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
Response to Amendment
The present Office Action is in response to the Request for Continued Examination dated 03/04/2026.
In the amendment dated 03/04/2026, the following occurred: Claims 1, 5, 7, 8 and 13 were amended. Claim 6 was canceled. Claim 21 is new.
Claims 1-5 and 7-21 are currently pending.
Request for Continued Examination
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/04/2026 has been entered.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(I) because the following figure(s) is/are unreadable and/or are unsatisfactory for reproduction:
Fig. 6A
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the Examiner , the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claim 20 is objected to for the following informality: “… transmitting the second code to a receiving device.” should read “… transmitting the second code to the receiving device.”
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 1-5 and 7-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1, 12 and 19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
The claim recites a non-transitory computer-readable storage medium, a method and a system for facilitating traceability of animal based meat products, which are within a statutory category.
Step 2A1
Regarding claims 1, 12 and 19, the limitation of (claim 1 being representative) receiving a label-generating request for generating a machine-readable image file for an animal-based meat product, the animal-based meat product corresponding to a particular source animal; accessing, in response to receiving the label-generating request, digital animal records for a plurality of source animals to identify a digital animal record for the particular source animal corresponding to the animal-based meat product, the digital animal records comprising animal information for the plurality of source animals, the animal information comprising identification information, location information, and health information for the plurality of source animals; generating, according to the animal information, an animal health score for the particular source animal; generating, based on the animal record and the animal information of the digital animal record for the particular source animal of the animal-based meat product, a machine-readable image file for the particular source animal of the animal-based meat product, wherein the machine-readable image file, when decoded, makes available meat facts regarding the particular source animal of the animal-based meat product, the meat facts comprising the animal health score and the other information regarding the particular source animal; transmitting the machine-readable image file; receiving, after a sale of the animal-based meat product, purchaser data comprising purchaser-identifying information and a date of purchase; and updating the digital animal records with the purchaser data such that the sale of the animal-based meat product is linked to a particular purchaser in the digital animal records and regarding claim 12- the limitation decoding data coded in an optical scan of a physical representation of a machine-readable image file located on a label for an animal-based meat product; and displaying the meat facts about the particular source animal associated with the animal-based meat product; and regarding claim 19- the limitation of stores a plurality of digital animal records for a plurality of animals, the plurality of digital animal records comprising identifying information for the plurality of animals and animal health information for the plurality of animals; updating the digital animal record corresponding to the source animal associated with the animal-based meat product with the first code for identifying the source animal as drafted, is a process that, under the broadest reasonable interpretation, covers certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions) but for the recitation of generic computer components. The claims encompass a series of rules or instructions for a person or persons to follow, with or without the aid of a computer, to receive label-generating request, access animal records, generate an animal health score, generate a machine-readable image file, transmit the machine-readable image file, receive purchaser data and update digital animal records in the manner described in the identified abstract idea, supra. The rules or instructions are the claimed steps of “receiving…accessing…generating… generating… transmitting… receiving and updating” as indicated supra.
Other than reciting generic computer components (discussed infra), i.e., a non-transitory computer-readable storage medium and one or more processors (in claim 1) and a non-transitory computer-readable storage medium, one or more processors and a storage system (in claim 19), the claimed invention amounts to managing personal behavior or interaction between people. The Examiner notes that Claim 12 is not tied to any particular technological environment. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A2
This judicial exception is not integrated into a practical application. In particular, claim 12 is purely directed to an abstract idea without the recitation of any additional elements. Claim 1 recites the additional elements of a non-transitory computer-readable storage medium and one or more processors. Claim 19 recites the additional elements of a non-transitory computer-readable storage medium, one or more processors and a storage system. These additional elements are not exclusively defined by the applicant and are recited at a high-level of generality (i.e., a generic computer components for enabling access to medical information or for performing generic computer functions, see Spec. at para. [0031], [0034], [0037], [0053], [0055], [0195] and [0196]) such that they amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, even in combination, 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.
Claim 1 further recite the additional element of a requesting device. Claim 12 recite the additional element of a user device. Claim 19 recite the additional element of a storage system and a receiving device. These additional element are recited at a high level of generality (i.e. a general means to receive/decode/access/display data) and amount to extra solution activity. MPEP 2106.04(d)(I) indicates that extra-solution data gathering activity cannot provide a practical application. Claims 1 and 12 also recited the additional element of a machine-readable image file. This additional element merely generally links the abstract idea to a particular technological environment or field of use. MPEP 2106.04(d)(I) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide a practical application. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application.
Step 2B
The claims do 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 a non-transitory computer-readable storage medium, one or more processors and a storage system to perform the noted steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”).
Also as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a requesting device, a user device and a receiving device were considered extra-solution activity. This has been re-evaluated under “significantly more” analysis and determined to be well-understood, routine and conventional activity in the field. MPEP 2016.05(d)(II) indicates that receiving and/or transmitting data over a network has been held by the courts to be well-understood, routine and conventional activity (citing Symantec, TLI Communications, OIP Techs., and buySAFE). The additional element of a machine-readable image file was determined to generally link the abstract idea to a particular technological environment or field of use. This has been re-evaluated under the “significantly more” analysis and has also been found insufficient to provide significantly more. MPEP 2106.05(A) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide significantly more. Moreover, the prior art of record indicates that machine-readable image file is well-understood, routine, conventional activity (see Poliska at [0002], [0007] and [0027] and Kanitz at ([0016], [0024] and [0027]). Well-understood, routine and conventional activity cannot provide an inventive concept (“significantly more”). Therefore when considering the additional elements alone, and in combination, there is no inventive concept in the claim, and thus the claim is not patent eligible.
The Examiner notes that: A well-known, general-purpose computer has been determined by the courts to be a well-understood, routine and conventional element (see, e.g., Alice Corp. v. CLS Bank; see also MPEP 2106.05(d));
Claims 2-5, 7-11, 13-18 and 20-21 are similarly rejected because they either further define/narrow the abstract idea and/or do not further limit the claim to a practical application or provide as inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination. Claim(s) 2 and 4 merely describe(s) the machine-readable image file when decode. Claim(s) 3 merely describe(s) receiving an information request, accessing the health information, generating data and transmitting data for display. Claim(s) 3 includes the additional element of “a user device” which is analyzed the same as the “requesting device” in claim 1 and does not provide a practical application or significantly more for the same reasons. Claim(s) 5 merely describe(s) the meat facts. Claim(s) 7 merely describe(s) receiving a request, accessing the digital animal record and transmitting the location information. Claim(s) 8 merely describe(s) generating an animal health score and updating the digital animal records. Claim(s) 8 includes the additional element of “an artificial intelligence engine” to analyze the animal information. This is interpreted as “apply it” to the abstract idea and does not provide practical application or significantly more, see MPEP 2106.04(d)(I) and MPEP2106.05(I)(A). Claim(s) 9 merely describe(s) the animal based meat product. Claim(s) 10 merely describe(s) the particular source. Claim(s) 11 merely describe(s) the machine-readable image file. Claim(s) 13 merely describe(s) the physical representation of the machine-readable image file. Claim(s) 14, 16 and 18 merely describe(s) the meat facts. Claim(s) 14 and 16 includes the additional element of “a processing system”, which is analyzed the same as the one or more processors in claims 1 and 19 and does not provide practical application or significantly more for the same reasons. Claim(s) 15 merely describe(s) the data coded. Claim(s) 17 merely describe(s) the website address. Claim(s) 20 merely describe(s) receiving a request, accessing the digital animal record, generating a second code, updating the digital animal record and transmitting the second code. Claim(s) 21 merely describe(s) receiving a recall request, accessing the digital animal record and purchaser data and transmitting recall notification. Claims 2-5, 7-11, 13-18 and 20-21 further define the abstract idea and are rejected for the same reason presented above with respect to claims 1, 12 and 19.
Claim Rejections - 35 USC § 103
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 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 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-5, 7, and 9-21 are rejected under 35 U.S.C. 103 as being unpatentable over Poliska (US 2004/0236191), in view of Kanitz US (2007/0005173) and in further view of Beier (US 2017/0293882).
REGARDING CLAIM 1
Poliska discloses A non-transitory computer-readable storage medium storing a program for execution by one or more processors, the program including instructions for: a machine-readable image file for an animal-based meat product, the animal-based meat product corresponding to a particular source animal ([0002] teaches bar-code labels (interpreted by Examiner as the machine-readable image file for an animal-based meat product) affixed to animal carcasses and [0007] teaches a label with the identifier is attached onto the packaged meat portion. The label provides identifying information about the livestock product); accessing, in response to receiving the label-generating request, digital animal records for a plurality of source animals to identify a digital animal record for the particular source animal corresponding to the animal-based meat product, the digital animal records comprising the animal information comprising identification information ([abstract] teaches labelling livestock products with such information as country, place and date of origin, among other things (interpreted by Examiner as the label generating of Kanitz below). [0007] teaches the label provides identifying information about the livestock product (interpreted by Examiner as the animal information comprising identification information). [0019] teaches the use of a database for storage and management of information. [0032] teaches the information on animal's place and country of origin, for example, as well as other data, is forwarded to a remotely located back-end portal. The portal comprises server and database for document management, statistical processing of information, and report generation and [0027] teaches scanning the tag with an RFID reader. Once the tag is read by the RFID reader, the information stored in the tag is transferred via a wireless medium to the RFID reader. One or more application programs running on the server create a record for each carcass. As shown in FIG. 5, the record is then displayed on a message panel at the operator station (where the record is interpreted by Examiner as the digital animal records for a plurality of source animals)); generating, based on the animal information of the digital animal record for the particular source animal of the animal-based meat product, a machine-readable image file for the particular source animal of the animal-based meat product ([0031] teaches the tag is read by the RFID reader. In particular, the tag emits an RF signal that uniquely identifies the particular meat portion (tenderloin and big loin) when energized by the RFID reader. A number of pre-printed bar-code labels, arranged in pairs such that the first bar-code label is identical to the second bar-code label in any given pair, are available to operators for packaging the meat product. Each pair of the bar-code labels, printed, corresponds to a tag. The cross-reference of each tag with a pair of labels is maintained on a server (FIG. 10), such that the information in each tag is contained in the bar-code label (interpreted by Examiner as generating, based on the animal information of the digital animal record for the particular source animal of the animal-based meat product, a machine-readable image file for the particular source animal of the animal-based meat product));
Poliska does not explicitly disclose receiving a label-generating request for generating a machine-readable image file for an animal-based meat product, the digital animal records comprising animal information for the plurality of source animals, the animal information comprising identification information, location information, and health information for the plurality of source animals, generating, according to the animal information, an animal health score for the particular source animal, generating, based on the animal score a machine-readable image file for the particular source animal of the animal-based meat product, wherein the machine-readable image file, when decoded, makes available meat facts regarding the particular source animal of the animal-based meat product, the meat facts comprising the animal health score and other information regarding the particular source animal and transmitting the machine-readable image file to a requesting device, however Kanitz discloses:
receiving a label-generating request for generating a machine-readable image file for an animal-based meat product (Kanitz at [0016] teaches generating labels, [0024] teaches the 2D barcode label may be generated by printing and read by a CCD camera. [0027] teaches EID (electronic identification device) reader for reading EID tag on livestock (commodity graphically illustrated by circle). The data retrieved from the EID reader is received by computer and posted to a network for receipt and storage by server (see FIG. 1). In addition to sharing the data retrieved from the tag, the computer induces a 2D barcode printer to generate a 2D barcode label, which is applied to commodity (interpreted by Examiner as means to receive request for generating a machine-readable image file for an animal-based meat product)); the digital animal records comprising animal information for the plurality of source animals, the animal information comprising identification information, location information, and health information for the plurality of source animals (Kanitz at [0003] teaches records to provide country of origin information to retailers, including the "born, raised, and slaughtered" information required to make U.S. origin claims for the covered commodities beef, pork, and lamb. To verify products are properly labeled at the retail level, records must be maintained from an animal's birth to retail. [0016] teaches a tracking and labeling system for recording and reporting data about a commodity such as a steer may come into existence in a first environment, a farm where it is born and raised. The steer may be sold and shipped to a meat processing plant at another location where it is butchered and processed into meat products (e.g., sides of beef or other large cuts of meat). The meat products may then be shipped to a retail store, for further processing and packaging into retail packages of meat. At each point in this sequence of events, data concerning the commodity may be noted and recorded by local (node) data capture and processing systems. Attributes of interest, such as age, breed, weight, source, appearance, veterinary record, feed history, etc. may have been previously recorded data, recorded on some media, such as an Electronic Identification Tag (EID) tag, Radio Frequency Identification (RFID), color-coded image, barcode or 2D barcode label (interpreted as the label of Poliska). In the farm environment, a steer would typically have an EID tag fastened to it at birth or soon after. The EID tag would record owner information, birth date, breed, identification number, etc. The data "written" on the EID tag would be an example of recorded data on media. [0018] teaches in addition to the recorded data on media, it would be expected that additional new data, i.e., observed data such as current weight, health, age, etc. can be captured and recorded. [0019] teaches a current picture of the animal, a prior picture, the owner, EID tag number, animal name, date of birth, gender, brand or tattoo, type, breed class, age, medical history, pedigree, weight, weighing date, size and color. [0020] teaches for example, the birth date, breed and ownership data retrieved from an EID tag may be merged with the weight, health and feed history data keyed into a node system computer to produce a 2D barcode label that records the entirety of this data and is readable by other persons and systems who encounter the 2D barcode label. [0022] teaches a data record collected on steer at farm may be associated/tagged/identified by a location field specifying the location of the farm and [0027] teaches identification number, owner identification number, owner address, breed information, etc. taken from EID tag by EID reader, combined with observed data, such as the weight of the steer, its health condition, veterinary record, feed record, and age (all of this information is interpreted by Examiner as the digital animal records comprising animal information for the plurality of source animals, the animal information comprising identification information, location information, and health information for the plurality of source animals and interpreted by Examiner as meat facts regarding the particular source animal)); generating, according to the animal information, an animal health score for the particular source animal (Kanitz at [0018] teaches observed data such as current weight, health, age, etc. would be of interest to the overall process of tracking and describing the steer in the farm environment. [0020] teaches the birth date, breed and ownership data retrieved from an EID tag may be merged with the weight, health and feed history data keyed into a node system computer to produce a 2D barcode label that records the entirety of this data and [0027] teaches a veterinary record. [0019] teaches a numerical scoring and that this scoring data may include: body conditioning, locomotion, hoof condition, lameness, longevity, udder, mouth, body frame and reproductive condition (interpreted by Examiner as generating, according to the animal information, an animal health score for the particular source animal)); generating, based on the animal health score a machine-readable image file for the particular source animal of the animal-based meat product ([0020] teaches the birth date, breed and ownership data retrieved from an EID tag may be merged with the weight, health and feed history data keyed into a node system computer to produce a 2D barcode label that records the entirety of this data and [0019] teaches that observed data would include any data concerning the present state of the commodity or item being tracked. In the case of a steer, this will include the time and location that the data is entered, a current picture of the animal, a prior picture, the owner, EID tag number, animal name, date of birth, gender, brand or tattoo, type, breed class, age, medical history, pedigree, weight, weighing date, size and color. Besides the foregoing objective data, certain data in the form of expert judgment or scoring may be entered in terms of a numerical score, the recorded data would include printed textural material, barcodes, 2D barcode labels, Data Matrix labels, data recorded in magnetic media, such as CDs, magnetic sticks, strips and discs, EID tags, RFIDs, ROM chips, and any other conventional data recording media (interpreted by Examiner as generating, based on the animal score a machine-readable image file for the particular source animal)); wherein the machine-readable image file, when decoded, makes available meat facts regarding the particular source animal of the animal-based meat product, the meat facts comprising the animal health score and other information regarding the particular source animal ([0018] teaches capability of digital cameras and cell phones to capture images in digital form allows these devices to scan or "read" a digitally encoded label, such as a barcode or 2D barcode. Image data captured by the cell phone can then be sent to the server system 22 for decoding and/or storage in the database if the cell phone or PDA does not have label decoding software. While the foregoing example utilizes remote decoding, in an alternative embodiment, a cell phone and/or PDA could be programmed to provide on-board decoding. [0021] teaches having collected and stored the data in a database, the system can readily generate reports concerning the commodity (interpreted by Examiner as wherein the machine-readable image file, when decoded, makes available meat facts regarding the particular source animal of the animal-based meat product, the meat facts comprising the animal health score and other information regarding the particular source animal)); transmitting the machine-readable image file to a requesting device ([0033] teaches when the commodity has completed all processing, and the data record(s) is/are finalized in the database and in the form of a label on a product, this data can be archived for a specified storage period and accessed for reporting the history of the object, its origin and processing, as required. Reading the label on the finished product (online or offline) allows the user to retrieve and report the final source information and processing history on each individual item and [0035] teaches the tracking of the commodity through its various states and locations during processing are readily obtainable as a written or viewable report presented on the screen of a user's computer);
It would have been obvious for one of the ordinary skill in the art before the effective filling date of the claimed invention to have modified identifying and labeling system of Poliska to incorporate the electronic record keeping, animal score and the machine-readable image file as taught by Kanitz, with the motivation of providing global recordkeeping capabilities for tracking and labeling livestock, produce, wine, food products, manufactured goods and virtually any object or collection of objects as they move from place to place over time in the course of production, transportation, processing, marketing and use. (Kanitz at [0001]).
Poliska and Kanitz do not explicitly disclose receiving, after a sale of the animal-based meat product, purchaser data comprising purchaser-identifying information and a date of purchase; and updating the digital animal records with the purchaser data such that the sale of the animal-based meat product is linked to a particular purchaser in the digital animal records, however Beier discloses:
receiving, after a sale of the animal-based meat product, purchaser data comprising purchaser-identifying information and a date of purchase; and updating the digital animal records with the purchaser data such that the sale of the animal-based meat product is linked to a particular purchaser in the digital animal records (Beier at [0028] teaches a product (interpreted by Examiner as the animal-based meat product of Poliska and Kanitz) passed through distribution channels to retail operations and available for purchase by a consumer. And teaches a serial or lot identifiers (interpreted by Examiner as the machine-readable image file of Poliska and Kanitz) on the product. The retail operations may also produce a retail record (interpreted by Examiner as the digital animal record of Poliska) which is added to the traceability server, the retail record may include consumer purchase data (interpreted by Examiner as a date of purchase) and other data and [0030] teaches the transaction information (interpreted by Examiner as purchaser data comprising purchaser-identifying information) from when a consumer purchases the product could also be included in the retail record (interpreted by Examiner as means to receive purchaser data that comprises purchaser-identifying information and a date of purchase; and updating the digital animal records with the purchaser data so that a sale of the animal-based meat product is linked to a particular purchaser) [0059] teaches a user to purchase sirloin steak and is using the application to inform the purchasing decision. The user has scanned a barcode from a first meat package at a retail location. [0081] teaches the system can also store a history of user purchases. Moreover, [0072] teaches the barcode image is decoded to produce barcode data. The barcode data may be a unique serialized number).
It would have been obvious for one of the ordinary skill in the art before the effective filling date of the claimed invention to have modified the digital animal record of Poliska and Kanitz to incorporate receiving, after a sale of the animal-based meat product, purchaser data and updating the digital animal records with the purchaser data as taught by Beier, with the motivation of improving productivity, efficiency, product safety, and other elements of the supply chain and the products it produces. (Beier at [0023]).
REGARDING CLAIM 2
Poliska, Kanitz and Beier disclose the limitation of claim 1.
Poliska and Beier do not explicitly disclose wherein the machine-readable image file, when decoded, comprises a website address to a website that provides the meat facts about the particular source animal of the animal-based meat product based at least in part on an animal identifier, however Kanitz further discloses:
The non-transitory computer-readable storage medium of Claim 1, wherein the machine-readable image file, when decoded, comprises a website address to a website that provides the meat facts about the particular source animal of the animal-based meat product based at least in part on an animal identifier (Kanitz at [0018] teaches website associated with the server system 22. [0032] teaches building the historical processing record in accordance with an embodiment of the present invention using 2D symbology, each processing environment 14e-14g reads the label, e.g., 14d on the input object, e.g., 12e to that environment, e.g. 14d, updates the label's record with new information, and creates a quantity of labels, e.g., 46e to identify each output object, e.g. 12f for transfer to the next environment 14f. The first record on each label, e.g., 46d may be a standard key data element common to all states 12d-12g and processing environments 14d-14f, corresponding to the URL (Internet web address) for the server 22 and [0038] teaches the identity of the record keeper(s) may be used as a hyperlink to the web page of the record keeper such that if the node system, e.g., is online, double clicking on the link will connect the user to that website.).
The obviousness of combining the teachings of Kanitz within the systems and methods taught by Poliska and Beier are discussed in the rejection of claim 1, and incorporated herein.
REGARDING CLAIM 3
Poliska, Kanitz and Beier disclose the limitation of claim 1.
Poliska and Beier do not explicitly disclose receiving an information request from a user device that has decoded the website address from an optical scan of a package label that includes a physical representation of the machine-readable image file, the information request providing the animal identifier, the animal identifier corresponding to the particular source animal; accessing, according to the animal identifier and from the digital animal records for the plurality of source animals, the health information for the particular source animal; generating, according to the health information for the particular source animal, data for receipt by the user device, the data comprising the meat facts regarding the particular source animal; and transmitting the data to the user device for display, however Kanitz further discloses:
The non-transitory computer-readable storage medium of Claim 2, wherein the program further includes instructions for: receiving an information request from a user device that has decoded the website address from an optical scan of a package label that includes a physical representation of the machine-readable image file, the information request providing the animal identifier, the animal identifier corresponding to the particular source animal; accessing, according to the animal identifier and from the digital animal records for the plurality of source animals, the health information for the particular source animal; generating, according to the health information for the particular source animal, data for receipt by the user device, the data comprising the meat facts regarding the particular source animal; and transmitting the data to the user device for display (Kanitz at [0024] teaches the 2D barcode label may be generated by printing and read by a CCD camera. [0027] teaches EID (electronic identification device) reader for reading EID tag on livestock (commodity graphically illustrated by circle). The data retrieved from the EID reader is received by computer and posted to a network for receipt and storage by server (see FIG. 1). In addition to sharing the data retrieved from the tag, the computer induces a 2D barcode printer to generate a 2D barcode label, which is applied to commodity. [0003] teaches records to provide country of origin information to retailers, including the "born, raised, and slaughtered" information required to make U.S. origin claims for the covered commodities beef, pork, and lamb. To verify products are properly labeled at the retail level, records must be maintained from an animal's birth to retail. [0016] teaches a tracking and labeling system for recording and reporting data about a commodity such as a steer may come into existence in a first environment, a farm where it is born and raised. The steer may be sold and shipped to a meat processing plant at another location where it is butchered and processed into meat products (e.g., sides of beef or other large cuts of meat). The meat products may then be shipped to a retail store, for further processing and packaging into retail packages of meat. At each point in this sequence of events, data concerning the commodity may be noted and recorded by local (node) data capture and processing systems. Attributes of interest, such as age, breed, weight, source, appearance, veterinary record, feed history, etc. may have been previously recorded data, recorded on some media, such as an Electronic Identification Tag (EID) tag, Radio Frequency Identification (RFID), color-coded image, barcode or 2D barcode label (interpreted as the label of Poliska). In the farm environment, a steer would typically have an EID tag fastened to it at birth or soon after. The EID tag would record owner information, birth date, breed, identification number, etc. The data "written" on the EID tag would be an example of recorded data on media. [0018] teaches in addition to the recorded data on media, it would be expected that additional new data, i.e., observed data such as current weight, health, age, etc. can be captured and recorded. [0019] teaches a current picture of the animal, a prior picture, the owner, EID tag number, animal name, date of birth, gender, brand or tattoo, type, breed class, age, medical history, pedigree, weight, weighing date, size and color. [0020] teaches for example, the birth date, breed and ownership data retrieved from an EID tag may be merged with the weight, health and feed history data keyed into a node system computer to produce a 2D barcode label that records the entirety of this data and is readable by other persons and systems who encounter the 2D barcode label. [0022] teaches a data record collected on steer at farm may be associated/tagged/identified by a location field specifying the location of the farm and [0027] teaches identification number, owner identification number, owner address, breed information, etc. taken from EID tag by EID reader, combined with observed data, such as the weight of the steer, its health condition, veterinary record, feed record, and age (interpreted by Examiner as meat facts regarding the particular source animal) [0018] teaches capability of digital cameras and cell phones to capture images in digital form allows these devices to scan or "read" a digitally encoded label, such as a barcode or 2D barcode. Image data captured by the cell phone can then be sent to the server system 22 for decoding and/or storage in the database if the cell phone or PDA does not have label decoding software. While the foregoing example utilizes remote decoding, in an alternative embodiment, a cell phone and/or PDA could be programmed to provide on-board decoding. [0021] teaches having collected and stored the data in a database, the system can readily generate reports concerning the commodity (interpreted by Examiner as wherein the machine-readable image file, when decoded, makes available meat facts regarding the particular source animal of the animal-based meat product). [0033] teaches when the commodity has completed all processing, and the data record(s) is/are finalized in the database and in the form of a label on a product, this data can be archived for a specified storage period and accessed for reporting the history of the object, its origin and processing, as required. Reading the label on the finished product (online or offline) allows the user to retrieve and report the final source information and processing history on each individual item and [0035] teaches the tracking of the commodity through its various states and locations during processing are readily obtainable as a written or viewable report presented on the screen of a user's computer and [0037] teaches a data entry/display screen of a node computer for entering and displaying data pertaining to a commodity by tracking and labeling system of the present invention.).
The obviousness of combining the teachings of Kanitz within the systems and methods taught by Poliska and Beier are discussed in the rejection of claim 1, and incorporated herein.
REGARDING CLAIM 4
Poliska, Kanitz and Beier disclose the limitation of claim 1.
Poliska and Beier do not explicitly disclose wherein the machine-readable image file, when decoded, comprises the meat facts about the particular source animal of the animal-based meat product, however Kanitz further discloses:
The non-transitory computer-readable storage medium of Claim 1, wherein the machine-readable image file, when decoded, comprises the meat facts about the particular source animal of the animal-based meat product (Kanitz at [0018] teaches capability of digital cameras and cell phones to capture images in digital form allows these devices to scan or "read" a digitally encoded label, such as a barcode or 2D barcode. Image data captured by the cell phone can then be sent to the server system 22 for decoding and/or storage in the database if the cell phone or PDA does not have label decoding software. While the foregoing example utilizes remote decoding, in an alternative embodiment, a cell phone and/or PDA could be programmed to provide on-board decoding. [0021] teaches having collected and stored the data in a database, the system can readily generate reports concerning the commodity (interpreted by Examiner as wherein the machine-readable image file, when decoded, comprises the meat facts about the particular source animal of the animal-based meat product)).
The obviousness of combining the teachings of Kanitz within the systems and methods taught by Poliska and Beier are discussed in the rejection of claim 1, and incorporated herein.
REGARDING CLAIM 5
Poliska, Kanitz and Beier disclose the limitation of claim 1.
Poliska and Beier do not explicitly disclose wherein the other information of the meat facts comprise one or more of: information regarding vaccinations of the particular source animal; information regarding antibiotics of the particular source animal; information regarding respiratory health of the particular source animal; information regarding liver health of the particular source animal; or information regarding neurological health of the particular source animal, however Kanitz further discloses:
The non-transitory computer-readable storage medium of Claim 1, wherein the other information of the meat facts comprise one or more of: information regarding vaccinations of the particular source animal; information regarding antibiotics of the particular source animal; information regarding respiratory health of the particular source animal; information regarding liver health of the particular source animal; or information regarding neurological health of the particular source animal (Kanitz at [0027] teaches health condition, veterinary record (interpreted by Examiner as to include information regarding vaccinations).
The obviousness of combining the teachings of Kanitz within the systems and methods taught by Poliska and Beier are discussed in the rejection of claim 1, and incorporated herein.
REGARDING CLAIM 7
Poliska, Kanitz and Beier disclose the limitation of claim 1.
Poliska and Beier do not explicitly disclose wherein the program further includes instructions for: receiving a request to determine location information associated with the particular source animal for animal-based meat product, the request comprising a purchaser identifier for a purchaser of the animal-based meat product; accessing, according to the purchaser identifier and the purchaser-identifying information of the purchaser data, the digital animal record for the particular source animal of the animal-based meat product to determine location information for the particular source animal; and transmitting the location information for the particular source animal, however Kanitz further discloses:
The non-transitory computer-readable storage medium of Claim 1, wherein the program further includes instructions for: receiving a request to determine location information associated with the particular source animal for animal-based meat product, the request comprising a purchaser identifier for a purchaser of the animal-based meat product; accessing, according to the purchaser identifier and the purchaser-identifying information of the purchaser data, the digital animal record for the particular source animal of the animal-based meat product to determine location information for the particular source animal; and transmitting the location information for the particular source animal (Kanitz at [0022] teaches the tracking of a commodity is facilitated by utilizing a data field or fields representing time (month, day, year, hour, minute) and geographic location in terms of latitude, longitude, and elevation. Geographic location may also be specified by conventional addressing information (station, building number, entity name, street address, town, country, zip code). For example, a data record collected on steer 12a at farm 14a may be associated/tagged/identified by a location field specifying the location of the farm 14a and a field specifying the time when the data was entered. By associating data concerning the commodity with the place and time of its recordation, the system can maintain a chronologically and geographically ordered, site-specific record of the history of the commodity (interpreted by Examiner as location information associated with the particular source animal for animal-based meat product) [claim 1] teaches location and time data for each state. [0035] teaches for example, if a person returns a cut of meat to the retail store in which they purchased it, complaining that it is in some manner unacceptable, such that it becomes of interest to determine exactly where the meat originated from, this task can be performed by the tracking and labeling system 10 of the present invention, where all commodities passing though that processing point can be identified and extracted from the database for any specified time period based upon a suitable query and [0004] teaches information about meat purchased and whether it’s been treated with growth hormones or antibiotics (interpreted by Examiner as the request comprising a purchaser identifier for a purchaser of the animal-based meat product)).
The obviousness of combining the teachings of Kanitz within the systems and methods taught by Poliska and Beier are discussed in the rejection of claim 1, and incorporated herein.
REGARDING CLAIM 9
Poliska, Kanitz and Beier disclose the limitation of claim 1.
Poliska further discloses:
The non-transitory computer-readable storage medium of Claim 1, wherein: the animal-based meat product is an animal carcass from which multiple sub-products are to be formed; or the animal-based meat product is a meat sub-product formed from an animal carcass (Poliska at [0007] teaches animal carcass).
REGARDING CLAIM 10
Poliska, Kanitz and Beier disclose the limitation of claim 1.
Poliska further discloses:
The non-transitory computer-readable storage medium of Claim 1, wherein the particular source animal is a cow or a pig (Poliska at [0020] teaches present invention is directed to a pork industry).
REGARDING CLAIM 11
Poliska, Kanitz and Beier disclose the limitation of claim 1.
Poliska and Beier do not explicitly disclose the machine-readable image file that is transmitted to the requesting device is a physical representation of the machine-readable image file that is printable; and the physical representation of the machine-readable image file comprises one or more of a quick resource (QR) code or a barcode, however Kanitz further discloses:
The non-transitory computer-readable storage medium of Claim 1, wherein: the machine-readable image file that is transmitted to the requesting device is a physical representation of the machine-readable image file that is printable; and the physical representation of the machine-readable image file comprises one or more of a quick resource (QR) code or a barcode (Kanitz at [0007] teaches labeling such as barcodes).
The obviousness of combining the teachings of Kanitz within the systems and methods taught by Poliska and Beier are discussed in the rejection of claim 1, and incorporated herein.
REGARDING CLAIMS 12-20
Claims 12-20 are analogous to Claims 1-11 thus Claims 12-20 are similarly analyzed and rejected in a manner consistent with the rejection of Claims 1-11.
REGARDING CLAIM 21
Poliska, Kanitz and Beier disclose the limitation of claim 1.
Poliska and Beier do not explicitly disclose receiving a recall request identifying a contaminated source animal or processing location; accessing the digital animal records to identify animal-based meat products associated with the contaminated source animal or processing location, however Kanitz further discloses:
The non-transitory computer-readable storage medium of Claim 1, wherein the program further includes instructions for: receiving a recall request identifying a contaminated source animal or processing location; accessing the digital animal records to identify animal-based meat products associated with the contaminated source animal or processing location (Kanitz at [0035] teaches for example, if a person returns a cut of meat to the retail store in which they purchased it, complaining that it is in some manner unacceptable (interpreted by Examiner as receiving a recall request identifying a contaminated source animal or processing location), such that it becomes of interest to determine exactly where the meat originated from, this task can be performed by the tracking and labeling system of the present invention. In the first instance, the consumer preferably returns the meat in its original packaging, which would include the label prepared for the packaging by the present invention. The label would be readable by, e.g., a 2D barcode label reader to ascertain the data associated with the package of meat. This data can be read directly into a computer. The entire history of the meat can be retrieved from the database by the server using conventional database techniques. For example, the tracking and labeling system may maintain tables of all data transactions received from all specific geographic locations (corresponding to sites of specific processing functions and/or specific responsible parties in the production chain). These tables can be linked by source and destination fields, such that each record entry signifying a data entry transaction typically associated with a state change for the commodity (some form of processing) will indicate the geographic location and time when the entry is made, the geographic location from which the commodity was received and optionally, the target geographic location to which the commodity is to be sent (interpreted by Examiner as accessing the digital animal records to identify animal-based meat products associated with the contaminated source animal or processing location);
The obviousness of combining the teachings of Kanitz within the systems and methods taught by Poliska and Beier are discussed in the rejection of claim 1, and incorporated herein.
Poliska and Kanitz do not explicitly disclose accessing the purchaser data to identify purchasers who purchased the identified animal- based meat products; and transmitting recall notifications to the identified purchasers, however Beier further discloses:
accessing the purchaser data to identify purchasers who purchased the identified animal- based meat products; and transmitting recall notifications to the identified purchasers (Beier at [0030] teaches sending automatic notifications of recalls to consumers (interpreted by Examiner as transmitting recall notifications to the identified purchasers) and [0037] teaches the history of products scanned or purchased by the user could be stored on the mobile device or server. If a user has previously scanned or purchased what is now a recalled product, the user is notified through the use of a push notification of the recall. For example, the recall notice could be implemented as a popup on the mobile device which identifies the product previously scanned, the time/location the product was scanned, and recall information (interpreted by Examiner as means for accessing the purchaser data to identify purchasers who purchased the identified animal- based meat products)).
The obviousness of combining the teachings of Beier within the systems and methods taught by Poliska and Kanitz are discussed in the rejection of claim 1, and incorporated herein.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Poliska (US 2004/0236191), in view of Kanitz US (2007/0005173), in view of Beier (US 2017/0293882) and in further view of Pham (WO 2024149612 A1).
REGARDING CLAIM 8
Poliska, Kanitz and Beier disclose the limitation of claim 1.
Poliska and Beier do not explicitly disclose, however Kanitz further discloses:
The non-transitory computer-readable storage medium of Claim 1, wherein the program further includes instructions for: the instructions for generating, according to the animal information, an animal health score for the particular source animal include instructions for analyzing according to a plurality of health parameters, the animal information to generate the animal health score for the particular source animal, the plurality of health parameters comprising two or more of vaccination status, antibiotic use, respiratory health, liver health, or neurological health; and the programing further includes instructions for updating the digital animal records with the animal health score, the meat facts comprising the animal health score (Kanitz at [0019] teaches certain data in the form of expert judgment or scoring may be entered in terms of a numerical score or other conventional classifying scheme along with the expert's identification. For a steer 12a, this scoring data may include: body conditioning, locomotion, hoof condition, lameness, longevity, udder, mouth, body frame and reproductive condition. [0027] teaches a veterinary record (interpreted by Examiner to contain vaccination record/status). and [0040] teaches quality scoring data pertaining to livestock (interpreted by Examiner as health score for the particular source animal) [0032] teaches allowing updates.).
The obviousness of combining the teachings of Kanitz within the systems and methods taught by Poliska and Beier are discussed in the rejection of claim 1, and incorporated herein.
Poliska, Beier and Kanitz do not explicitly disclose, however Pham further discloses:
include instructions for analyzing, by an artificial intelligence engine and according to a plurality of health parameters, the animal information to generate the animal health score for the particular source animal (Pham at [0032] and [0033] teaches using artificial intelligence to analyze fetal health and determine a health score).
It would have been prima facie obvious to one of ordinary skill in the art at the time of the invention was made to combine the noted features of Poliska, Beier and Kanitz with teaching of Pham since known work in one field of endeavor may prompt variations in design in either the same field or a different field based on design incentives or other market forces if the variations would have been predictable to one of ordinary skill in the art. One of ordinary skill in the art of healthcare would have found it obvious to update analyzing the animal health data to generate a health score of the primary, secondary and third reference using artificial intelligence technology, as found in the secondary reference, to analyze health data and generate a health score, in order to gain the commonly understood benefits of such adaptation, such as decreased size, increased reliability, simplified operation, and reduced cost. This update would be accomplished with no unpredictable results.
Response to Arguments
Drawing Objections
Regarding the drawing objection(s), the Applicant has replaced Fig. 6A, however, Fig. 6A is still unreadable/unsatisfactory for reproduction. The labels are unreadable.
Rejection under 35 U.S.C. § 101
Regarding the rejection of claims 1-5 and 7-21, the Examiner has considered the Applicant’s arguments, but does not find them persuasive. Applicant argues:
Applicant respectfully maintains that rather identifying the abstract idea to which Applicant's claims as a whole allegedly are directed, the Office Action merely lists virtually all claim features and summarily concludes that those features cover a method of organizing human activity. Applicant notes that "a method of organizing human activity" is not an identification of an alleged abstract idea, but instead is a category into which an alleged abstract idea might fall. Controlling authority requires that "the focus of the §101 inquiry should be on the character of the claimed invention as a whole." Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335 (Fed. Cir. 2016). Here, Applicant respectfully submits that the Office Action does not identify any coherent abstract idea that characterizes Applicant's claims as a whole.
Regarding 1, The Examiner respectfully disagrees. The Examiner follows Office guidelines in listing all claim limitations that state the abstract idea, stripped of all computer components. The abstract idea is clearly identified in bold lettering in the 101 rejection. The abstract idea identified by the Examiner, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, and falls within the “certain methods of organizing human activity” grouping of abstract ideas.
The claims do not simply organize human activity or collect data. They recite a technical solution/infrastructure for tracking and providing food health information and for food safety traceability linking source animal health records, consumer-accessible information, and post- sale purchaser data. See, e.g., U.S. Patent Publication 2023/0172218 ("Applicant's Published Application") at oo17-oo22, 0155-0157. Thus, Applicant respectfully submits that the Office Action has not established that Applicant's claims recite an abstract idea in a manner compliant with controlling authority, and that Applicant's claims are not directed to an abstract idea.
Regarding 2, The Examiner respectfully disagrees. The claims encompass a series of rules or instructions for a person or persons to follow, with or without the aid of a computer, to receive label-generating request, access animal records, generate an animal health score, generate a machine-readable image file, transmit the machine-readable image file, receive purchaser data and update digital animal records. Moreover, there is no technical problem/solution in the claim. The claim aims at receiving label-generating request, accessing animal records, generating an animal health score, generating a machine-readable image file, transmitting the machine-readable image file, receiving purchaser data and updating digital animal records and uses generic computer components to do so. Applicants disclosure at Para. [0160] states “may provide an ability to gather and store data for tracking the source of food products, along with (in the case of meat and potentially farm-raised fish) the medical history of the animal from which the meat is sourced and/or the various facts about the farm, and may allow the source of the food and any associated medical or other conditions that may be problematic to be determined or tracked.” and at Para. [0167] states “may save time by reducing or eliminating hand-written health records through a partial or complete digital solution… may reduce costs by allowing decision makers to use real-time data to make timely, potentially improved management decisions.” None of which are technical problems/solutions.
Even assuming for the sake of argument only that the claims recite an alleged abstract idea, which Applicant does not concede, the claims integrate any such abstract idea into a practical application under Step 2A, Prong 2. See, e.g., 2019 Revised Guidance; see also 2019 Update at Fig. 2 and pp. 10-12. For example, Applicant's claims "reflect an improvement in the functioning of a computer, or an improvement to another technology or technical field," and thereby "integrate[] the judicial exception into a practical application and thus impose[] a meaningful limit on the judicial exception." 2019 Update.
Regarding 3, The Examiner respectfully disagrees. The claims generate labels that allow for accessing meat facts about a particular source animal. This does not improve upon the functioning of a computer nor does it improve upon a technical field. The additional elements of a non-transitory computer-readable storage medium, one or more processor and a storage system do not integrate the abstract idea into a practical application because they are not exclusively defined by the applicant and are recited at a high-level of generality (i.e., a generic computer components. See Specification at para. [0031], [0034], [0037], [0053] and [0055]) such that they amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
For example, Claim 1 relates in part to "generating, based on the animal information of the digital animal record for the particular source animal of the animal-based meat product, a machine-readable image file for the particular source animal of the animal-based meat product." As recited in Claim 1, that "machine-readable image file, when decoded, makes available meat facts regarding the particular source animal of the animal-based meat product." At a minimum, this reflects a technological improvement in labeling technology and the manner in which meat facts are made available to those desiring to access information about animal-based meat products.
Regarding 4, The Examiner respectfully disagrees. The additional element of a machine-readable image file was determined to merely generally links the abstract idea to a particular technological environment or field of use. MPEP 2106.04(d)(I) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide a practical application. This has been re-evaluated under the “significantly more” analysis and has also been found insufficient to provide significantly more. MPEP 2106.05(A) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide significantly more. Moreover, the prior art of record indicates that machine-readable image file is well-understood, routine, conventional activity (see Poliska at [0002], [0007] and [0027] and Kanitz at ([0016], [0024] and [0027]). Well-understood, routine and conventional activity cannot provide an inventive concept (“significantly more”). Therefore when considering the additional element alone, and in combination, there is no inventive concept in the claim, and the additional element does not integrate the abstract idea into a practical application. Moreover, well-understood, routine, conventional activity cannot provide improvement.
Claim 1 thus integrates any alleged exception into a practical application by: (i) improving computer functionality through computational health score generation; (2) providing a specific technical solution to the food safety traceability problem; and (3) creating a technical infrastructure linking health records, consumer information, and purchaser data for public health protection.
Regarding 5, The Examiner respectfully disagrees. None of the listed above improve the functioning of a computer. Health score generation, food safety traceability and linking records at best provide improvements in administrative/health fields.
As another example, Claim 12 recites features of "decoding, by a user device, data coded in an optical scan of a physical representation of a machine-readable image file located on a label for an animal-based meat product;" "accessing, by the user device according to the data coded in the optical scan, meat facts about a particular source animal corresponding to the animal-based meat product;" and "displaying, by the user device, the meat facts about the particular source animal associated with the animal-based meat product." Again, at a minimum, these features reflect a technological improvement the manner in which meat facts are accessed and made available to those desiring to access information about animal-based meat products. As another example, Claim 19 recites features of "accessing, from digital animal records for a plurality of animals, a digital animal record corresponding to the source animal associated with the animal-based meat product;" "generating, based on the digital animal record corresponding to the source animal associated with the animal-based meat product, a first code for identifying the source animal;" "updating the digital animal record corresponding to the source animal associated with the animal-based meat product with the first code for identifying the source animal;" and "transmitting the first code to a receiving device." At a minimum, these features reflect a technological improvement the manner in which a code for identifying a source animal for an animal-based meat product is generated and stored in a digital animal record for the source animal.
Regarding 6, The Examiner respectfully disagrees. Claims 12 and 19 do not provide technical improvements nor improvements to a computer for the same reasons as claim 1.
Rejection under 35 U.S.C. § 103
Regarding the rejection of claims 1-5 and 7-21, the Examiner has considered the Applicant’s arguments, but does not find them persuasive. Applicant argues:
Whether or not Kanitz discloses these "receiving" features, which Applicant does not address, it is unclear how Poliska possibly could disclose, teach, or suggest "accessing, in response to receiving the label-generating request, digital animal records for a plurality of source animals to identify a digital animal record for the particular source animal corresponding to the animal-based meat product .. ." when Poliska does not even disclose, teach, or suggest "receiving a label-generating request for generating a machine-readable image file for an animal-based meat product," as recited in Claim 1. How could Poliska possibly disclose taking action X in response to action Y (as alleged), when Poliska does not even disclose action Y (as acknowledged).
Regarding 1, The Examiner respectfully submits that Poliska teaches a machine-readable image file for an animal-based meat product (see para. [0002] and [0007]). Kanitz is relied upon to teach the label-generating request to generate that same image file of Poliska. As a result, the accessing is only possible once the label is generated, which is accomplished by Kanitza. And the Examiner clarifies that labeling in Poliska is the same as that in Kanitz.
As another example, even setting aside this deficiency, the cited portions of the proposed Poliska-Kanitz do not disclose, teach, or suggest "generating, according to the animal information, an animal health score for the particular source animal," as recited in amended Claim 1. While Kanitz discusses "scoring data" at paragraphs [0019] and [0040], this scoring pertains to expert livestock evaluation metrics such as "body conditioning, locomotion, hoof condition, lameness, longevity, udder, mouth, body frame and reproductive condition." These are livestock quality/performance scores for ranchers and breeders, not health scores derived from health information (vaccinations, diseases, treatments) for assessing meat product safety or quality. The Office Action does not appear to cite Poliska as allegedly disclosing these features. Thus, Applicant respectfully submits that the cited portions of the proposed Poliska- Kanitz combination do not disclose, teach, or suggest "generating an animal health score based on animal health information," as recited in amended Claim 1.
Regarding 2, The Examiner respectfully disagrees. Kanitz at [0018] teaches observed data such as current weight, health, age, etc. would be of interest to the overall process of tracking and describing the steer in the farm environment. [0020] teaches the birth date, breed and ownership data retrieved from an EID tag may be merged with the weight, health and feed history data keyed into a node system computer to produce a 2D barcode label that records the entirety of this data and [0027] teaches using veterinary record as well (which is interpreted by Examiner to include health information (vaccinations, diseases, treatments) by definition of a veterinary record). Moreover, [0019] teaches observed data would include any data concerning the present state of the commodity or item being tracked. In the case of a steer, this will include the time and location that the data is entered, a current picture of the animal, a prior picture, the owner, EID tag number, animal name, date of birth, gender, brand or tattoo, type, breed class, age, medical history, pedigree, weight, weighing date, size and color. Besides the foregoing objective data, certain data in the form of expert judgment or scoring may be entered in terms of a numerical score or other conventional classifying scheme along with the expert's identification. For a steer, this scoring data may include: body conditioning, locomotion, hoof condition, lameness, longevity, udder, mouth, body frame and reproductive condition. So it’s a combination of data that is analyzed and use to determine the health score of an animal.
Given the broadest reasonable interpretation the cited references in combination teach the claimed features.
As another example, the cited portions do not disclose, teach, or suggest "receiving, after a sale of the animal-based meat product, purchaser data comprising purchaser-identifying information and a date of purchase" and "updating the digital animal records with the purchaser data such that the sale of the animal-based meat product is linked to a particular purchaser in the digital animal records," as recited in amended Claim 1. Poliska's system appears to end at packaging. See, e.g., Poliska at [oo31] (tags removed before packaging; labels applied to packages). Poliska does not appear to disclose receiving purchaser data or linking sales to purchasers in animal records. At best, Kanitz mentions a consumer returning defective meat at paragraph [0035], but does not appear to disclose, teach, or suggest receiving purchaser data after sale and updating animal records to link the sale to a particular purchaser.
Regarding 3, The Examiner respectfully submits that a new reference Beier, to teach the newly amended features stated above. Please refer to the new rejection under 35 U.S.C. § 103.
Conclusion
The prior art made of record though not relied upon in the present basis of rejection are noted in the attached PTO 892 and include:
Skocic (US 2012/0124387) discloses animal data management. Gibbs (US 2017/0330194) discloses pet feeding system.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to LIZA TONY KANAAN whose telephone number is (571)272-4664. The Examiner can normally be reached on Mon-Thu 9:00am-6:00pm ET.
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If attempts to reach the Examiner by telephone are unsuccessful, the Examiner ’s supervisor, Robert Morgan can be reached on 571-272-6773. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/LIZA TONY KANAAN/Examiner , Art Unit 3683
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