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 .
DETAILED ACTION
Priority
Acknowledgment is made of applicant’s foreign priority claim, for U.S. Application No. 19/006,961, based on a foreign application filed on 01/04/2024.
Status of Claims
Claims 1–19 are pending in the application. Claims 1–2, 7–10, and 15 are rejected.
Claims 3–6, 11–14, and 16–19 are objected to.
Allowable Subject Matter
Claims 3–6, 11–14, and 16–19
Overview of Grounds of Rejection
Ground of Rejection
Claim(s)
Statute(s)
Reference(s)
Ground 1
1, 2, 7–10, 15
§ 103
Chang et al. (NPL), Wu et al. (NPL), and Zheng et al. (NPL)
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.
(Please see the cited paragraphs, sections, pages, or surrounding text in the references for the paraphrased content.)
Ground of Rejection 1
Claims 1, 2, 7, 8, 9, 10, 15 are rejected under 35 U.S.C. § 103 as being unpatentable over Chang et al. (NPL), in view of Wu et al. (NPL), and further in view of Zheng et al. (NPL).
As per Claim 1, Cheng teaches the following portion of Claim 1, which recites: “A three-dimensional (3D) reconstruction method for a multi-tillering crop plant, comprising following steps:”
Chang et al. teaches that “[t]his study proposes a geometric modeling method of wheat plants based on the 3D phytomer concept” and applies the concept to “multi-tiller crops.” Thus, Chang et al. teaches 3D reconstruction of a multi-tillering wheat plant. (Chang et al. (NPL), Abstract, p. 1.)
Chang alone does not explicitly teach all the limitation(s) of the claim. However, when combined with Wu et al. (NPL), they collectively teach some of the limitation(s).
Wu et al. teach the following portion of Claim 1, which recites:
“acquiring point cloud data of a to-be-reconstructed plant;”
Wu et al. teaches that “[a] terrestrial laser scanner Faro Focus3D X130 was used here to acquire the point clouds of selected plants indoor.” Thus, Wu et al. teaches acquiring point-cloud data of the plant being processed. (Wu et al. (NPL), Materials, Fig. 1, p. 3.)
Wu et al. teach the following portion of Claim 1, which recites:
“determining single-stem growth characteristic information of the to-be-reconstructed plant according to the point cloud data;”
Wu et al. describes maize as having “one stem and several leaves” and teaches that the point-cloud-derived skeleton permits estimation of “plant height and volume in plant scale, and leaf length, leaf inclination angle, leaf azimuth, and more traits in organ scale.” These stem and leaf measurements constitute the claimed single-stem growth characteristic information determined from point-cloud data.
(Wu et al. (NPL), Introduction, p. 2; Accuracy Analysis of Phenotypic Traits Using the Extracted Skeleton, Fig. 13, p. 9.)
Chang and Wu alone do not explicitly teach all the limitation(s) of the claim. However, when combined with Zheng et al. (NPL), they collectively teach all of the limitation(s).
Chang and Zheng teach the following portion of Claim 1, which recites: “acquiring a first reconstruction result of each single stem of the to-be-reconstructed plant according to the single-stem growth characteristic information and a 3D leaf template database, the 3D leaf template database comprising multiple leaf mesh models;”
Chang et al. teaches that “a geometric modeling approach was developed for wheat phytomers, in the form of single stem (Equation (2)), and single plant (Equation (3)).” It further teaches determining the tiller and phytomer numbers, selecting 3D phytomers from a database, and determining translation and rotation. Chang et al. then uses phytomer azimuth and height “to form a single stem.” Thus, Chang et al. teaches obtaining a first reconstruction result of each single stem according to the target plant’s growth characteristics. (Chang et al. (NPL), Section 3.3, p. 7; Section 4.1, Fig. 4, p. 9.)
For the claimed database, Zheng et al. teaches that “[a] total of 2775 points of leaf data were standardized in order to generate a leaf template database,” that “a triangular mesh model was then generated,” and that representative leaves from “14 categories” were selected to build the database. Thus, the database contains multiple leaf mesh models. (Zheng et al. (NPL), Sections 3.3.1-3.3.2, pp. 5-6.)
Chang teaches the following portion of Claim 1, which recites:
“determining a second reconstruction result of the to-be-reconstructed plant according to the first reconstruction result of the single stem;”
Chang et al. teaches that “[a] tiller was assembled by selecting 3D phytomer templates” and that “a wheat shoot was assembled by determining the rotation and translation matrices of the already constructed tiller models.” The already constructed tiller models correspond to the first reconstruction results, and the assembled wheat shoot corresponds to the second reconstruction result. (Chang et al. (NPL), Section 4.1, Fig. 4, p. 9.)
Chang teaches the following portion of Claim 1, which recites:
“and optimizing an azimuth of each leaf in the second reconstruction result to obtain a 3D reconstruction result of the to-be-reconstructed plant.”
Chang et al. includes a leaf azimuth parameter,
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, for each phytomer and teaches that “[t]he phytomer azimuth . . . was normalized to zero via rotational transformation.” During reconstruction, “the corresponding rotation matrix
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was determined using the azimuth . . . of each phytomer.” Accordingly, Chang et al. adjusts each leaf-bearing phytomer according to its target azimuth to produce the final plant model. (Chang et al. (NPL), Section 2.2, p. 4; Section 3.2, Equation (1), p. 6; Section 4.1, p. 9.)
The term “optimizing” is not used verbatim by Chang et al.; the mapping relies on treating azimuth normalization and azimuth-based rotational placement as the claimed azimuth optimization.
Before the effective filing date of the claimed invention, a person of ordinary skill in the art would have been motivated to apply Wu et al.’s point-cloud acquisition and skeleton-extraction method to Chang et al.’s multi-tiller wheat modeling framework to automate the determination of stem and leaf characteristics used for template selection and placement. A POSITA would further have incorporated Zheng et al.’s leaf mesh-template database and deformation method to improve leaf-shape accuracy and preserve morphological detail. The combination uses each technique for its established function and would predictably produce a detailed 3D plant model by reconstructing individual stems, assembling the stems into a plant, and adjusting leaf orientations according to measured azimuth information.
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As per Claim 2, Chang alone does not explicitly teach all the limitation(s) of the claim. However, when combined with Wu and Zheng, they collectively teach all of the limitation(s).
Wu teaches the following portion of Claim 2, which recites:
“The 3D reconstruction method for a multi-tillering crop plant according to claim 1, wherein the 3D leaf template database is obtained as follows: acquiring single-stem point cloud data of the to-be-reconstructed plant;”
Wu et al. describes maize as having “one stem and several leaves” and teaches that a laser scanner “was used here to acquire the point clouds of selected plants.” Thus, Wu et al. teaches acquiring point-cloud data of a single-stem plant. (Wu et al. (NPL), Introduction, p. 2; Materials, Fig. 1, p. 3.)
Wu teaches the following portion of Claim 2, which recites:
“acquiring a leaf point cloud segmented result according to the single-stem point cloud data of the to-be-reconstructed plant;”
Wu et al. teaches that plant morphological data may be 3D point clouds and that “[t]he first process is to segment these data into independent organs with semantics.” Because the disclosed single-stem maize contains leaves, the semantic organ segmentation yields a leaf point cloud segmented result. (Wu et al. (NPL), Introduction, p. 2.)
Wu teaches the following portion of Claim 2, which recites:
“acquiring leaf mesh models according to the leaf point cloud segmented result;”
Wu et al. further teaches that, following semantic organ segmentation, methods “3D reconstruct each organ into fine organ meshes.” Applied to the segmented leaf organs, this produces the claimed leaf mesh models according to the leaf point cloud segmented result. (Wu et al. (NPL), Introduction, p. 2.)
Zheng teaches the following portion of Claim 2, which recites:
“and obtaining the 3D leaf template database according to multiple different leaf mesh models.”
Zheng et al. teaches generating a “leaf template database,” generating a “triangular mesh model” from each leaf’s normalized data, and selecting representative leaves from “14 categories in order to build a leaf template database.” Thus, Zheng et al. teaches obtaining the database from multiple leaf mesh models having different representative shapes. (Zheng et al. (NPL), Sections 3.3.1-3.3.2, pp. 5-6; Fig. 3.)
Before the effective filing date of the claimed invention, a person of ordinary skill in the art would have been motivated to use Wu et al.’s point-cloud organ segmentation and organ-mesh reconstruction workflow to generate the leaf models used in Zheng et al.’s leaf template database. This modification would automate acquisition of diverse leaf templates, reduce manual digitization, and improve model throughput while predictably producing a database containing multiple leaf mesh models for subsequent plant reconstruction.
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Claim 7 does not include any additional limitations that would significantly distinguish it from claim 1. Therefore, it is likewise rejected under 35 U.S.C. § 103 in view of the same references and for the same reasons set forth above.
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Claim 8 does not include any additional limitations that would significantly distinguish it from claim 1. Therefore, it is likewise rejected under 35 U.S.C. § 103 in view of the same references and for the same reasons set forth above.
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Claim 9 does not include any additional limitations that would significantly distinguish it from claim 1. Therefore, it is likewise rejected under 35 U.S.C. § 103 in view of the same references and for the same reasons set forth above.
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Claim 10 does not include any additional limitations that would significantly distinguish it from claim 2. Therefore, it is likewise rejected under 35 U.S.C. § 103 in view of the same references and for the same reasons set forth above.
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Claim 15 does not include any additional limitations that would significantly distinguish it from claim 2. Therefore, it is likewise rejected under 35 U.S.C. § 103 in view of the same references and for the same reasons set forth above.
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Conclusion
The prior art made of record and relied upon in this action is as follows:
Patent Literature:
(none)
Non-Patent Literature (NPL):
USED
Zheng et al. — “Three-Dimensional Wheat Modelling Based on Leaf Morphological Features and Mesh Deformation”, 2022-02-07. Available at: [https://www.mdpi.com/2073-4395/12/2/414]
Chang et al. — “Geometric Wheat Modeling and Quantitative Plant Architecture Analysis Using Three-Dimensional Phytomers”, 2023-01-18. Available at: [https://www.mdpi.com/2223-7747/12/3/445]
Wu et al. — “An Accurate Skeleton Extraction Approach From 3D Point Clouds of Maize Plants”, 2019-03-07. Available at: [https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2019.00248/full]
Note: A PDF copy of each NPL reference is attached with this Office Action. URLs are included for applicant convenience. If a link becomes unavailable in the future, the citation information may be used to locate the reference or access archived versions via the Wayback Machine.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and is listed as follows:
Patent Literature:
(none)
Non-Patent Literature (NPL):
(none)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ADEEL BASHIR whose telephone number is (571) 270-0440. The examiner can normally be reached Monday-Thursday.
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/ADEEL BASHIR/
Examiner, Art Unit 2616
/DANIEL F HAJNIK/Supervisory Patent Examiner, Art Unit 2616
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