DETAILED ACTION
Non-Final Rejection
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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 3-4, 6-9 and 19 are rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claims 3-4, 6-9 and 19 recite the term " preferably". It is not clear whether this element with following limitation elements are part of the claim invention or not. Because, the term “preferably” refers to an alternate/optional solution/element and insignificant in claim invention. Therefore, claim is considered to be indefinite.
The remaining claims are also rejected under 35 U.S.C. 112(b), for being dependent upon a rejected base claim.
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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 1-14, 16, 18-21 and 24 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Each of claims1, 3, 6-7 and 10-14 falls within one of the four statutory categories. See MPEP § 2106.03. For example, each of claims 1-14, 16, 18-19 fall within category of process; each of claim 20-21 and 24 falls within category of machine, i.e., a “concrete thing, consisting of parts, or of certain devices and combination of devices.” Digitech, 758 F.3d at 1348–49, 111 USPQ2d at 1719 (quoting Burr v. Duryee, 68 U.S. 531, 570, 17 L. Ed. 650, 657 (1863)).
Regarding Claims 1-14, 16, 18-19
Step 2A – Prong 1
Exemplary claim 1 is directed to an abstract idea of corrected plant-related index data .
The abstract idea is set forth or described by the following italicized limitations:
A computer-implemented method for providing corrected plant-related index data, the method comprising:
providing initial plant-related index data for an agricultural field; and
correcting the initial plant-related index data for the agricultural field at least based on historical plant-related index data for the agricultural field and providing corrected plant-related index data.
The italicized limitations above represent combination of mathematical concepts (i.e., a process that can be performed by mathematical relationships or rules or idea) and mental step (i.e., a process that can be performed by can be performed mentally and/or with pen and paper or a mental judgment). Therefore, the italicized limitations fall within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance.
For example, the limitations “correcting the initial plant-related index data for the agricultural field at least based on historical plant-related index data for the agricultural field and providing corrected plant-related index data ” are combination of mathematical concepts (i.e., a process that can be performed by mathematical relationships or rules or idea) and mental step (i.e., a process that can be performed by can be performed mentally and/or with pen and paper or a mental judgment), see 2106.04(a)(2). Limitations (are considered together as a single abstract idea for further analysis. (discussing Bilski v. Kappos, 561 U.S. 593 (2010)).
Step 2A – Prong 2
Claims 1 does not include additional elements (when considered individually, as an ordered combination, and/or within the claim as a whole) that are sufficient to integrate the abstract idea into a practical application.
For example, additional first element is “providing initial plant-related index data for an agricultural field” to be performed, at least in-part, these additional elements appear to only add insignificant extra-solution activity (e.g., data gathering) and only generally link the abstract idea to a particular field. Therefore, this element individually or as a whole does not provide a practical application. See MPEP 2106.05(g)
In view of the “additional element” individually does not provide a practical application of the abstract idea. Furthermore, the “additional elements” in combination amount to a generic system with extra solution activity. The combination of additional elements does no more than generally link the use of the abstract idea to a particular technological environment, and for this additional reason, the combination of additional elements does not provide a practical application of the abstract idea.
Step 2B
Claims1 does not include additional elements, when considered individually and as an ordered combination, that are sufficient to amount to significantly more than the abstract idea..
The reasons for reaching this conclusion are substantially the same as the reasons given above in § Step 2A – Prong 2. For brevity only, those reasons are not repeated in this section. See MPEP §§ 2106.05(g) and MPEP §§2106.05(II).
Dependent Claims 2-14, 16, 18-19
Dependent claims 2-14, 16, 18-19 fail to cure this deficiency of independent claim 1 (set forth above) and are rejected accordingly. Particularly, claim 6 recite limitations that represent (in addition to the limitations already noted above) either the abstract idea or an additional element that is merely extra-solution activity, mere use of instructions and/or generic computer component(s) as a tool to implement the abstract idea, and/or merely limits the abstract idea to a particular technological environment.
For example, the limitations of Claims 2-3, 7-13, 16, 18: to be performed, at least in-part, these additional elements appear to only add insignificant extra-solution activity (e.g., data gathering) and only generally link the abstract idea to a particular field. Therefore, this element individually or as a whole does not provide a practical application. See MPEP 2106.05(g)
For example, the limitations of Claims 4-6, 14, 19: a combination of mathematical concepts (i.e., a process that can be performed by mathematical relationships or rules or idea) and mental step (i.e., a process that can be performed by can be performed mentally and/or with pen and paper or a mental judgment). Therefore, the italicized limitations fall within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance.
Regarding Claims 20-21 and 24
Claims 20-21 and 24 contains language similar to claims 1 as discussed in the preceding paragraphs, and for reasons similar to those discussed above, claims 20-21 and 24 are also rejected under 35 U.S.C. § 101(abstract idea).
Furthermore, Claim 20-21, recites additional element is “ a system, a processing unit, processor, ”. This element amounts to mere use of a generic computer system which is well understood routine and conventional (see background of current discloser and IDS) and this element individually does not provide a practical application. In view of the above, the “additional element” individually or combine does not provide a practical application of the abstract idea. see MPEP 2106.05(d).
Claim 24, recites additional element is “ A control device for controlling an agricultural equipment based on an application map of an agricultural field, ”. This element amounts to mere use of a generic control system of an agricultural equipment which is well understood routine and conventional (see background of current discloser and IDS) and this element individually does not provide a practical application. In view of the above, the “additional element” individually or combine does not provide a practical application of the abstract idea. see MPEP 2106.05(d).
Claim Rejections - 35 USC § 102
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-2, 11,14, 16, 18, 20-21 and 24is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Itakura et al. (US 2024/0177478).
Regarding Claims 1, 20-21 and 24. Itakura teaches a computer-implemented method for providing corrected plant-related index data, the method comprising-the steps of(figs. 2, 11 &16):
(A control device for controlling an agricultural equipment based on an application map of an agricultural field based on corrected plant-related index data)(as cited in claim 24)( controller: fig. 2; [0006], an equipment management device: [0097]; variable fertilization is thus achieved on the basis of the fertilizer quantity rate map: [0117], [0174])
providing initial plant-related index data for an agricultural field(DT2: fig. 11); and
correcting the initial plant-related index data for the agricultural field(FN3: fig. 11; s110: fig.11) at least based on historical plant-related index data for the agricultural field (DT6: fig. 11) and providing corrected plant-related index data(DT5: fig. 11).
Regarding Claim 2. Itakura further teaches wherein the plant-related index data is: leaf area index (LAI) data, leaf chlorophyll content (LC) data, canopy chlorophyll content (CCC) data, normalized difference vegetation index (NDVI) data, canopy biomass data, canopy nitrogen content data, leaf canopy content data of the plant or vegetation water content data (NDVI: fig.11).
Regarding Claim 11. Itakura further teaches providing boundary data based on the historical plant-related index data representing boundaries(Gr) for the corrected plant-related index data([0190]-[0192]).
Regarding Claim 14. Itakura further teaches correcting the initial plant-related index data for the agricultural field is based on a correction term based on a statistical model at least derived from the historical plant-related index data of the agricultural field, and wherein the correction term is additionally based on predefined rules in view of the typical ranges with respect to the crop variety, crop type, growth stage and/or soil condition(DT4, Fn3:[0178]-[0180], [0199], [0246]-[0247]; fig.16-17).
Regarding Claim 16. Itakura further teaches the correction term is additionally based on at least one crop- specific statistical model(fn3: [0178]-[0180], [0212][0216]; fig. 17), and wherein the dataset constituting the historical plant-related index data(DT;6: 0069]-[0070],[0140], [0190]-[0191]) is obtained from any combination of different available sources, including satellite images, unmanned aerial vehicles, agricultural robots, handheld or mounted cameras, and/or other measurement devices located on the agricultural field([0069]-[0071], [0119]).
Regarding Claim 18. Itakura further teaches a processor queries, identifies, obtains, standardizes, and outputs the relevant historical plant-related index data of possibly various origins to the correction algorithm(figs 2, 11-12).
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.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Itakura in view of Marciano et al. (US 2022/0301301).
Regarding Claim 3. Itakura further teaches the plant-related index data is based on images(multispectral camera, flying object , satellite communication: [0119],[0065], [0073]), wherein the images are preferably in the visible and/or near infrared range (NIR)([0119]).
Itakura silent about the plant-related index data is based on satellite images, wherein the satellite images are preferably in the visible and/or near infrared range.
However, Marciano teaches the plant-related index data is based on satellite images, wherein the satellite images are preferably in the visible and/or near infrared range([0023]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Itakura, the plant-related index data is based on satellite images, wherein the satellite images are preferably in the visible and/or near infrared range, as taught by Marciano, so as to enable improving accuracy in classifying and localizing pixels corresponding to the feature of interest to include more information together with the original pixel values in the satellite image.
Claim(s) 4-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Itakura in view of Yao et al. (US 2024/0135570).
Regarding Claim 4. Itakura silent about the plant-related index data, preferably the initial leaf area index data, for the agricultural field is obtained by using a calibrated mathematical model based on the plant-related index data, preferably the leaf area index data, and surface reflectance bands of the at least one satellite image.
However, Yao teaches the plant-related index data, preferably the initial leaf area index data, for the agricultural field is obtained by using a calibrated mathematical model based on the plant-related index data, preferably the leaf area index data, and surface reflectance bands of the at least one satellite image (NIR in the red-edge area of the multispectral curve of the wheat canopy extracted from the Sentinel-2 satellite image, determining calculation formulas of different slopes by way of permutation and combination, totally 10 slopes; and [0034] b, based on the calculation formulas of the 10 different slopes, respectively calculating the slope of the red-edge area of the multispectral curve of the wheat canopy and the slope of the red-edge area of the multispectral curve of the field background; acquiring 10 different SATF.sub.R2-R1 through step (2); and performing linear fitting on the obtained SATF.sub.R2-R1 with the LAI measured value of the corresponding growth stage, where SATF.sub.R2-R1 with the maximum degree of linear fitting R.sup.2 serves as the optimum option for estimating the LAI of wheat in the growth stage, and corresponding two bands are the optimum band combination, LAI estimation model: NIR-RE2:[0012], [0032]-[0037], [0064]-[0069]; fig. 2).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Itakura, the plant-related index data, preferably the initial leaf area index data, for the agricultural field is obtained by using a calibrated mathematical model based on the plant-related index data, preferably the leaf area index data, and surface reflectance bands of the at least one satellite image, as taught by Yao, so as to improve the estimation of the leaf area index in early stage of wheat growth.
Regarding Claim 5. Yao further teaches further teaches the calibrated mathematical model is adapted to different crop varieties, crop types, growth stage, soil conditions and/or data sources([0035]-[0039]).One of ordinary skill in the art would have been motivated to combine these references to render the claimed invention obvious for the same or similar reasons as described above in regard to parent claim 4, or similar.
Regarding Claim 6. Yao further teaches the calibrated mathematical model is a calibrated machine learning model and the plant-related index data for the agricultural field is obtained by using the calibrated machine learning model based on plant-related index data and surface reflectance bands of the at least one satellite image, wherein the machine learning model is preferably: an artificial neural network (ANN), multiple linear regression, random forest regression, or an approach that is able to establish a statistical relationship to predict plant-related index data(LAI estimation model, empirically and linearly fit, a regression :[0064]-[0070],[0086]-[0091]). One of ordinary skill in the art would have been motivated to combine these references to render the claimed invention obvious for the same or similar reasons as described above in regard to parent claim 4, or similar
Claim(s) 7-10 and 12-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Itakura in view of Albrecht et al. (US 2018/0373932).
Regarding Claim 7. Itakura further teaches the historical plant-related index data of the agricultural field (DT6: fig. 11) is based on images([0119], [0073]), wherein the images are preferably in the visible and/or near infrared range (NIR)([0069]-[0070],[0190]-[0191]).
Itakura does not explicitly teach the historical plant-related index data of the agricultural field is based on satellite images, wherein the satellite images are preferably in the visible and/or near infrared range.
However, Albrecht teaches the historical plant-related index data of the agricultural field is based on satellite images, wherein the satellite images are preferably in the visible and/or near infrared range ([0059])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Itakura, the historical plant-related index data of the agricultural field is based on satellite images, wherein the satellite images are preferably in the visible and/or near infrared range, as taught by Albrecht, so as to generate an accurate and efficient crop prediction.
Regarding Claim 8. Itakura does not explicitly teach the historical plant-related index data of the agricultural field comprises satellite images of the agricultural field from a period between 1 and 5 years or satellite images from within the last twelve months, preferably between 2 year and 3 years.
However, Albrecht teaches the historical plant-related index data of the agricultural field comprises satellite images of the agricultural field from a period between 1 and 5 years or satellite images from within the last twelve months, preferably between 2 year and 3 years([0038]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Itakura, the historical plant-related index data of the agricultural field comprises satellite images of the agricultural field from a period between 1 and 5 years or satellite images from within the last twelve months, preferably between 2 year and 3 years, as taught by Albrecht, so as to generate an accurate and efficient crop prediction.
Regarding Claim 9. Itakura does not explicitly teach the historical plant-related index data of the agricultural field comprises satellite images of the agricultural field from a period between 1 and 30 days, preferably between 1 and 15 days, and especially preferred satellite images from the last 10 days.
However, Albrecht teaches the historical plant-related index data of the agricultural field comprises satellite images of the agricultural field from a period between 1 and 30 days, preferably between 1 and 15 days, and especially preferred satellite images from the last 10 days ([0038]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Itakura, the historical plant-related index data of the agricultural field comprises satellite images of the agricultural field from a period between 1 and 30 days, preferably between 1 and 15 days, and especially preferred satellite images from the last 10 days, as taught by Albrecht, so as to generate an accurate and efficient crop prediction.
Regarding Claim 10. Itakura does not explicitly teach the historical plant-related index data of the agricultural field comprises satellite images of the agricultural field from the actual growing season starting from the seeding time.
However, Albrecht teaches the historical plant-related index data of the agricultural field comprises satellite images of the agricultural field from the actual growing season starting from the seeding time([0038], [0045], [0056]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Itakura, the historical plant-related index data of the agricultural field comprises satellite images of the agricultural field from the actual growing season starting from the seeding time, as taught by Albrecht, so as to generate an accurate and efficient crop prediction.
Regarding Claim 12. Itakura does not explicitly teach providing an uncertainty-probability value based on the historical plant-related index data for the reliability of the corrected plant-related index data.
However, Albrecht teaches providing an uncertainty-probability value based on the historical plant-related index data for the reliability of the corrected plant-related index data(estimated probability, a probability that a certain crop type should be planted, taking in account historical data (e.g., crop rotational patterns, historical planting patterns, historical production costs, historical prices for crop types, historical demand for crop types, etc.). For example, new recommendations can be made regarding management practices (e.g., application of fertilizer, planting of a particular crop types, etc.) based on a deviation of the NDVI values compared with a mean value extracted from farms in close proximity. In some embodiments, generating the management plan includes estimating agricultural yield based on, for example, NDVI values, historical yield data and/or amount of planted acreage within the one or more parcels: [0046], [0056]-[0057]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Itakura, providing an uncertainty-probability value based on the historical plant-related index data for the reliability of the corrected plant-related index data, as taught by Albrecht, so as to generate an accurate and efficient crop prediction.
Regarding Claim 13. Itakura does not explicitly teach teaches the historical plant-related index data are crop-specific plant- related index data.
However, Albrecht teaches the historical plant-related index data are crop-specific plant- related index data ([0034], [0037]-[0038])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Itakura, the historical plant-related index data are crop-specific plant- related index data, as taught by Albrecht, so as to generate an accurate and efficient crop prediction.
Claim(s)19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Itakura in view of Groeneveld et al. (US 20160180473)
Regarding Claim 19. Itakura does not explicitly teach the models estimating plant-related index data from reflectance bands are either continuously or periodically updated, wherein independent measurements of plant-related index data available in the system and their corresponding reflectance bands are fed into a calibration algorithm, wherein the calibration algorithm uses the fed data to improve the performance of the calibrated mathematical model, preferably of the calibrated machine learning model.
However, Groeneveld teaches the models estimating plant-related index data from reflectance bands are either continuously or periodically updated, wherein independent measurements of plant-related index data available in the system and their corresponding reflectance bands are fed into a calibration algorithm, wherein the calibration algorithm uses the fed data to improve the performance of the calibrated mathematical model, preferably of the calibrated machine learning model(fig. 8; [0029]; [0104]; linear regression calibration procedure:[0164]-[0168]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Itakura, the models estimating plant-related index data from reflectance bands are either continuously or periodically updated, wherein independent measurements of plant-related index data available in the system and their corresponding reflectance bands are fed into a calibration algorithm, wherein the calibration algorithm uses the fed data to improve the performance of the calibrated mathematical model, preferably of the calibrated machine learning model, as taught by Groeneveld, so as to prescribe spatially-variable application rate of one or more nutrient for agricultural field, which utilizes NDVI as vegetation index that reliably permits comparison and calculation of vegetation across agricultural field at contemporaneous moment in time.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
a) Goyal et al. (US 20200074605) disclose a virtual satellite system may receive, re-project to a spatial resolution and interpolate to a desired temporal resolution, georeferenced data representing an image of a geographic region from a plurality of different satellites. Bias in the georeferenced data between the plurality of satellites is determined and based on which satellite's image data contains an identified minimum spatial resolution, vegetation index data may be set to one of the satellite's data, which may or may not be adjusted. A target image may be generated based on the set vegetation index data.
b) Suarez et al. (Image Vegetation Index through a Cycle Generative Adversarial Network, ieee, 2019
c) Lin et al. (US 20210201024) disclose In a crop identification method, multi-temporal sample remote sensing images labeled with first planting blocks of a specific crop are acquired. NDVI data of the sample remote sensing images are calculated. Noise of the NDVI data is reduced.
d) carlos et al. ( US 20230316555) disclose a set of images providing a visual evaluation of the performance of the data-processing method for computing crop coverage (CC) and CC×CHM at different growth stages on three wheat varieties with variable growth rates;
e) Riley et al. (US 20190107521) disclose guided agronomic trial management includes: identifying a field test for a geographic region; and determining field characteristics for the field test based on field data (e.g., current field data, historic field data, etc.) associated with the field test.
f) shriver et al. ( US 9652840) disclose managing nitrogen applied by nitrogen application equipment to a geographic region includes determining a growth stage for the geographic region using a crop module, and determining a nitrogen change for the geographic region based on the growth stage using a nitrogen change module, which can additionally or alternatively include determining an amount of nitrogen initially available for a geographic region.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMAD K ISLAM whose telephone number is (571)270-0328. The examiner can normally be reached M-F 9:00 a.m. - 5:00 p.m..
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A Turner can be reached at 571-272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMMAD K ISLAM/Primary Examiner, Art Unit 2857