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 14 has been canceled.
Specification
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” “The present invention relates to”, etc.
The abstract of the disclosure is objected to because it contains legal phraseology, specifically “The present invention relates to” in line 1 thereof. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
In view of the International Search Report completed on January 12, 2022 and mailed on January 20, 2022 in parent application PCT/EP2021/077956, and in view of the Written Opinion of the International Searching Authority cited in counterpart application EP 21789752 on April 24, 2023, claims 1-13 and 15-19 are rejected under 35 U.S.C. 102(a)91) as being anticipated by WO 2019/032648 A1.
With respect to claims 1 and 13, WO 2019/032648 A1 discloses a method and a system for forecasting of a parameter value of a cultivation area, the method comprising:
generating, by an ensemble modelling structure, at least one first-model output parameter related to the cultivation area using ensemble modelling based on at least one first-model input parameter (see for example §§7, 8, 14, 64, 65, 70, 74, 75, 77-79, 81: first-model input parameter: field information inputs as described in §§8, 14; ensemble modelling structure as described in §§7, 64, 65 and 79);
generating, by a machine learning structure, at least one second-model output parameter related to the cultivation area using machine learning based on at least one second-model input parameter (see for example §§8, 14, 64, 65, 66, 70, 74, 75, 77-79, 81: second-model input parameter: farming operation inputs as described in §§8, 14; machine learning structure as described in §§64 and 65); and
merging, by a model merging structure, the at least one first-model output parameter and the at least one second-model output parameter to calculate the parameter value of the cultivation area (see for example §§11, 77-79, 81: map combination corresponds to merging of output parameters in order to obtain a parameter value of the cultivation area as for example an expected crop productivity).
WO 2019/032648 A1 also describes the method for forecasting of a parameter value (c.f. claim 1 of the present application) of a cultivation area in connection with a method of applying an agricultural product as fertilizer and with a corresponding agricultural system/ equipment (see title of WO 2019/032648 A1 as well as paragraphs [0004] and [0014]).
As to claim 2, see paragraph [0084] of WO 2019/032648 A1.
Regarding claims 4 and 5, see paragraph [0008] of WO 2019/032648 A1.
With respect to claims 6-11, see figure 1 of WO 2019/032648 A1.
As to claim 12, see paragraphs [0062] and [0064] as well as figure 4 of WO 2019/032648 A1.
With respect to claims 3 and 15-19, see the disclosure in pages 1-2, paragraph [0004]; page 2, paragraph [0007] - page 3, paragraph [0008]; page 4, paragraph [0011]; pages 5-6, paragraph [0014]; page 27, paragraph [0062] - page 29, paragraph [0066]; pages 30-32, paragraph [0070]; page 33, paragraph [0074] - page 34, paragraph [0075]; page 35, paragraph [0077] - page 36, paragraph [0079]; page 37, paragraph [0081]; page 40, paragraphs [0084], [0085]; page 43, paragraph [0092] - page 45, paragraph [0095]; page 45, paragraphs [0097], [0098]; and the figures of WO 2019/032648 A1.
Reasoning for Claim Rejections Under 35 USC § 101 Not Being Present
No rejection under 35 USC § 101 is present since parent claim 1 is directed to machine learning, which does not involve human mental processes necessary for a rejection under 35 USC § 101 to be present.
Examiner Request
The examiner requests, in response to this office action, support must be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line number(s) in the specification and/or drawing figure(s). This will assist the examiner in prosecuting the application.
When responding to this office action, applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of art disclosed by the references cited or the objections made. He or she must also show how the amendments avoid such references or objections. In amending in reply to a rejection of claims in an application or patent under reexamination, the applicant or patent owner must clearly point out the patentable novelty which he or she thinks the claims present in view the state of the art disclosed by the references cited or the objections made. The applicant or patent owner must also show how the amendments avoid such references or objections.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Phillips et al. US 2014/0195466 A1 disclose integrated machine learning for a data management project.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER J NOVOSAD whose telephone number is (571)272-6993. The examiner can normally be reached on a variable schedule.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rocca M Joseph can be reached at 571-272-8971. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Christopher J. Novosad/Primary Examiner, Art Unit 3671
August 19, 2025