klavins discloses evaluating a product based on a determined carbon footprint. Bellowe improves upon the combination of Asntekar and Klavins by disclosing suggesting one or more actions that improve a first carbon footprint value. One of ordinary skill in the art would be motivated to further include suggesting one or more actions that improve a first carbon footprint value, to efficiently allow a person to make a more environmentally minded decision on which actions should be taken at the production level to reduce a carbon footprint. Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of evaluating a product based on a determined carbon footprint in the combination of Asntekar and Klavins to further utilize suggesting one or more actions that improve a first carbon footprint value as disclosed in Bellowe, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 8, Asntekar teaches:
An evaluation platform, comprising: a memory; a processor coupled to the memory, the processor, when executing program instructions, configured to: (Paragraph Number [0047] teaches the CO2E sequestration server 130 may include a presentation processor 141 that is coupled to a parcel database 151. The presentation processor 141 comprises a user interface (UX) component 142, a search engine component 143, and a user database 144. Paragraph Number [0048] teaches the CO2E sequestration server 130 may further comprise an agricultural metrics processor 152, a crop simulation processor 153, a CO2E detection processor 155, and a remote sense processor 156, all of which are coupled to the parcel database 151. The CO2E sequestration server 130 may further comprise a CO2E management processor 154 that is coupled to the CO2E detection processor 155, the remote sense processor 157, and the crop simulation processor 153).
determine, for each product, if a generated carbon value exists (Paragraph Number [0034] teaches the various human activities that emit, or release, greenhouse gases into the air. For example, driving a car burns fossil fuels which releases CO2 as a byproduct. In agricultural parcels, emissions occur directly from the soil as a result of soil management, from performing necessary farming activities (e.g., driving tractors, which burn fossil fuels, releasing CO2), and from manufacturing nitrogen fertilizer (which also burns fossil fuels, releasing CO2). Paragraph Number [0080] teaches the CO2E determination processor 155 determines CO2E sequestration for each of the parcels by calculating greenhouse gas emissions under the baseline management scenario from emissions corresponding to one of the plurality of regenerative practices scenarios (e.g., best practices or better practices scenarios) and converting these emissions into units of CO2E. Paragraph Number [0104] teaches the CO2E determination processor 155 retrieves outputs corresponding to carbon dioxide flux from the soil (one component of the greenhouse gas emissions for each parcel) from the parcel database 151 (See Example in Paragraph Numbers [0111]-[0116])).
in response to determining that the generated carbon value exists for a particular selected product, utilizing an algorithm to generate a first customer score for the particular selected product (Paragraph Number [0035] teaches the amount of additional carbon is retained in the soil. In some cases, the amount of carbon in the soil increases over time and such is referred to as the amount of carbon that is being sequestered. If the amount of carbon in the soil is decreasing over time (i.e., being released into the atmosphere as CO2), then such is referred to as a greenhouse gas emission. In any given calculation for a field, carbon is either being sequestered or emitted. Paragraph Number [0080] teaches the CO2E determination processor 155 determines CO2E sequestration for each of the parcels by calculating greenhouse gas emissions under the baseline management scenario from emissions corresponding to one of the plurality of regenerative practices scenarios (e.g., best practices or better practices scenarios) and converting these emissions into units of CO2E. Accordingly, the value of CO2E sequestration reflects the amount of CO2E that can be sequestered in the soil by implementing one or more regenerative management practices over baseline management practices. The CO2E sequestration values are stored in the parcel database 318 along with their corresponding management practices scenarios).
wherein the first customer score is based on the carbon value and one or more other values, for the selected product, that corresponds to the customer specific information (Paragraph Number [0037] teaches a single number expressed in CO2e that represents the aggregation of both greenhouse gas emissions and carbon sequestration occurring in a single field (or prescribed region, etc.). Since both greenhouse gas emissions and carbon sequestration may be converted to CO2e, a field's net total greenhouse gas emissions (i.e., greenhouse gas emissions minus carbon sequestration) is referred to as it's carbon footprint. Paragraph Number [0116] teaches the annual carbon dioxide emissions under the baseline management practices scenario determined at block 614 are subtracted from the annual carbon dioxide emissions under the best management practices scenario to yield each parcel's regenerative carbon footprint potential value, which is stored in the parcel database 151. Flow then proceeds to block 630. Paragraph Number [0148] teaches each parcel's regenerative carbon footprint determined at block 904 are assigned to a percentile bin relative to all other regenerative carbon footprint values corresponding to remaining parcels in the prescribed region. In one embodiment, the percentile bins range from 0 (i.e., implying no regenerative potential) to 100 (i.e., implying more regenerative potential than all other parcels in the prescribed region) in increments of one percent. Other embodiments contemplate binning in increments of five percent and 10 percent).
or in response to determine that the corresponding generated carbon value does not exist for the particular selected product (Paragraph Number [0034] teaches the various human activities that emit, or release, greenhouse gases into the air. For example, driving a car burns fossil fuels which releases CO2 as a byproduct. In agricultural parcels, emissions occur directly from the soil as a result of soil management, from performing necessary farming activities (e.g., driving tractors, which burn fossil fuels, releasing CO2), and from manufacturing nitrogen fertilizer (which also burns fossil fuels, releasing CO2). Paragraph Number [0080] teaches the CO2E determination processor 155 determines CO2E sequestration for each of the parcels by calculating greenhouse gas emissions under the baseline management scenario from emissions corresponding to one of the plurality of regenerative practices scenarios (e.g., best practices or better practices scenarios) and converting these emissions into units of CO2E. Paragraph Number [0104] teaches the CO2E determination processor 155 retrieves outputs corresponding to carbon dioxide flux from the soil (one component of the greenhouse gas emissions for each parcel) from the parcel database 151 (See Example in Paragraph Numbers [0111]-[0116])).
utilizing the algorithm to generate a second customer score for the particular selected product (Paragraph Number [0035] teaches the amount of additional carbon is retained in the soil. In some cases, the amount of carbon in the soil increases over time and such is referred to as the amount of carbon that is being sequestered. If the amount of carbon in the soil is decreasing over time (i.e., being released into the atmosphere as CO2), then such is referred to as a greenhouse gas emission. In any given calculation for a field, carbon is either being sequestered or emitted. Paragraph Number [0080] teaches the CO2E determination processor 155 determines CO2E sequestration for each of the parcels by calculating greenhouse gas emissions under the baseline management scenario from emissions corresponding to one of the plurality of regenerative practices scenarios (e.g., best practices or better practices scenarios) and converting these emissions into units of CO2E. Accordingly, the value of CO2E sequestration reflects the amount of CO2E that can be sequestered in the soil by implementing one or more regenerative management practices over baseline management practices. The CO2E sequestration values are stored in the parcel database 318 along with their corresponding management practices scenarios).
Asntekar teaches evaluating a product based on a determined carbon footprint, but does not explicitly teach specific products that are produced at a farm which is taught by the following citations from Klavins:
receive a selection of one or more products for sale at a merchant (Paragraph Number [0095] teaches the user definable grid has further application in improving harvesting agricultural products. The system allows for maintaining the Agricultural Pedigree for grower's field's product by grid designation of the user defined grid. This information can also yield a selective harvesting of the field based upon distinctions in the Agricultural Pedigree via grid designation. Paragraph Number [0107] teaches a first farmer, also accessing device 2 via the open communications network, has such agricultural product in her field, and so she attempts to offer to fill a portion of the shipper's need. The device 2, locates the agricultural pedigree for that product for that farmer, and further applies the sustainability rating filter set by the shipper and the MRL filter set by the country of destination, and concludes that this farmer's agricultural product will meet the criteria set, and proceeds to facilitate the making of the sale between the farmer and the shipper. Paragraph Number [0118] teaches a grower desires to harvest his seed-based agricultural product in a manner that allows him to harvest that portion of his agricultural product which is ready for harvesting, but to leave in the field that portion which must mature further before harvesting. Utilizing the device 2, the grower maintains an agricultural pedigree for the agricultural product grown on his farm. In this example, the device 2 includes the capability for the grower to define one or more of his own grid designation units, which user definable grid designation unit may be his entire farm or one or more sub portions, such as one or more fields, within his farm. By combining the agricultural pedigree of the device 2 with the user definable grid, designation unit, the grower can use any combination of historical data, real time data, predictive modeling and combinations thereof to ascertain which section within the grid designation unit contains agricultural product ready for harvesting).
A person of ordinary skill in the art would have been motivated to combine these Asntekar teaches evaluating a product based on a determined carbon footprint, but does not explicitly teach suggesting one or more actions that improve a first carbon footprint value which is taught by the following citations from Bellowe:
receive customer specific information that includes one or more factors of importance to a user when purchasing a product (Paragraph Number [0071] teaches a common carbon footprint estimate for eating any meal in any restaurant anywhere. Later embodiments may provide more accurate, fine-grained estimates. For example, the carbon footprint estimate may vary between a steak houses and a vegetarian restaurant, assigning a higher carbon footprint to eating in the steak house. Another example is that a different carbon footprint may be associated with eating dinner rather than breakfast. Finer grained considerations for a restaurant's carbon impact may consider eco-friendly practices Paragraph Number [0131] teaches the user profile 1801 can store information about the user, such as user's carbon footprint activity 1802 and/or user's interaction 1805 with the application GUI 1803 including the user's response to recommendations to change behavior impacting the carbon footprint and/or user’s responses to rewards and/or incentives. In at least one embodiment, the user carbon footprint activity 1804 can be tracked and recorded in the user profile. In at least one embodiment, reports and/or incentives can be provided to the user for engaging in ecologically friendly activities 1808. Paragraph Number [0139] teaches the member can be presented with the option to pay the carbon offset. In some embodiments, the carbon offset is automatically paid. The user can be presented with one or more organizations which money and/or time can be donated to offset the carbon footprint. The organizations can be suggested to the user based on the user profile, user cluster, and/or user behavior).
wherein the second customer scores does not consider carbon and is only based on the one or more other values, for the particular selected product, corresponding to the customer specific information (Paragraph Number [0071] teaches the system may be built so that modules are plug replaceable as more information becomes available. For example, first embodiments may use a common carbon footprint estimate for eating any meal in any restaurant anywhere. Later embodiments may provide more accurate, fine-grained estimates. For example, the carbon footprint estimate may vary between a steak houses and a vegetarian restaurant, assigning a higher carbon footprint to eating in the steak house. Another example is that a different carbon footprint may be associated with eating dinner rather than breakfast. Finer grained considerations for a restaurant's carbon impact may consider eco-friendly practices. Paragraph Number [0131] teaches the user profile 1801 can store information about the user, such as user's carbon footprint activity 1802 and/or user's interaction 1805 with the application GUI 1803 including the user's response to recommendations to change behavior impacting the carbon footprint and/or user’s responses to rewards and/or incentives. In at least one embodiment, the user carbon footprint activity 1804 can be tracked and recorded in the user profile. In at least one embodiment, reports and/or incentives can be provided to the user for engaging in ecologically friendly activities 1808. Paragraph Number [0139] teaches the member can be presented with the option to pay the carbon offset. In some embodiments, the carbon offset is automatically paid. The user can be presented with one or more organizations which money and/or time can be donated to offset the carbon footprint. The organizations can be suggested to the user based on the user profile, user cluster, and/or user behavior).
A person of ordinary skill in the art would have been motivated to combine these references as described in regard to claim 1.
As per claim 14, claim 14 recites a method that is substantially similar to the steps performed by the system in claim 1 and is rejected for the same reasons put forth in regard to claim 1.
As per claims 2 and 15, the combination of Asntekar, Klavins, and Bellowe teaches each of the limitations of claims 1 and 14 respectively.
In addition, Asntekar teaches:
wherein the one or more farm characteristics include one or more of a location of the farm, climate information for the farm, farm management software utilized at the farm (Paragraph Number [0124] teaches the CO2E determination processor 155 retrieves from the parcel database 151 field history data, committed best management practice data, soil data, and geographical location data for the parcel. Flow then proceeds to block 714).
As per claims 3, 10, and 16, the combination of Asntekar, Klavins, and Bellowe teaches each of the limitations of claims 1, 8 and 9, and 14 respectively.
In addition, Asntekar teaches:
wherein the one or more first field characteristics or the one or more second field characteristics include one or more of field management practice information, size of the field information, usage of field information, soil color of field information, soil texture of field information, number of trees or plants per acre information, year of planting information, land type information (Paragraph Number [0069] teaches deciphering the history and potential of a parcel is critical to understanding the parcel's ultimate regenerative potential and economic value; however, this type of information is typically not available outside of hard-to-come-by operator data, and without access to this data, those interested in assigning CO2E sequestration potential and value to a parcel are typically limited to public soil maps and state-level productivity rankings, which are inadequate for representing actual field conditions. In addition, one skilled in the art will appreciate that most states don't have a consistent productivity score that allows for comparison of parcels across states, and that state productivity scores are based on historical information of weather and soil. In contrast, the metrics and valuations provided for by the present invention are 1) consistent and 2) based upon topography, soil, and crop simulations that are validated by remote sensing in test fields. (Examiner asserts that this section teaches at least the alternatives of land type information and usage of the field information)).
As per claims 4, 11, and 17, the combination of Asntekar, Klavins, and Bellowe teaches each of the limitations of claims 1, 8-10, and 14 respectively.
Asntekar teaches evaluating a product based on a determined carbon footprint, but does not explicitly teach specific products that are produced at a farm which is taught by the following citations from Klavins:
wherein the one or more first product characteristics or the one or more second product characteristics include one or more of type information indicating a type of product and yield information indicating an amount of product produced (Paragraph Number [0095] teaches the user definable grid has further application in improving harvesting agricultural products. The system allows for maintaining the Agricultural Pedigree for grower's field's product by grid designation of the user defined grid. This information can also yield a selective harvesting of the field based upon distinctions in the Agricultural Pedigree via grid designation. Paragraph Number [0107] teaches a first farmer, also accessing device 2 via the open communications network, has such agricultural product in her field, and so she attempts to offer to fill a portion of the shipper's need. The device 2, locates the agricultural pedigree for that product for that farmer, and further applies the sustainability rating filter set by the shipper and the MRL filter set by the country of destination, and concludes that this farmer's agricultural product will meet the criteria set, and proceeds to facilitate the making of the sale between the farmer and the shipper. Paragraph Number [0118] teaches a grower desires to harvest his seed-based agricultural product in a manner that allows him to harvest that portion of his agricultural product which is ready for harvesting, but to leave in the field that portion which must mature further before harvesting. Utilizing the device 2, the grower maintains an agricultural pedigree for the agricultural product grown on his farm. In this example, the device 2 includes the capability for the grower to define one or more of his own grid designation units, which user definable grid designation unit may be his entire farm or one or more sub portions, such as one or more fields, within his farm. By combining the agricultural pedigree of the device 2 with the user definable grid, designation unit, the grower can use any combination of historical data, real time data, predictive modeling and combinations thereof to ascertain which section within the grid designation unit contains agricultural product ready for harvesting).
A person of ordinary skill in the art would have been motivated to combine these references as described in regard to claim 1.
As per claims 5, 12, and 18, the combination of Asntekar, Klavins, and Bellowe teaches each of the limitations of claims 1, 8 and 9, and 14 respectively.
In addition, Asntekar teaches::
wherein the field is an area of land or a body of water. (Paragraph Number [0069] teaches deciphering the history and potential of a parcel is critical to understanding the parcel's ultimate regenerative potential and economic value; however, this type of information is typically not available outside of hard-to-come-by operator data, and without access to this data, those interested in assigning CO2E sequestration potential and value to a parcel are typically limited to public soil maps and state-level productivity rankings, which are inadequate for representing actual field conditions. In addition, one skilled in the art will appreciate that most states don't have a consistent productivity score that allows for comparison of parcels across states, and that state productivity scores are based on historical information of weather and soil. In contrast, the metrics and valuations provided for by the present invention are 1) consistent and 2) based upon topography, soil, and crop simulations that are validated by remote sensing in test fields).
As per claims 6 and 19, the combination of Asntekar, Klavins, and Bellowe teaches each of the limitations of claims 1 and 14 respectively.
In addition, Asntekar teaches:
further comprising generating a carbon ledger for the product by aggregating the carbon footprint for the first field with one or more other carbon footprints associated with one or more other storage or processing facilities that store or process the first product after it leaves the first field (Paragraph Number [0034] teaches the various human activities that emit, or release, greenhouse gases into the air. For example, driving a car burns fossil fuels which releases CO2 as a byproduct. In agricultural parcels, emissions occur directly from the soil as a result of soil management, from performing necessary farming activities (e.g., driving tractors, which burn fossil fuels, releasing CO2), and from manufacturing nitrogen fertilizer (which also burns fossil fuels, releasing CO2). Paragraph Number [0080] teaches the CO2E determination processor 155 determines CO2E sequestration for each of the parcels by calculating greenhouse gas emissions under the baseline management scenario from emissions corresponding to one of the plurality of regenerative practices scenarios (e.g., best practices or better practices scenarios) and converting these emissions into units of CO2E. Paragraph Number [0104] teaches the CO2E determination processor 155 retrieves outputs corresponding to carbon dioxide flux from the soil (one component of the greenhouse gas emissions for each parcel) from the parcel database 151 (See Example in Paragraph Numbers [0111]-[0116])).
As per claims 7 and 20, the combination of Asntekar, Klavins, and Bellowe teaches each of the limitations of claims 1 and 6, and 14 and 19 respectively.
In addition, Asntekar teaches:
wherein the carbon ledger account for carbon emissions for transportation of the first product to the one or more other storage or processing facilities (Paragraph Number [0034] teaches the various human activities that emit, or release, greenhouse gases into the air. For example, driving a car burns fossil fuels which releases CO2 as a byproduct. In agricultural parcels, emissions occur directly from the soil as a result of soil management, from performing necessary farming activities (e.g., driving tractors, which burn fossil fuels, releasing CO2), and from manufacturing nitrogen fertilizer (which also burns fossil fuels, releasing CO2). (See Example in Paragraph Numbers [0111]-[0116]) (Examiner asserts that the determining of emissions while driving of tractors is equivalent to accounting for carbon emissions for transportation of the product)).
As per claim 9, the combination of Asntekar, Klavins, and Bellowe teaches each of the limitations of claim 8.
In addition, Asntekar teaches:
wherein the generated carbon value is a carbon footprint value that is generated for a first product that is produced on a farm of a field (Paragraph Number [0037] teaches a single number expressed in CO2e that represents the aggregation of both greenhouse gas emissions and carbon sequestration occurring in a single field (or prescribed region, etc.). Since both greenhouse gas emissions and carbon sequestration may be converted to CO2e, a field's net total greenhouse gas emissions (i.e., greenhouse gas emissions minus carbon sequestration) is referred to as it's carbon footprint. Paragraph Number [0116] teaches the annual carbon dioxide emissions under the baseline management practices scenario determined at block 614 are subtracted from the annual carbon dioxide emissions under the best management practices scenario to yield each parcel's regenerative carbon footprint potential value, which is stored in the parcel database 151. Flow then proceeds to block 630. Paragraph Number [0148] teaches each parcel's regenerative carbon footprint determined at block 904 are assigned to a percentile bin relative to all other regenerative carbon footprint values corresponding to remaining parcels in the prescribed region. In one embodiment, the percentile bins range from 0 (i.e., implying no regenerative potential) to 100 (i.e., implying more regenerative potential than all other parcels in the prescribed region) in increments of one percent. Other embodiments contemplate binning in increments of five percent and 10 percent).
As per claim 13, the combination of Asntekar, Klavins, and Bellowe teaches each of the limitations of claim 8.
Asntekar teaches evaluating a product based on a determined carbon footprint, but does not explicitly teach specific products that are produced at a farm which is taught by the following citations from Klavins:
wherein receiving the selection of the one or more products is based on a quick response (QR) code associated with each of the one or more products (Paragraph Number [0080] teaches the information may be present as, for example a QR Codes reader. Such readers are currently used in a broad commercial context, including both commercial tracking applications and convenience-oriented applications aimed at mobile phone users (known as mobile tagging). Users with a camera phone or I-Phone or similar apparatus, equipped with the correct reader application can scan the image of the QR Code to display text, contact information, connect to a wireless network, or open a web page in the phone's browser. This act of linking from physical world objects is known as a "hard link" or physical world hyperlinks. Such technology may be employed to place the QR Code on the fruit, which the shopper scans with his or her phone, to be linked to a web site providing all such data to the shopper as the shopper may desire to make the purchase).
A person of ordinary skill in the art would have been motivated to combine these reference as described in regard to claim 1.
Response to Arguments
Applicant’s arguments filed 11/16/2025 have been fully considered but they are not persuasive.
Applicant argues that the claims are eligible under 35 USC 101. (See Applicant’s Remarks, 11/16/2025, pgs. 1-4). Examiner respectfully disagrees. As noted in the 35 USC 101 analysis presented above, the claims recite an abstract concept that is encapsulated by decision making analogous to a method of organizing human activity or mathematical concepts. Examiner notes that each of the limitations that encapsulate the abstract concepts are recited in the above 35 USC 101. Additionally, the claims do not recite a practical application of the abstract concepts in that there is no specific use or application of the method steps other than to make conclusory determinations and provide for direction for either a person or machine to follow at some future time or to make calculations that are mathematical operations. The claims do not recite any particular use for these determinations and directions that improve upon the underlying computer technology (in this instance the computer software, processor, and memory). Instead, Examiner asserts that the additional elements in the claim language are only used as implementation of the abstract concepts utilizing technology. The concepts described in the limitations when taken both as a whole and individually are not meaningfully different than those found by the courts to be abstract ideas and are similarly considered to be certain methods of organizing human activity such as managing personal behavior or relationships or interactions between people, including social activities, teaching, and following rules or instructions or to make calculations that are mathematical operations. The steps are then encapsulated into a particular technological environment by executing these steps upon a computer processor and utilizing features such as a computer interface or sending and receiving data over a network or displaying information via a computerized graphical user interface. However, sending and receiving of information over a network and execution of algorithms on a computer are utilized only to facilitate the abstract concepts (i.e. selecting data on an interface, publishing/displaying information, etc.). As such, Examiner asserts that the implementation of the abstract concepts recited by the claims utilize computer technology in a way that is considered to be generally linking the use of the judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)). Accordingly, Examiner does not find that the claims recite a practical application of the abstract concepts recited by the claims.
Applicant argues that the cited references only teach determining a carbon footprint at the parcel level and not at a field or inter-field level. (See Applicant’s Remarks, 11/16/2025, pgs. 5-7). Examiner respectfully disagrees. As an initial note, Examiner contends that the difference between a parcel and a field is negligible in that the two works are synonymous. A parcel of land has no specific definition that takes it out of the realm of a field. Indeed, this interpretation is supported by the Asntekar reference that uses the terms parcel and field interchangeably. Second, Examiner notes that a person of ordinary skill would understand that even if there were slight semantic differences between the two terms, the functionally of the two words is the same, in that they connote a piece of land set apart for a use and that the use of one term over the other provides no distinction. Examiner asserts that they must read Applicant’s claims under a broadest reasonable interpretation. Contrary to Applicant’s assertions, a broadest reasonable interpretation does not distinguish the two terms, particularly from a functional standpoint. Examiner notes that there is no specific limitation of the use of the term “field” in Applicant’s claims that would limit the field to any other particular characteristic. Indeed, the field could be anything from a small 8’ by 8’ garden to a multi acre farm. If Applicant wishes the term field to limit the claim language to something specific, then additional descriptions should be contained in the claim language.
Examiner further notes, in response to Applicant’s assertions, that gathering information about fields is well known both in the art and by a person of ordinary skill and the repetition of the steps, as claimed in the present invention, add little to the patentable weight of the claim limitations. Further, the carbon algorithm as used by the claims is only used by an alternative statement of “at least one of” which is interpreted as needing to only have one of the alternatives found in the art to read on the claim language. The broad use of the term “farm characteristics” and “field characteristics” make for a wide variety of teaching to read on the claim limitations. In the case of the Asntekar reference, the cited paragraphs teach determining greenhouse gas emissions (a characteristic of the field) and using that information to determine a carbon algorithm and then use that algorithm to generate a carbon footprint. The broad terms used by Applicant do not sufficiently restrict this reading of the claim language. Examiner suggest that Applicant better restrict the breadth of the terms utilized in the claim language to overcome the prior art cited. Examiner is not persuaded by the distinctions Applicant is attempting to make.
In regard to the final limitation of the independent claim where a suggestion of actions that improve the carbon footprint, Examiner notes that this section is taught by the Bellowe reference in combination with the Asntekar and Klavins references. The Bellowe reference specifically teaches “recommendations to change behavior impacting the carbon footprint.” Examiner notes that while the Bellowe reference is generally referring to an individual and how they can lower their personal carbon footprint, the teaching extends to a farmer (an individual) and how they might lower their carbon footprint. Thus, the teachings of the cited references work together to teach the use of a carbon algorithm and then the use of recommendations to a user based on that data. As such, Examiner reasserts that the combination of Asntekar, Klavins, and Bellowe teach each of the claim limitations of the independent claims.
Conclusion
Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW H DIVELBISS whose telephone number is (571)270-0166. The examiner can normally be reached on 7:30 am - 6:00 PM. 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, Jerry O'Connor can be reached on (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/M. H. D./
Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624
Prosecution Insights