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 Arguments
Regarding the 35 USC 101 rejection, Examiner has fully considered Applicant’s arguments and amendments.
Regarding Applicant’s assertion of “These steps define a specific, data-driven agronomic optimization process, not a generalized idea. In particular, amended Claims 1 and 11 recite domain-specific agronomic constraints for filtering candidate seeds: "filtered based on...relative maturity (RM), resistance traits, tolerance traits, or product category". These features are derived from specialized agricultural datasets and breeding pipelines and require structured agronomic databases and classification systems. Importantly, these constraints involve multi-parameter filtering across large datasets. A human cannot practically access and analyze hundreds/thousands of seed records, apply probabilistic Bayesian inference, and simultaneously filter across agronomic attributes at production scale. Therefore, Claims 1 and 11 are not directed to steps that can be performed in the human mind.,” Examiner respectfully disagrees with Applicant’s assertion. Examiner preliminarily notes that the present claims do not recite “simultaneously” filtering across agronomic attributes at production scale. Applicant asserts that the present claims reflect “simultaneously” filtering data at an agronomic scale, which is not recited or reflected under broadest reasonable interpretation within the present claims. For the amended imitations, see 35 USC 101 rejection below. Applicant is reminded that it is impermissible to import limitations from the specification into the claims. (See MPEP 2111.01(II)) In order for Applicant to be given the argued interpretation, the claims must positively recite the argued subject matter. Even assuming arguendo, the present claims recite “filtering, by the agricultural computer system, the plurality of candidate seeds, based on at least one feature of the target seed and/or the plurality of candidate seeds; wherein the plurality of candidate seeds are filtered based on at least one feature including relative maturity (RM), resistance traits, tolerance traits, and/or product category.” These limitations, as drafted, but for the recitation of “by an agricultural computer system,” is a process that covers performance of the limitations in the mind or manually with aid of pencil and paper but for the recitation of generic computer components. That is, but for the “by an agricultural computer system” language, nothing in the claim elements preclude the steps from practically being performed in the human mind. For example, with the exception of the “by an agricultural computer system” language, the claim steps in the context of the claim encompass a user mentally or manually performing the steps of the claim.
Regarding Applicant’s assertion of “This sequence constitutes a practical technological workflow that is specifically directed to controlling agricultural decision-making and field operations, rather than an abstract idea.,” Examiner respectfully disagrees. The listed sequence comprises several abstract limitations for consideration under Step 2A, Prong 1. This type of abstract behavior is not sufficient to prove integration into a practical application or anything significantly more. For example, limitations related to filtering data, generating probabilities, identifying a subset of seeds, and other limitation do not comprise any particular additional elements for consideration. Rather, these abstract limitations are part of the abstract idea identified under Step 2A, Prong 1 and thus are not capable to prove integration into a practical application or anything significantly more.
Regarding Applicant’s assertion of “Moreover, Claims 1 and 11 recite the use of real-world agronomic data tied to a physical environment. This includes yield data from actual growing spaces, location data tied to geographic regions, and filtering based on a region defined relative to the target field. These limitations ensure that the model is anchored to real physical growing conditions and tailored to specific environmental contexts. (Specification, para. [0025].) This environment-specific modeling ties the claims to a particular physical context rather than an abstract concept.,” Examiner respectfully disagrees. Examiner respectfully asserts that providing more accurate data in order to generate a more accurate outcome would be an improvement related to the abstract limitations for consideration under Step 2A Prong 1. This does not improve any of the additional elements of the claims. MPEP 2106.05(a): “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements...” Additionally, as discussed in 2106.05(a)(II) improvements to technology or technical fields, “an improvement in the abstract idea itself … is not an improvement in technology”
Regarding Applicant’s assertion of “Additionally, the Bayesian yield-delta model is applied in a technical, field-constrained manner. Claims 1 and 11 do not merely recite "a mathematical model." Instead, they recite training a model using empirical agricultural data, modeling pairwise yield deltas with a noise expression, and generating probabilities tied to real-world performance thresholds. This modeling is directed to predicting physical crop yield outcomes based on field-specific and region-specific constraints for downstream physical planting decisions. (Id., para. [0043].) Therefore, the mathematical framework is embedded within a technical agricultural system and applied to a real-world problem, not an abstract calculation.,” Examiner respectfully disagrees with Applicant’s assertion. While the claim recites training a model using a mathematical equation, the present claims are directed to improving the predicted crop outcomes, which is not an improvement to the functioning of the computer itself. Rather, the training of the model is nothing more than mere use of a computer as a tool. The limitations of training a model using a mathematical equation and applying the trained model to generate a probability, as drafted, provide nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Regarding Applicant’s assertion of “Furthermore, the amended filtering step ensures that selected seeds are biologically and operationally compatible with the target field (e.g., uniquely links the selected seeds to the target field) and that ultimate recommendations are deployable under actual growing conditions. For example, RM ensures compatibility with the field's growing season, resistance/tolerance traits ensure survivability under environmental stress, and product category ensures suitability for intended agricultural use. (Id., para. [0057] and [0076]-[0078].) These constraints operate in conjunction with the modeling and data processing to produce field-ready outputs, not theoretical results.,” Examiner respectfully asserts that generating a more accurate recommendation or output is not an improvement to the functioning of the additional elements of the claim. This type of improvement would be an improvement to the abstract limitations for consideration under Step 2A, Prong 1. MPEP 2106.05(a): “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements...” Additionally, as discussed in 2106.05(a)(II) improvements to technology or technical fields, “an improvement in the abstract idea itself … is not an improvement in technology”
Regarding Applicant’s assertion of “Additionally, Claims 1 and 11 achieve a meaningful transformation. The claims transform raw agronomic data into actionable, field-specific planting recommendations (that include particular field-ready seeds). This transformation is meaningful because it directly affects seed selection and planting decisions, influences crop yield outcomes, and alters real-world agricultural operations. Further, the recited system is not limited to analysis, but produces outputs specifically intended for implementation in planting and enables split planting arrangements for comparative evaluation. This coupling between data processing, modeling, decision, and physical deployment demonstrates that Claims 1 and 11 are directed to a complete technological system, not an abstract calculation. Accordingly, the claims recite a non- conventional, technically grounded combination of elements that goes well beyond any alleged judicial exception and therefore constitutes significantly more.,” Examiner respectfully asserts that the cited improvements, such as improvements to generating recommendations, would be an improvement to the abstract limitations for consideration under Step 2A, Prong 1 and is not an improvement related to the additional elements for consideration under Step 2A, Prong 2 or Step 2B. MPEP 2106.05(a): “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements...” Additionally, as discussed in 2106.05(a)(II) improvements to technology or technical fields, “an improvement in the abstract idea itself … is not an improvement in technology”
Accordingly, the present claims are rejected under 35 USC 101.
Information Disclosure Statement
The information disclosure statement (IDS) filed on 07/07/2026 has been fully considered.
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 1-4, 8-14, and 18-20 are rejected under 35 USC 101 because the claimed invention is directed to a judicial exception (i.e. abstract idea) without anything significantly more.
Step 1: Claims 1-4 and 8-10 are directed to a method and claims 11-14 and 18-20 are directed to a system. Therefore, the claims are directed to patent eligible categories of invention.
Step 2A, Prong 1: Independent claims 1 and 11 recite identifying a set of candidate seeds, constituting an abstract idea based on “Mental Processes” related to concepts performed in the human mind including observation, evaluation, judgment, and opinion. Claim 1 recites abstract limitations including “receiving, a request for a planting recommendation, from a user, the request including a target field and a target seed; and in response to the request: accessing data, the data representative of hundreds of seeds harvested from various growing spaces, the data including at least yield data and location data for the growing spaces; filtering, the accessed data based on a region including the target field, the region defined based on a center of the region relative to the target field; a yield delta prediction model for a plurality of candidate seeds, based, at least in part, on the filtered data, a Bayesian framework and a plurality of yield deltas expressed as:
d
i
j
1
j
2
=
z
j
1
-
z
j
2
+
σ
i
ε
i
j
1
j
2
; wherein di is the yield delta,
z
j
1
and
z
j
2
are yield advantages of iterative pairs of the plurality of candidate seeds, and σiεi is a noise expression; for each one of the plurality of candidate seeds, generating, a probability of said one of the plurality of candidate seeds exceeding a performance threshold, relative to the target seed; filtering, the plurality of candidate seeds, based on at least one feature of the target seed and/or the plurality of candidate seeds, wherein the plurality of candidate seeds are filtered based on at least one feature including relative maturity (RM), resistance traits, tolerance traits, and/or product category; identifying, from the filtered plurality of candidate seeds, a set of the candidate seeds, based on the generated probability for the respective candidate seed satisfying a defined threshold; outputting, the identified set of candidate seeds to a user; the target seed and at least one of the identified set of candidate seeds in the target field, in a split planting arrangement to permit direct comparison of the target seed and the at least one of the identified set of candidate seeds.” Independent claim 11 recites abstract limitations including “receive a request for a planting recommendation, from a user, the request including a target field and a target seed; and in response to the request: access data, the data representative of hundreds of seeds harvested from various growing spaces, the data including at least yield data and location data for the growing spaces; filter the accessed data based on a region including the target field, the region defined based on a center of the region relative to the target field; a yield delta prediction model for a plurality of candidate seeds, based, at least in part, on the filtered data, a Bayesian framework and a plurality of yield deltas expressed as:
d
i
j
1
j
2
=
z
j
1
-
z
j
2
+
σ
i
ε
i
j
1
j
2
; wherein di is the yield delta,
z
j
1
and
z
j
2
are yield advantages of iterative pairs of the plurality of candidate seeds, and σiεi is a noise expression; for each one of the plurality of candidate seeds, generate, a probability of said one of the plurality of candidate seeds exceeding a performance threshold, relative to the target seed; filter the plurality of candidate seeds, based on at least one feature of the target seed and/or the plurality of candidate seeds, wherein the plurality of candidate seeds are filtered based on at least one feature including relative maturity (RM), resistance traits, tolerance traits, and/or product category; identify, from the filtered plurality of candidate seeds, a set of the candidate seeds, based on the generated probability for the respective candidate seed satisfying a defined threshold; output, to the user the identified set of candidate seeds to a user; and instructions to automatically plant the target seed and at least one of the identified set of candidate seeds in the target field, in a split planting arrangement to permit direct comparison of the target seed and the at least one of the identified set of candidate seeds.” These limitations, as drafted, but for the recitation of “by an agricultural computer system,” is a process that covers performance of the limitations in the mind but for the recitation of generic computer components. That is, but for the “by an agricultural computer system” language, nothing in the claim elements preclude the steps from practically being performed in the human mind. For example, with the exception of the “by an agricultural computer system” language, the claim steps in the context of the claim encompass a user mentally or manually performing the steps of the claim.
Dependent claims 2-4, 8-9, 12-14, and 18-19 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration.
Dependent claims 10 and 20 will be evaluated under Step 2A, Prong 2 below.
Step 2A, Prong 2: Independent claims 1 and 11 do not integrate the judicial exception into a practical application. Independent claim 1 recites steps performed “automatically” and/or “by the computing device.” Independent claim 1 recites additional elements including “receiving, by an agricultural computer system, a request for a planting recommendation, from a user, through a mobile application at a field manager computing device,” “accessing, by the agricultural computer system, data from a data server,” and “outputting, by the agricultural computer system, to the user, through the mobile application at the field manager computing device, the identified set of candidate seeds to a user.” Independent claim 11 recites “A system for use in identifying a set of candidate seeds for planting in a target field based on a prediction model, the system comprising at least one processor configured, by executable instructions, to” within the preamble of the claim. Independent claim 11 recites abstract limitations including “receive a request for a planting recommendation, from a user, through a mobile application at a field manager computing device,” “access data from a data server,” and “output, to the user, through the mobile application at the field manager computing device, the identified set of candidate seeds to a user.” These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Independent claim 1 recites additional elements including “training, by the agricultural computer system, from the data representative of hundreds of seeds, a yield delta prediction model for a plurality of candidate seeds, based, at least in part, on the filtered data, a Bayesian framework and a plurality of yield deltas expressed as:
d
i
j
1
j
2
=
z
j
1
-
z
j
2
+
σ
i
ε
i
j
1
j
2
; wherein di is the yield delta,
z
j
1
and
z
j
2
are yield advantages of iterative pairs of the plurality of candidate seeds, and σiεi is a noise expression” and “for each one of the plurality of candidate seeds, automatically generating, using the trained yield delta prediction model, a probability….” Independent claim 11 recites abstract limitations including “train, from the data representative of hundreds of seeds, a yield delta prediction model for a plurality of candidate seeds, based, at least in part, on the filtered data, a Bayesian framework and a plurality of yield deltas expressed as:
d
i
j
1
j
2
=
z
j
1
-
z
j
2
+
σ
i
ε
i
j
1
j
2
; wherein di is the yield delta,
z
j
1
and
z
j
2
are yield advantages of iterative pairs of the plurality of candidate seeds, and σiεi is a noise expression” and “for each one of the plurality of candidate seeds, automatically generate, using the trained yield delta prediction model, a probability…” The limitations of training a model using a mathematical equation and applying the trained model to generate a probability, as drafted, provide nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Independent claim 1 recites additional elements including “in response to at least the identified set of candidate seeds, automatically planting, by an agricultural apparatus, in communication with the agricultural computer system and/or the field manager computing device, the target seed and at least one of the identified set of candidate seeds in the target field, in a split planting arrangement to permit direct comparison of the target seed and the at least one of the identified set of candidate seeds.” This limitation, as drafted, is nothing more than post-solution activity. This type of post-solution activity is not enough to prove integration into a practical application. See MPEP 2106.05(g).
Independent claim 11 recites abstract limitations including “transmit instructions for execution by an agricultural apparatus to automatically plant the target seed and at least one of the identified set of candidate seeds in the target field, in a split planting arrangement to permit direct comparison of the target seed and the at least one of the identified set of candidate seeds.” Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Therefore, the additional elements of the independent claims, when considered both individually and in combination, are not sufficient to prove integration into a practical application.
Dependent claims 2-4, 8-9, 12-14, and 18-19 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which does not integrate the judicial exception into a practical application.
Dependent claim 10 recites the additional element of “further comprising selecting said at least one of the identified set of candidate seeds, based on an input from the user, via the mobile application; and wherein automatically planting the target seed and at least one of the identified set of candidate seeds in the target field, in a split planting arrangement, is further based on the input from the user.” Dependent claim 20 recites the additional element of “wherein the at least one processor is further configured, by the executable instructions, to select said at least one of the identified set of candidate seeds, based on an input from the user, via the mobile application at the field manager computing device, in response to the output of the identified set of candidate seeds to the user through the mobile application; and wherein the at least one processor is configured, by the executable instructions, to transmit the instructions for execution by the agricultural apparatus to automatically plant the target seed and the at least one of the identified set of candidate seeds in the target field, in response to the input from the user.” Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
Therefore, the additional elements of the dependent claims, when considered both individually and in the context of the independent claims, are not sufficient to prove integration into a practical application.
Step 2B: Independent claims 1 and 11 do not comprise anything significantly more than the judicial exception. Independent claim 1 recites steps performed “automatically” and/or “by the computing device.” Independent claim 1 recites additional elements including “receiving, by an agricultural computer system, a request for a planting recommendation, from a user, through a mobile application at a field manager computing device,” “accessing, by the agricultural computer system, data from a data server,” and “outputting, by the agricultural computer system, to the user, through the mobile application at the field manager computing device, the identified set of candidate seeds to a user.” Independent claim 11 recites “A system for use in identifying a set of candidate seeds for planting in a target field based on a prediction model, the system comprising at least one processor configured, by executable instructions, to” within the preamble of the claim. Independent claim 11 recites abstract limitations including “receive a request for a planting recommendation, from a user, through a mobile application at a field manager computing device,” “access data from a data server,” and “output, to the user, through the mobile application at the field manager computing device, the identified set of candidate seeds to a user.” These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Independent claim 1 recites additional elements including “training, by the agricultural computer system, from the data representative of hundreds of seeds, a yield delta prediction model for a plurality of candidate seeds, based, at least in part, on the filtered data, a Bayesian framework and a plurality of yield deltas expressed as:
d
i
j
1
j
2
=
z
j
1
-
z
j
2
+
σ
i
ε
i
j
1
j
2
; wherein di is the yield delta,
z
j
1
and
z
j
2
are yield advantages of iterative pairs of the plurality of candidate seeds, and σiεi is a noise expression” and “for each one of the plurality of candidate seeds, automatically generating, using the trained yield delta prediction model, a probability….” Independent claim 11 recites abstract limitations including “train, from the data representative of hundreds of seeds, a yield delta prediction model for a plurality of candidate seeds, based, at least in part, on the filtered data, a Bayesian framework and a plurality of yield deltas expressed as:
d
i
j
1
j
2
=
z
j
1
-
z
j
2
+
σ
i
ε
i
j
1
j
2
; wherein di is the yield delta,
z
j
1
and
z
j
2
are yield advantages of iterative pairs of the plurality of candidate seeds, and σiεi is a noise expression” and “for each one of the plurality of candidate seeds, automatically generate, using the trained yield delta prediction model, a probability…” The limitations of training a model using a mathematical equation and applying the trained model to generate a probability, as drafted, provide nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Independent claim 1 recites additional elements including “in response to at least the identified set of candidate seeds, automatically planting, by an agricultural apparatus, in communication with the agricultural computer system and/or the field manager computing device, the target seed and at least one of the identified set of candidate seeds in the target field, in a split planting arrangement to permit direct comparison of the target seed and the at least one of the identified set of candidate seeds.” These limitations, as drafted, are nothing more than post-solution activity. This finding is supported by the fact that the instant specification, in at least [0099, 0134-0135, 0140], merely discloses the use of the apparatus to plant the at least one seed. In particular, paragraph [0099] merely discloses that the “to receive one or more scripts that are used to control an operating parameter of the agricultural apparatus (or another agricultural vehicle or implement) from the agricultural computer system 116 (e.g., planting instructions generated by the agricultural computer system 116 and transmitted to a planter agricultural apparatus that then control operation of the planter agricultural apparatus to plant certain selected seeds (e.g., in a particular manner, etc.), etc.).” The specification merely describes the capabilities of the apparatus to perform operations in a “particular manner.” However, the specification does not describe how the agricultural apparatus itself operates on a technical level to perform the automatic planting of the seeds. The instant specification does not disclose any particular manner or means by which the agricultural apparatus operates in response to the instructions other than what is well-understood, routine, and conventional because Applicant is relying on a person having ordinary skill in the art to recognize how the agricultural apparatus performs the planting operation in response to the scripted instructions. Therefore, this additional element, as drafted, as shown by the original disclosure, is nothing more than post-solution activity, which is not anything significantly more than the judicial exception.
Independent claim 11 recites abstract limitations including “transmit instructions for execution by an agricultural apparatus to automatically plant the target seed and at least one of the identified set of candidate seeds in the target field, in a split planting arrangement to permit direct comparison of the target seed and the at least one of the identified set of candidate seeds.” Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) anything significantly more than the judicial exception. See MPEP 2106.05(f).
Therefore, the additional elements of the independent claims, when considered both individually and in combination, are not anything significantly more than the judicial exception.
Dependent claims 2-4, 8-9, 12-14, and 18-19 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which does not integrate the judicial exception into a practical application.
Dependent claim 10 recites the additional element of “further comprising selecting said at least one of the identified set of candidate seeds, based on an input from the user, via the mobile application; and wherein automatically planting the target seed and at least one of the identified set of candidate seeds in the target field, in a split planting arrangement, is further based on the input from the user.” Dependent claim 20 recites the additional element of “wherein the at least one processor is further configured, by the executable instructions, to select said at least one of the identified set of candidate seeds, based on an input from the user, via the mobile application at the field manager computing device, in response to the output of the identified set of candidate seeds to the user through the mobile application; and wherein the at least one processor is configured, by the executable instructions, to transmit the instructions for execution by the agricultural apparatus to automatically plant the target seed and the at least one of the identified set of candidate seeds in the target field, in response to the input from the user.” Use of a computer or other machinery in its ordinary capacity for tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., mental processes) is not anything significantly more than the judicial exception. See MPEP 2106.05(f).
Therefore, the additional elements of the dependent claims, when considered both individually and in the context of the independent claims, are not anything significantly more than the judicial exception.
Accordingly, claims 1-4, 8-14, and 18-20 are rejected under 35 USC 101.
Allowable Subject Matter
Claims 1 and 10 are rendered neither obvious nor anticipated by the available field of prior art. With respect to claims 1 and 10, the prior art of the record does not teach the claim combination of: training, by the agricultural computer system, from the data representative of hundreds of seeds, a yield delta prediction model for a plurality of candidate seeds, based, at least in part, on the filtered data, a Bayesian framework and a plurality of yield deltas expressed as:
d
i
j
1
j
2
=
z
j
1
-
z
j
2
+
σ
i
ε
i
j
1
j
2
;
wherein di is the yield delta,
z
j
1
and
z
j
2
are yield advantages of iterative pairs of the plurality of candidate seeds, and σiεi is a noise expression.
As drafted, are rendered neither obvious nor anticipated by the available field of prior art. The closest prior art of the record discloses:
Leibman et al. (Comparative analysis of maize (Zea mays) crop performance: natural variation, incremental improvements and economic impacts, 2014) discloses the yield delta is the sum of the variances of yield from each hybrid minus twice the covariance of yield from the two hybrids. However, Leibman fails to explicitly disclose finding the difference between the variances, adding a noise expression, and applying a Bayesian framework.
Griffin et al. (US 20140278731 A1) discloses optimizing a bundle of crop varieties to meet a yield goal with the minimal amount of covariance risk. However, Griffin fails to explicitly disclose the claimed equation above and applying a Bayesian framework.
Jiang et al. (US 20200134486 A1) discloses determining predicted yield performance for one or more seeds using a mixed genomic BLUP (best linear unbiased prediction) model including an error value. However, Jiang fails to explicitly disclose the claimed equation above and applying a Bayesian framework.
Therefore, the present independent claims are rendered neither obvious nor anticipated by the available field of prior art. However, these claims are not in condition for allowance because they remain rejected under 35 USC 101, as set forth in the instant office action. See the detailed rejection above.
As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Stark et al. (US 6662185 B1) discloses assessing wide area performance of a crop variety using a linear mixed model that includes parameters for fixed effects, random effects, and covariances, which is related to the independent claim limitations including at least “σiεi is a noise expression”
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. 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 nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Sara G Brown whose telephone number is (469)295-9145. The examiner can normally be reached M-F 8:00 am- 5:00 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, Brian Epstein can be reached at (571) 270-5389. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SARA GRACE BROWN/Primary Examiner, Art Unit 3625
Prosecution Insights