DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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., an abstract idea) without “significantly more.” Claims 1-20 are directed to generating a post-harvest trial block, clustering a training set, indicate a label for a target post-harvest trial block and storing the label, which is considered an abstract idea. Further, the claim(s) as a whole, when examined on a limitation-by-limitation basis and in ordered combination do not include an inventive concept.
Step 1 – Statutory Categories
As indicated in the preamble of the claims, the examiner finds the claims are directed to a process, machine, or article of manufacture.
Step 2A – Prong One - Abstract Idea Analysis
Exemplary claim 1 (and similarly claims 9 and 17) recites the following abstract concepts, in italics below, which are found to include an “abstract idea”:
A computer-implemented method for use in assessing treatment trials associated with agricultural fields, the method comprising:
for each of multiple treatment trials in agricultural fields, generating, by a computing device, a post-harvest trial block, based on multiple data layers associated with the agricultural field, the post-harvest trial block defining an area of the agricultural field associated with the treatment trial;
clustering, by a computing device, a training set of the post-harvest trial block based on one or more geospatial features of the areas of the post-harvest trial blocks;
training, by the computing device, a model to indicate a label for a target post-harvest trial block based on the one or more geospatial features of an area of the target post-harvest trial block; and
storing the label in a memory.
The claim features in italics above as drafted, under its broadest reasonable interpretation, are mental processes and/or certain methods of organizing human activity performed by generic computer components. That is, other than reciting “a computing device”, “training a model” and “a memory,” nothing in the claim element precludes the step from practically being performed in the mind or a method of organized human activity. For example, but for the “computing device”, “training a model” and “memory,” language, “for each of multiple treatment trials in agricultural fields, generating… a post-harvest trial block, based on multiple data layers associated with the agricultural field, the post-harvest trial block defining an area of the agricultural field associated with the treatment trial; clustering… a training set of the post-harvest trial block based on one or more geospatial features of the areas of the post-harvest trial blocks; indicate a label for a target post-harvest trial block based on the one or more geospatial features of an area of the target post-harvest trial block; and storing the label” in the context of this claim encompasses mental processes and/or certain methods of organizing human activity. If the claim limitations, under its broadest reasonable interpretation, covers steps which could be performed in the human mind including an observation, evaluation, judgement of opinion and/or fundamental economic practices, commercial or legal interaction or managing personal behavior or relationships or interactions between people but for the recitation of generic computer components, then it falls within the “mental process and certain method of organizing human activity” grouping of abstract ideas respectively. Accordingly, the claim recites an abstract idea.
Step 2A – Prong Two - Abstract Idea Analysis
This judicial exception is not integrated into a practical application. In particular, the claims only recite three additional elements – “a computing device” (claims 1 and 17) or “at least one processor” (claim 9), “training a model” (claims 1, 9 and 17) and “a memory” (claims 1, 9 and 17). The “computing device” or “processor”, “training a model” and “memory” are recited at a high-level of generality (i.e., as a generic processor performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using a generic computer component (MPEP 2106.05(f), i.e. the generating, clustering, training and storing steps) and linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h), i.e. treatment trials and post-harvest trial blocks). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B - Significantly More Analysis
The claim does not include additional elements that are sufficient to amount to
significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of the “computing device” or “processor”, “training a model” and “memory” amount to no more than mere instructions to apply the exception using a generic computer component and linking the use of the judicial exception to a particular technological environment or field of use. Mere instructions to apply the exception using a generic computer component and linking the use of the judicial exception to a particular technological environment or field of use cannot provide an inventive concept. Further, the background does not provide any indication that the “computing device” or “processor”, “training a model” and “memory” are anything other than generic, off-the-shelf computer components. For these reasons, there is no inventive concept. The claim is not patent eligible.
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, 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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over United States Patent Application Publication No. 2020/0193589 A1 to Peshlov et al. (“Pehlov”) in view of United States Patent Application Publication No. 2022/0274207 A1 to Sibley et al. (“Sibley”).
As per claims 1, 9 and 17 the claimed subject matter that is met by Peshlov includes:
a computer-implemented method for use in assessing treatment trials associated with agricultural fields, the method comprising (Peshlov: Abstract and ¶ 0121):
for each of multiple treatment trials in agricultural fields, generating, by a computing device, a post-harvest trial block, based on multiple data layers associated with the agricultural field, the post-harvest trial block defining an area of the agricultural field associated with the treatment trial (Peshlov: ¶¶ 0052, 0135 and 0174);
clustering, by a computing device, a training set of the post-harvest trial block based on one or more geospatial features of the areas of the post-harvest trial blocks (Peshlov: ¶¶ 0085, 0183 and 0188);
training, by the computing device, a model to indicate a label for a target post-harvest trial block based on the one or more geospatial features of an area of the target post-harvest trial block (Peshlov: ¶¶ 0170, 0183 and 0188-0191); and
storing the label in a memory (Peshlov: ¶¶ 0073, 0167, 0182 and 0220).
Peshlov does teach obtaining a training set, Peshlov fails to specifically teach the technical term of clustering. The Examiner provides Sibley to teach and disclose this claimed feature.
The claimed subject matter that is met by Sibley includes:
clustering (Sibley: ¶¶ 0108, 0160 and 0177)
Peshlov teaches an agriculture observation system and method. Sibley teaches a comparable agriculture observation system and method that was improved in the same way as the claimed invention. Sibley offers the embodiment of clustering. One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the adaptation of the clustering as disclosed by Sibley to the obtaining of data as taught by Peshlov for the predicted result of improved agriculture observation systems and methods. No additional findings are seen to be necessary.
As per claims 2, 10 and 18, the claimed subject matter that is met by Peshlov and Sibley includes:
further comprising assigning labels to the training set of the post-harvest trial blocks, prior to clustering the training set of post-harvest trial blocks (Peshlov: ¶¶ 0070 and 0170).
The motivation for combining the teachings of Peshlov and Sibley are discussed in the rejection of claims 1, 9 and 17, and are incorporated herein.
As per claims 3, 11 and 19, the claimed subject matter that is met by Peshlov and Sibley includes:
wherein the multiple data layers include a headlands layer, an emergent data layer, a split planting data layer, and a planting traversals data layer; and wherein the method further comprises combining the headlands data layer, the emergent data layer, the split planting data layer, and the planting traversals data layer into a post-planting trial block and then combining the post-planting trial block and a confounded data later into the post-harvest trial block (Peshlov: ¶¶ 0063, 0085-0086, 0113 and 0146).
It would have been obvious to a person of ordinary skill in the art at the time the invention was made to different layers of data than those specifically described in Peshlov and Sibley because merely displaying different layers from that in the prior art would have been obvious matter of design choice. See In re Japikse, 181 F.2d 1019, 86 USPQ 70 (CCPA 1950); In re Kuhle, 526 F.2d 553, 555, 188 USPQ 7, 9 (CCPA 1975). Further motivation for combining the teachings of Peshlov and Sibley are discussed in the rejection of claims 1, 9 and 17, and are incorporated herein.
As per claims 4 and 12, the claimed subject matter that is met by Peshlov and Sibley includes:
wherein clustering the training set of post-harvest trial blocks includes clustering, by a K-mean clustering algorithm, the training set of post-harvest trial blocks (Peshlov: ¶ 0114 and Sibley: ¶ 0108).
The motivation for combining the teachings of Peshlov and Sibley are discussed in the rejection of claims 1 and 9, and are incorporated herein.
As per claims 5, 13 and 20, the claimed subject matter that is met by Peshlov and Sibley includes:
wherein the model includes a classifier model and wherein training the model includes: training a classifier model with the training set of post-harvest trial blocks; appending labels to a portion of unlabeled post-harvest trial blocks; assessing a confidence of each appended label to the portion of the unlabeled post-harvest trial blocks; and based on the confidence, adding the unlabeled post-harvest trial blocks with the appended labels to the training set and retaining the classifier model (Sibley: ¶¶ 0109, 0112, 0194 and 0255).
The motivation for combining the teachings of Peshlov and Sibley are discussed in the rejection of claims 1, 9 and 17, and are incorporated herein.
As per claims 6 and 14, the claimed subject matter that is met by Peshlov and Sibley includes:
wherein training the model includes: clustering the training set of post-harvest trial blocks and a plurality of unlabeled post-harvest trial blocks; and appending labels to the unlabeled post-harvest trial blocks; and training the model based on the training set and the label post-harvest trial blocks (Peshlov: ¶¶ 0170 and 0190-0191).
The motivation for combining the teachings of Peshlov and Sibley are discussed in the rejection of claims 1 and 9, and are incorporated herein.
As per claims 7 and 15, the claimed subject matter that is met by Peshlov and Sibley includes:
wherein clustering the training set of post-harvest trial blocks and the plurality of unlabeled post-harvest trial blocks includes clustering, by a K-mean clustering algorithm, the training set of post-harvest trial blocks and the plurality of unlabeled post-harvest trial blocks (Sibley: ¶ 0108).
The motivation for combining the teachings of Peshlov and Sibley are discussed in the rejection of claims 1 and 9, and are incorporated herein.
As per claims 8 and 16, the claimed subject matter that is met by Peshlov and Sibley includes:
wherein the treatment trial is defined by the planting of two different hybrid seeds (Peshlov: ¶ 0085).
The motivation for combining the teachings of Peshlov and Sibley are discussed in the rejection of claims 1 and 9, and are incorporated herein.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Hunter Wilder whose telephone number is (571)270-7948. The examiner can normally be reached Monday-Friday 8:30AM-5:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Florian Zeender can be reached at (571)272-6790. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/A. Hunter Wilder/Primary Examiner, Art Unit 3627
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