Dairy Farming, Food Traceability, Distributed Ledger Technology (Blockchain), and Multilayered Physical-Digital Product Security System and Method

Abstract

The invention includes: individual animal-based milking data capture and individual animal identification profile module (24); automatic pipe routing mechanism and valves according to milk quality with closed pipelines isolated from operator access (15, 16, 17); spectroscopic milk molecular analyzer interface (40), machine learning biochemical fingerprint module (55), wearable animal welfare monitoring module (22) and animal-specific autochthonous starter culture dosing unit and pump (160-162); individual holding tank monitoring module (125), operator authentication (127), production boiler process records, mass balance control module (140), autonomous sampling (165) and molecular analyzer interface and verification module (170, 171); extended veterinary module with multi-drug breakthrough management (19); milk-cheese-whey biological chain of identity modules (86, 99, 199); central scanning server with passive sensor configuration (193) and synchronized time source module (194);The dual-layer physical security element (90), sequential read session manager (105), product lifecycle status manager (95) and multi-lab DAT module (84) relate to an integrated system and method that includes SaaS licensing features as a vendor-independent platform.

Description

1 Specifications Dairy Farming, Food Traceability, Distributed Ledger Technology (Blockchain), and Multilayered Physical-Digital Product Security System and Method Technical Area The invention has implications for dairy farming, food traceability, distributed ledger technology (blockchain), and many more. It relates to layered physical-digital product safety areas. The invention specifically focuses on collecting milking data on an individual dairy animal basis using machine learning. with milk quality estimation and automated pipe routing, biochemical analysis and machinery. blockchain systems integrated with learning-based fraud anomaly detection It relates to the system and methods for integration. 10 The invention also provides individual animal identification of geographically specific autochthonous starter cultures. Based on automatic dosing to the milking line; in-production boiler process. Simultaneous recording of parameters (pH, temperature, stirring speed); final Automated sampling from the product; starter culture, GMO markers, feed in a single reaction. The source is plant DNA and animal breed genetics, detected through multiplex PCR analysis and 15 qPCR density validation; and environmental parameters of the maturation process. Continuous monitoring to ensure seamless, multi-parameter and autonomous transmission from milking to the consumer. It encompasses an integrated system and method that provides a verification chain. The invention also involves the biological treatment of milk obtained from milking with a starter culture assigned to the animal. labeled as such and 20% of the final product (cheese, whey and derivatives) Milk-cheese-whey, which allows this signal to be detected again through molecular analysis. water biological chain authentication mechanism; third-party laboratory External Analysis Descriptor (DAT) and results reconciliation mechanism for integration; Software service model without having the system's own milking or analysis hardware. (SaaS) allows for licensing to third parties, making it vendor-independent. orchestration architecture; and the consumer validation lifecycle of the final product. Product lifecycle status manager managing statuses under "active / scanned / consumed". It includes the mechanism. State of the Art 2 Currently, with existing technology, milking data of a single animal can be obtained in real-time during milking. the pipe routing decision based on milk quality, the milk biochemistry for that milking, and the final irrevocably associating the physical integrity of the product with the consumer's very There is no integrated system that offers layered verification capabilities. In the previous technique, several independent patents were established in the fields of dairy farming and food traceability. Applications numbered CN107944892A, "A blockchain technology The patent, titled "Blockchain-based milk source monitoring system," involves milking data being transferred to a blockchain. by recording it and creating a transparent and immutable traceability chain. It is geared towards; however, it does not differentiate between batches on an individual animal basis, herd milk. They are combined and processed, and a biochemical fingerprint from the moment of milking is obtained. 10 They are not being caught. Patent number US20050126498A1, titled "Automatic Milk Separation," allows for the separation of individual milk cartons. Automatically detects and separates milk with mastitis by performing cell counts on an animal-by-animal basis. It describes a valve system; however, it is integrated with blockchain or distributed ledger. It is not, it does not produce an immutable record of biochemical data and the final product is 15 It does not include a validation layer. Patent number WO2020067880A1, titled "Milking System with Detection System" Meanwhile, milk samples taken during milking are analyzed using reactive pads and a camera. a company that performs biochemical analysis and controls the milking process based on the analysis results. It is related to robotic milking systems; however, the physical-digital dual-layer product safety element 20 It does not include a consumer-side verification mechanism and geographical anomaly detection. It does not contain. Commercial systems are available that enable in-line starter culture dosing into the milk stream, The most common examples of these are produced by Tetra Pak and Novonesis (formerly Chr. Hansen). It is an improved AISY (Automatic In-line Starter Culture) system. The AISY system has a high 25 dilution of the concentrated starter culture with cold water in a buffer tank and milk in-line into the flow or automatically into fermentation / cheese vats It is based on the principle of pumping. However, these systems require a single culture for collective milk flow at the herd level. It is designed to implement the combination of; (i) individual animal identification and 30 (ii) RFID does not include a central assignment mechanism among culture combinations. (iii) not making animal-specific culture combination selection, dosage amount 3 (iv) not adjusting proportionally to individual milking volume and (iv) distributing the dosing event The ledger is not processed cryptographically. The invention is remarkable because it solves these shortcomings under a single integrated architecture. It differs from other systems. In the current state of the art, there are 5 various blockchain-based food traceability systems. Common technical shortcomings are listed below: ● Data is manually entered into the system by supply chain actors; There is no automatic verification mechanism. ● Traceability begins at the earliest dairy / processing stage; starting from the moment of milking. Individual biochemical data is not being captured. 10 ● No batch (lot) separation is done on an individual animal basis. ● Real-time connection between robotic milking systems and laboratory analysis equipment. Time-based blockchain integration has not been established. ● Conformity assessment according to the target product type and related automated milk processing. No guidance mechanism is available. 15 ● The link between the physical product and the digital record is established solely via a single-factor QR code. is provided. ● Geographic anomaly detection and active protection against fraudulent verification attempts. It is not available. ● Milk quality assessment and fraud detection are carried out solely according to rule 20, which is based on a fixed threshold. They rely on their engines; learning from past data patterns, animal-specific A machine that creates a baseline and adapts to evolving fraud methods. learning-based prediction and anomaly detection mechanisms integrated Not offered. ● Current two-factor authentication systems require both NFC and QR code to be used simultaneously with a physical device. This requires it to be read as such; however, the NFC antenna of smartphones requires the device to be read as such. on the back, since the camera is located on the front, this allows for simultaneous reading. It is not physically feasible. ● Existing traceability systems fall under the EU CSRD and CBAM regulations. mandatory sustainability data (carbon footprint, water consumption, energy 30 4 usage, methane emissions) are automatically transferred to the blockchain on a batch basis. It does not include an integrated infrastructure capable of recording data. ● Current systems detect excretion in animals treated with antibiotics or hormones. integrating withdrawal period data with veterinary record systems It cannot evaluate in this way and perform automatic milk redirection. 5 ● Current systems focus only on cow-based milk production; sheep, goat, General principles applicable to buffalo and other dairy animal species, regardless of species. It does not offer architecture. ● Current systems suffer data loss in the event of internet outages; farm By maintaining a local cache at the level of 10, the blockchain receives data when the connection is re-established. Automatic edge computing infrastructure that handles writing is not offered. ● Current systems determine the animal identity of the starter culture dosed into the milking line. its basis is its use as a unique biological marker and from the final product The milk-cheese identity chain was mathematically identified by molecular analysis. It does not provide an infrastructure that would allow this to be proven. 15 ● Current systems extract whey and other derivative products from the main production chain. Treating them in isolation; multiple milking sessions obtained from a single milking session common source traceability of the final product (cheese + whey-derivative beverage, etc.) It does not allow it to be monitored underneath. ● Current systems allow 20% of samples to be sent to third-party laboratories. the results are cryptographically automated with the original milking session ID. the matching and the result cannot be changed as a single blockchain block. It does not provide an interface that enables processing in this way. ● Current systems are dependent on milking equipment and laboratory infrastructure. without, third-party farm and processing facilities proprietary core 25 traceability architecture by licensing it through a software as a service (SaaS) model. It does not offer a vendor-independent orchestration platform that can be used. ● Current systems involve purchasing the product in-store or by the consumer before the purchase. the scenario of being able to be read multiple times (browse) in reality Product life cycle stage 30 that can distinguish the act of consumption. The manager does not offer it; the product's token is consumed upon the first successful verification. This makes pre-purchase shelf verification impossible. ● Current systems record the animal's date of birth, pedigree, name, behavior, and welfare. Enriched credentials, such as background information, are integrated into an identity profile module. It does not link it to consumer verification. ● Current systems use wearable sensors that continuously monitor the animal. Welfare data obtained (activity, rumination, body temperature, estrus) during milking session 5 It lacks a connection to its identity; this situation is in line with EU animal welfare regulations. This prevents verifiable welfare reporting within the scope of the invention. Furthermore, the invention... It has been determined that the following shortcomings in the current technology have also been solved in an integrated manner. has been done: ● In current systems, the starter culture, dosed in-line to the milking line, is individually measured in 10 units. It is not assigned as a unique combination based on animal identity; all A single culture is applied to the herd or the entire tank. This involves injecting it into the raw milk. This prevents the cultured animal from functioning as a digital signature and milk- It is impossible to provide a biologically based mathematical proof of the cheese chain of identity. It makes it possible. 15 ● In existing systems, the internal process parameters of the cheese production vat (pH curve, (temperature curve, mixing speed, fermentation timestamp) timestamped It is not being cryptographically recorded; therefore, the milk leaves the tank and turns into cheese. in the approximately three to six hours of production process it goes through until it comes out as a finished product It is not possible to determine whether there was any external interference. 20 ● In current systems, the mass balance of the cheese produced (the ratio of the volume of raw milk to the volume of raw milk) is important. (Consistency between the mass of the final cheese and the theoretical yield limit) automatic It is not being monitored; this situation results in milk being diluted with other milk or filler materials. Systematic protection against fraud in the form of increased productivity. It does not provide. 25 ● In current systems, a sample taken from the final product after cheese production is a single sample. starter culture identity in the reaction, genetically modified organism (GMO) markers, feed source plant DNA signature and animal breed genetic markers with multiplex polymerase chain reaction (PCR) in which simultaneous screening can be performed not being evaluated; quantitative PCR (qPCR) signature density (Ct value) measurement 30 By performing this process, dilution or mixing fraud is not detected. ● In existing systems, samples are taken from the holding tank, the production boiler, and the final product. The acquisition largely depends on manual operator intervention; this 6 The situation involves both the risk of human error and operator-based fraud vulnerabilities. is giving birth. ● In existing systems, environmental parameters during the maturation process (temperature, humidity, carbon dioxide), maturation chamber entry and exit records and product chamber location tracking within, milking and production phases with blockchain chain 5 not continuously recorded in an integrated manner; in long-term ripening cheeses (for example, Kashar or Cheddar type cheeses that mature for 6 to 24 months) during this period Protection against attempts to alter or relocate the product. It is not provided. ● In existing systems, in-situ cleaning of holding tanks (Clean-In-Place, 10 CIP (Certified Imaging) cycles are records linked to an animal-specific identification chain. It is not being processed on the blockchain; this situation crosses between successive milkings. This prevents verifiable monitoring of the risk of contamination. ● In current systems, the operator identity grants the authority to initiate the production process. its verification is linked, processed as an operator signature on the blockchain, and 15 There is no mechanism to monitor operator changes. The invention also integrates the following additional shortcomings in the existing art: It shows that it has been resolved: ● In current systems, veterinary record database integration is only possible with a single system. The investigation is limited to the drug's elimination time; 20 simultaneously in the same animal The elimination periods of multiple administered drugs are calculated independently and maximized. Determining the effective breakthrough period based on a long-term perspective, with a veterinary electronic signature. Treatment record, vaccination schedule integration, and quarantine status management all in one place. It is not offered under an integrated infrastructure. ● In current systems, the difference between the pairs of tanks and boilers assigned to individual animals is 25 milk transfer, open pipelines where the operator can physically intervene. This is done through; the milk is not being directed into the wrong cauldron or otherwise. The fact that it is mixed with animal milk does not structurally prevent adulteration. ● In existing systems, an automatically dosed starter culture system is used in the milking line. 30 in an open enclosure physically accessible to the operator is being positioned; culture prescription, dosage amount or injection 7 Manually changing the timing is structurally It is not blocked. ● In current systems, each sensor or data source is independently linked to the blockchain. They can have the authority to write; any sensor physically Damage or manipulation of the entire traceability chain would compromise its integrity. this poses a threat; the sensors are only in the position of data publisher. its operation and all resources of a single central scanning and logging server. an architecture that consolidates and writes a single ledger stream to the blockchain Not offered. ● In current systems, timestamps from different components are different. These can come from various sources (local time, network time, vendor time); among them Deviations at the millisecond level can be found; all system components are integrated. from a central synchronized time source (GPS-disciplined oscillator or (NTPv4 server with RFC 5905 standard) chronologically by time taken It is not possible to provide a verifiable blockchain ledger stream. 15 ● In current systems, samples taken from a single milking batch are processed multiple times. simultaneous or sequential submission to an independent third-party laboratory In this case, a separate external analysis identifier should be assigned to each sample, and this identifiers under the same milking session ID in the DAT pool 20 by consolidating them within its structure and adding them to the blockchain as a single traceability block. No processing mechanism is provided. Purpose of the Invention The invention aims to eliminate the disadvantages inherent in the prior art. One purpose is automatic valve decision-making based on instantaneous sensor data during milking, and this The decision is written to the blockchain using SOK (State Order). 25 Another purpose of the invention is to enable milking, orientation decisions, with the SOK (milking session ID). a centralized system that combines lab analysis and blockchain recording into a single immutable chain. It is the presentation of a descriptive text. Another objective of the invention is to make the double-layered physical security element machine-readable. Separation of the verification element and the contactless electronic micro-verification element 30 8 structurally in a way that permanently disables the element in question of the initiative It is the combination. Another aim of the invention is machine learning trained on historical milking data. With its threshold-based quality estimation module, it offers higher performance compared to classic threshold-based rule engines. The goal is to make a decision regarding the suitability of cheese production with accuracy. 5 Another goal of the invention is to create a machine that learns the pattern of consumer verification attempts. Learning-based behavioral anomaly detection module for new fraud methods It is about providing adaptive protection. Another goal of the invention is to create a machine that learns a biochemical baseline specific to each animal. With the learning-based biochemical fingerprint verification module, physical tag 10 biochemical precursor to the milk mixture or product substitution layer It is the detection at the level. Another aim of the invention is to integrate a contactless electronic micro-verification element with the machine. sequential reading of the readable verification element in a physically feasible manner + operated with a single authentication session (session token) model; a single session 15 inside, first of all, the touchless electronic micro-verification element, then machine-readable verification element or vice versa reading is mandatory. verification becomes invalid if the session duration is exceeded. It is counting. Another aim of the invention is to make the system suitable for animals of all species, including cows, sheep, goats, and buffaloes. to camels and other milk-producing mammals; regardless of breed (Holstein, Jersey, (Simental, Awassi, Ivesi, Saanen, etc.) is applicable. Another purpose of the invention is to comply with the EU CSRD / CBAM regulations. Sustainability factors such as carbon footprint, water consumption, energy use, and methane emissions. It is the automatic recording of data to the blockchain on a batch basis. 25 Another aim of the invention is to analyze the excretion of bacteria in animals treated with antibiotics or hormones. during this time the milk is automatically directed to the general pool and this situation This is the process of recording it in the blockchain. Another purpose of the invention is to collect all data generated by the system (milking data, quality data, etc.). (decisions, blockchain hashes, verification logs) in case of future disputes 30 9 in a manner that can be used as evidence in forensic expert examinations, as required by legislation It is the backup storage of data over a period of time. Another purpose of the invention is to provide data even when the internet connection is interrupted. to prevent data loss; data is stored locally with farm-level edge computing infrastructure. Caching in cryptographically signed form and 5 when the connection is re-established It is the automatic synchronization with the blockchain network. Another aim of the invention is to enable the system to comply with ICAR (International Committee for Animals) regulations. (Recording) and IDF (International Dairy Federation) international standards; also APIs for robotic milking systems from various manufacturers such as Lely, DeLaval, GEA, and BouMatic. It provides cross-interoperability at the level of 10. Another aim of the invention is to isolate microflora from autochthonous microflora specific to the production location, Included in the EFSA QPS (Qualified Presumption of Safety) list and manufactured by TC Türk Gıda. Lactic acid permitted under Article 6 / r of the Codex Cheese Regulation (No: 2015 / 6). Regionally specific starter cultures formed from Bacteria (LAB) strains. combinations; 15 unique to each milking animal by the central assignment module. and individualized in proportion to the instantaneous milk volume measured during milking. It is the automatic dosing of milk into the milk flow. Another aim of the invention is to regulate the process parameters (pH) inside the cheese production vat. (change curve, heat treatment temperature curve, mixing speed, fermentation time stamp) Measured via real-time sensors and at predetermined intervals of 20 (e.g., every 60 seconds) a cryptographic hash is generated and processed into the distributed ledger; furthermore, this the curve's tolerance band predefined by the biochemical profile of the raw material milk It is the autonomous monitoring of whether it is compatible or not. Another purpose of the invention is to regulate the volume of raw milk in cheese production and the volume of the final cheese. The theoretical upper limit of efficiency for mass balance between masses (e.g., 25) Automatic consistency of Jersey cow milk (approximately 12-14% cheese yield) This should be monitored; if this limit is exceeded, the milk should be replaced with other milk or filler. The goal is to detect fraudulent activities carried out by inflating the price with artificially inflated substances. Another purpose of the invention is to automatically extract the final product at the output of the cheese production line. Multiplex polymerase chain reaction (PCR) or equivalent analysis of the sample taken is performed. 30 with timed multi-target molecular screening method; (i) animal-specific assigned starter (ii) the identity of the culture combination, genetically modified organism (GMO) markers (e.g., CaMV 35S promoter, Agrobacterium tumefaciens NOS terminator, MON810, (Roundup Ready soybean), (iii) feed source plant DNA signature (e.g., corn, soybean, pasture (iv) simultaneous screening of animal breed genetic markers; in addition, quantitative Dilution or mixing can be determined by measuring the signature density (Ct value) using PCR (qPCR). The detection of forgery. 5 Another aim of the invention is to eliminate human intervention in the cheese production and verification process. from the holding tank, production boiler and final product to minimize Automated sampling, conditioning, and autonomous transfer to analysis instruments. This involves integrating a robotic sample collection station into the system. The invention applies to animals of all types and breeds, including cows (Bos taurus), sheep (Ovis aries), and goats. (Capra aegagrus hircus), buffalo (Bubalus bubalis), camel (Camelus) and other lactating Milk obtained from domesticated mammals; cheese, butter, cream, yogurt, kefir, for ayran, lor, ice cream, milk powder and all derivative products made from milk raw materials It provides traceability and verification infrastructure. System; ICAR (International Committee for Animal Recording) and IDF (International 15 It operates in compliance with international standards (Dairy Federation); Lely, DeLaval, GEA, Programming applications with BouMatic and similar different manufacturer robotic milking systems. It provides cross-interoperability through its interfaces (APIs). The invention is realized through the system and method that is the subject of the invention; Primary application: Produced from the milk of a single animal (cow, sheep, goat, buffalo, etc.), 20 physical-digital dual security, matched with the animal's identity and biochemical profile. high value-added dairy products (cheese, butter, yogurt, kefir, protected by a protective layer) cream, ice cream, etc.) and whey derivative products (whey protein concentrate, Production of functional beverages, distilled alcoholic beverages and equivalent lines) and marketing, 25 Secondary application: The system's standardized application programming interface (API) third-party farm, architecture and vendor-independent orchestration platform, Software as a Service (SaaS) model for dairies, processing plants and laboratories It is licensing. The invention also reduces the classic breakthrough time of 30 for the veterinary record database integration module. Beyond the inquiry, multidrug simultaneous breakthrough calculation, veterinary electronics Signature requirement, treatment history recording, vaccination schedule integration, and quarantine. 11 expansion to include situation management; individual animal tank-boiler pairs milk transfer between them via closed, sealed pipelines isolated from operator access. to be carried out via; all sensors and data sources passive broadcaster (publisher) works in a centralized scanning and recording server for the data. consolidation by; all timestamps synchronized into a single central 5 the provision of time by the source; and the number of milkings coming from a single batch sending multiple samples to multiple independent third-party laboratories In this case, the DAT pool encompasses the consolidation mechanism. Another objective of the invention is the milk analysis device, final product spectroscopic analysis module, mass balance and molecular analysis instrument outputs in analytical matching module 10 a holistic assessment; final if all verifications are successful. Permission is granted to apply a double-layered physical security feature to product packaging; Otherwise, the labeling line will be autonomously stopped and the party will be labeled as a "non-compliant party". It is recorded on the blockchain. Another objective of the invention is to preserve the milk of an individual animal at +4°C for approximately 24 hours. the environmental parameters of the holding tank in which it is stored (temperature, lid opening log, (duration) continuous monitoring; in case of temperature deviation or unauthorized lid opening automatic anomaly recording is created and the tank is activated when the daily milking process is complete. It means putting it into "ready for production" status. Another objective of the invention is to enable the production process to be controlled by the operator (cheese maker) in 20... initiation through a badge-based authentication module Verification; operator signature and timestamp of successful authentication. this is processed on the blockchain, thus ensuring that who produced it, when, and with what information is recorded. It is the immutable recording of the fact that the authorization was used to initiate the process. Another aim of the invention is to modify the process steps outside the cheese production vat (the curd's 25 (removal from the cauldron, molding, pressing, brining application) multi-camera the system continuously records the data; the image hashes are processed into the blockchain, and AI-based process anomaly detection algorithms automatically identify deviations from the process. It is the identification of. Another aim of the invention is to regulate the process of cheese ripening in the ripening chamber (temperature, humidity, 30 (carbon dioxide level, room entry-exit logs, product location within the room) continuously monitoring; especially in cheeses that mature over a long period, the product during the maturation process. 12 providing protection against attempts at modification; and maturing when necessary. During the process, molecular analysis surveys are conducted using random sampling to determine the identity chain. It is the verification of its continuity. Another purpose of the invention is to replace waiting tanks between successive milkings. Clean-in-place (CIP) cycles; conductivity, temperature and 5 for each cycle. Measurement of time parameters; transfer of measured parameters to the animal chain of identification. By connecting and processing on the blockchain; and thus reducing the risk of cross-contamination. It is the verifiable monitoring of data. Another purpose of the invention is to support devices such as FOSS MilkoScan, FOSS FoodScan, Lactoscope, and similar devices. Roche LightCycler, BioRad CFX, 10 are cross-functional biochemical analysis devices. Applied Biosystems QuantStudio and similar cross-functional multiplex PCR methods. The goal is to ensure cross-operability between devices and the system at the API level. Another aim of the invention is to inject animal-specific substances into the milk stream during the milking process. The starter culture combination was determined from the final cheese by molecular analysis of the milk. Mathematical verification of the cheese biological chain of identity; the same verification 15 whey protein is extracted from whey by stretching it to produce whey derivatives (whey protein). identity chain continuity for concentrates, functional beverages, distilled alcoholic beverages, etc. is to ensure. Another aim of the invention is to create biological derivative products in which DNA integrity is preserved. detection, derivative products in which DNA integrity is lost (e.g., vodka 20 as a result of distillation) For (or gin), the equations involved are mass balance, cryptographic chain of custody, and segregation. hybrid form of operational identity chain continuity based on integrity is to ensure. Another purpose of the invention is to ensure that samples sent to third-party laboratories are original. A unique external analysis cryptographically linked to the milking session ID 25 marking under the identifier (DAT); third-party laboratory analysis result Automatic matching with the original SOK via DAT; and a single matching result. It is the process of processing a blockchain block in an immutable manner. Another aim of the invention is to provide a system equipped with milking, analysis, and laboratory equipment. without, the core traceability architecture (SOK assignment engine, third-party 30 adapter layer, DAT module, blockchain record module, dual-layer physical security 13 element) software as a service model (SaaS) with third-party farms, dairies, processing plants and It is the provision of the product to laboratories in a licensed form. Another objective of the invention is to make the product's consumer validation lifecycle "active". Managing the product under separate statuses: "scanned" and "consumed"; product purchase 5 times prior for verification purposes, either in the store or by the consumer. The ability to browse is provided without consuming the token; if consumed, it will be removed. mechanical failure signal of transition, geo-temporal anomaly, point of sale record or This is done through triggering events such as consumer statements. Another aim of the invention is to use wearable sensors that continuously monitor the animal. Activity, rumination, body temperature, estrus and behavioral data obtained from milking session 10 Encryption on the blockchain by linking with its Identity (SOK); EU animal welfare regulations. This includes providing verifiable welfare reporting opportunities. Another aim of the invention is to obtain demographic, physiological, medical and Storing identifying data under an integrated identity profile module; the profile of the consumer The animal's identity story can be presented in summary form during verification and the product's 15 It forms the basis of its premium positioning. Another objective of the invention is to create an individual holding tank specific to each individual dairy cow. and allocation of individual production boilers; individual holding tanks, individual production establishing a one-to-one identity match between the cauldron and the animal identifier and In applications involving multiple animals, the system provides 20 independent and parallel signals for each animal. It is scalable to include an individual standby-production line. Another purpose of the invention is to collect data continuously 24 / 7 by an environmental sensor network. the barn's indoor and outdoor meteorological parameters (temperature, humidity, pressure, CO2, light, wind, rainfall) values ​​measured during the milking session in relation to SOK in time Matching and processing the batch-specific environmental context fingerprint onto the blockchain; 25 This fingerprint is part of the product story in consumer authentication. It is possible to present it. Another objective of the invention is to integrate the veterinary records database module with the same giving the animal more than one veterinary drug at the same time (antibiotics, antiparasitics, In cases where anti-inflammatory drugs, hormones, etc. are administered, the excretion of each drug is 30%. independent calculation of the duration and the longest one as the effective breakthrough period. The list includes the name of the drug, the dosage, and the date of administration for each treatment given to the animal. 14 application route and verification of the veterinarian's identity (electronic) who administered the treatment (signature, digital certificate or Turkish Veterinary Medical Association registration number) registration taking precautions; changes to vaccination schedule and quarantine status before treatment. This involves processing the data into the blockchain as reference data. Another aim of the invention is to provide individual waiting tanks for each animal, ensuring individual 5-in-1 living spaces. The transfer of milk between production tanks; physically by the operator or a third party. a pipeline that is closed, sealed and leakproof in such a way that it cannot be tampered with This is done through; individual animal lines being separated from the lines of other animals physically separated and with electronic seal sensors at line access points By equipping it, any unauthorized access attempt is recorded as an anomaly on the blockchain. 10 Another objective of the invention is to enable the starter culture dosing unit to be used in animal-culture... combination assignment module and volume-proportional precision dosing pump operator in a sealed, hygienic, closed container that is physically inaccessible to them positioning; granting the operator only the authority to initiate processes and culture The absence of the possibility of manual intervention in the prescription or dosage parameters. 15 Another aim of the invention is to bring all sensors and data sources directly to the blockchain. working solely as a data publisher without authorization; The system includes a single central scanning and logging server; this server handles all It extracts data by querying sources in a predefined order and frequency. consolidating under session ID (SOK) and transferring 20 records to the blockchain as a single log stream. It is the process. Another purpose of the invention is to reduce the time used by all system components. their single central synchronized time source — at the Stratum 1 level GPS-disciplined oscillator (GPSDO), atomic reference clock or RFC 5905 standard NTPv4 server — provided by and with ±10 millisecond accuracy 25 It is about synchronization. Another aim of the invention is to analyze multiple samples taken from a single milking batch. simultaneously or sequentially to multiple independent third-party laboratories If submitted, a separate External Analysis Identifier (DAT) for each sample. assignment; the DATs in question are to be placed under the same SOK within a DAT pool structure 30 consolidation within a multi-source analysis of all laboratory results. It is recorded on the blockchain as a consolidation record. Explanation of the Figures Figure 1 shows the layers and elements of the system that is the subject of the invention. Figure 2 shows a view of the elements of the system that is the subject of the invention. Figure 3 shows the flowchart of the method implemented with the system that is the subject of the invention. It is the appearance, 5 Figure 4 details the extended production chain elements added to the system that is the subject of the invention. It is appearance, Figure 5 shows the seamless verification of the invention system from milking to consumer. This is a flowchart view of the chain. Figure 6 shows the production boiler data node, recipe compliance verification module, mass 10. balance control module, final product spectroscopic analysis module, molecular functional connection diagram of the analyzer and label production control module It is appearance, Figure 7 shows the regional specific starter culture dosing unit for animal-culture. Combination assignment module and volume-proportional precision dosing pump for milking 15 It is a view of its positioning along the line. Figure 8 shows the external analysis with a vendor-independent software as a service (SaaS) architecture. Data identifier (DAT) module, external lab results reconciliation module, multi-vendor data adapter layer, vendor-independent cross-interoperability orchestration module and two This is a view of the connection scheme between layered data ownership boundary descriptors, 20 Figure 9 shows the milk-cheese-whey biological chain authentication architecture for milk- cheese biological chain authentication module, whey biological identity verification module and derivative product biological-operational hybrid identity chain module This is a view of the flowchart between them. Figure 10 shows the N-way parallel individual tank-boiler architecture (1:1:1 25) of the system that is the subject of the invention. Matching: the appearance of an animal (a holding tank, a production boiler). Explanation of Reference Numbers 16 Reference Number Reference Name Layer 1 (Milking and Quality Orientation) Layer B, Layer 2 (Biochemical Analysis) Layer C 3 (Data Transformation and Blockchain) Layer D 4 (Physical Security Labeling) E Layer 5 (Consumer Verification) F Layer 6 (Individual Tank Waiting and Production Start) G Layer 7 (In-Production Vessel Process Monitoring) H Layer 8 (Automatic Sampling and Multi-Analysis Validation) Layer 9 (Label Production Control and Maturation Monitoring) Robotic Milking Unit 11. Radio Frequency Animal Identifier (RFID) — RFID, NFC, BLE, UWB, LoRa, biometric identifier or equivalent interpreted as a wireless animal identification element. 12 Teat Flowmeters 13 Milking Line Electrical Conductivity Sensor 14. Flow Meter (volume of milk transfer from holding tank to production tank) (for measurement) Quality-Based Automatic Pipe Guidance Mechanism 16 Individual Tank Diverter Valves 17 General Tank Diverter Valves 18 Machine Learning-Based Quality Prediction Modules 19 Veterinary Registry Database Integration Module 17 Data Capture Module 22 Wearable Animal Welfare Monitoring Modules 24 Individual Animal Identification Profile Modules Milking Session Identifier (MSI) 40 Milk Analyzers — FT-IR, MIR, NIR, Raman, ultrasonic, microfluidic biosensor or interpreted as equivalent milk composition analysis technologies 50 Analytical Matching Modules 55 Machine Learning-Based Biochemical Fingerprint Modules 60 Environmental Sensor Network 65 Sustainability Data Calculation Module 70 Data Transformation and Loading Layer (ETL) 75 Edge Computing / Local Cache Module 80 Blockchain Registry Modules (Permission-based Distributed Ledger Network, BatchRegistry) or equivalent smart contract) 84 External Analysis Descriptor (DAT) Module 85 External Laboratory Results Reconciliation Module 86 Milk-Cheese Biological Chain of Identity Verification Module 90 Double Layer Physical Security Elements 91 Machine-Readable Verification Elements — QR code, DataMatrix, hologram, optical watermark, microscopic surface pattern or equivalent machine-readable identifier 92 Non-Contact Electronic Microverification Elements — 18 NFC microchip, BLE beacon, UHF RFID, PUF or equivalent. non-contact electronic identifier 95 Product Lifecycle Status Manager 99 Whey Biological Authentication Module 100 Disposable Token Mechanism 105 Sequential Reading Verification Session Manager 110 Verification and Security Module 115 Machine Learning-Based Behavioral Anomaly Detection Modules 120 Forensic Expert Witness Evidence Preservation Module 125 Individual Holding Tanks Environmental Monitoring Module 126 Holding Tank CIP (Clean-In-Place) Cycle Verification Module 127 Operator Authentication and Badge Management Module 128 Sample Chain of Custody NFC Session Module 130 Smart Manufacturing Boiler Data Node 135 Prescription Compliance Verification Module 140 Mass Balance Control Module 145 Production Line Image Monitoring Module 150 Final Product Spectroscopic Analysis Module — NIR, FT-IR, MIR, Raman, hyperspectral, ultrasound, mass spectrometry or equivalent 160 Regional Specific Starter Culture Dosing Units 161 Animal-Culture Combination Assignment Module 162 Volume-Proportional Precision Dosing Pump 19 165 Robotic Sample Collection Stations 170 Molecular Analyzer Interfaces — Multiplex PCR, dPCR, CRISPR-Cas, isothermal amplification (LAMP, RPA), nanopore sequencing or equivalent 171 Quantitative Molecular Concentration Verification Module 175 Automatic Label Production Control Module 180 Maturation Chamber Environmental Monitoring and Access Control Module 185 Cold Chain Tracking Module (Optional) 188 Individual Animal-Derivative Product Line Integrity Module 190 Multi-Vendor Data Adapter Layers 191 Vendor-Independent Cross-Interoperability Orchestration Module 192 Two-Layer Data Ownership Boundary Descriptor 193 Central Scanning and Registration Servers — By passively reading all sensors and data sources, under SOK (Sensor Control). a central authority that consolidates and writes a single ledger stream to the blockchain presenter 194 Synchronized Time Source Module — At the stratum 1 level, GPSDO, atomic reference clock, or RFC. Centralized time containing an NTPv4 server with the 5905 standard. synchronization source 195 Whey Grade Segregation and Premium Flow Navigation Module 196 Derivative Product Line Process Tracking and Session ID Continuity Module Adapted Multilayer Packaging Validation for 197 Derivative Products Layer 198 Multi-Product Cuvée Registration and Verification Mechanism 199 Derivative Product Biological-Operational Hybrid Identity Chain Module Method Steps 200: Automatic data transfer of individual animal data via the interface of the robotic milking unit. capture and unique SOK assignment 202: With the RFID (11) data of the animal-culture combination assignment module (161). 5 Called from the central module 205: By querying the veterinary record database integration module (19), the animal's Checking whether it is in the breakthrough phase; if it is in the breakthrough phase, milk directly 208 Directing to the general tank Instantaneous milk volume measured during milking (flowmeter) 12 data) proportionally by the precision dosing pump (162) regional starter culture 10 The combination is automatically injected into the milk stream, and the injection event is SOK. (30) together with the blockchain record module (80) is processed cryptographically. 210: Evaluation of real-time sensor data during milking to determine suitability for the target product. the decision is made and the milk is automatically directed through pipes to either individual or general tanks. 212: After the milk is transferred to the individual holding tank, the holding tank's environmental 15 monitoring module (125) +4°C temperature stabilization control, lid opening log and 24 start the hourly waiting timer 213: Activity of the wearable animal welfare monitoring module (22) at the time of milking, rumination measuring duration, body temperature and behavioral parameters and the well-being score SOK (30) by connecting to the blockchain module (80) 20 215: Cheese production suitability with machine learning-based quality prediction module (18) probabilistic calculation of the score 218: After the daily milking process is completed, the waiting tank monitoring module (125) put the tank into "ready for production" status 220: Processing of the milk sample from the same milking session in the milk analyzer (40) 25 222: From the cheese master's (operator's) badge authentication module (127) With RFID, NFC, biometric identification, or mobile QR code-based authentication. 21 initiating the production process; operator ID, authorization status, and initiation time. The operator's stamp is cryptographically signed on the blockchain module (80). to be recorded as a signature 225: Machine learning-based biochemical fingerprint module (55) for milk source probabilistic verification 5 228: Transfer during the transfer of milk from the individual holding tank to the production boiler. Measuring the volume with the flow meter (14) of the smart production boiler data node (130) activation and transfer event in connection with SOK (30) blockchain record processing of module (80) 230: Matching milking data with analysis results based on SOC and matching 10 cryptographic verification 232: pH probe, temperature sensor inside the smart production boiler data node (130) and by reading the mixing speed encoder data at predefined intervals obtaining a cryptographic hash (SHA-256, SHA-3, BLAKE3, or equivalent) and recording it on the blockchain. processing of the module (80); simultaneously processing of the prescription compliance verification module (135) 15 checking the conformity of the boiler curve with the raw material analysis profile 235: Sustainability data calculation module (65) with batch basis carbon footprint, water calculation of consumption, energy use and methane emission values 236: Multiple non-boiler process steps of the production line image monitoring module (145). continuous recording with a camera; AI-based process anomaly detection 20 Detecting deviations from the process using algorithms; image hashes on the blockchain processing of module (80) 237: Barn interior and exterior data collected 24 / 7 continuously by the environmental sensor network (60). The values ​​of meteorological parameters measured during the milking session are SOK (30) 25 by temporally matching with the batch-specific environmental context fingerprint. processing into the blockchain module (80) 240: Processing the matching data packet into the authorized distributed ledger network and creating an immutable record. creation 245: Edge computing / local cache module (75) interrupted internet connection When it is accessed, the data is cached locally in a cryptographically signed form and 30 Automatic synchronization to the blockchain network when the connection is re-established. 22 250: Application of a double-layered physical security element (90) to the final product — machine- Readable verification element (91) with touchless electronic microverification structural integration of element (92) 251: Microstructured machine-readable verification element (91), final product packaging Information on batch-specific one-time token mechanism (100) on the verification surface 5 implementation as embedded 252: The touchless electronic micro-verification element (92), machine-readable under the verification element (91); the element is permanently disabled by peeling off the label. structurally integrated in a way that will leave 255: Initiating sequential read verification session (105): user first touchless 10 Creating a session token by reading the electronic micro-verification element (92), then read the machine-readable verification element (91) within a limited time 260: Consumer verification: sequential read control, session duration control, single Token redundancy verification and geographic anomaly check 261: Physically impossible simultaneous location determination 15 262: Generating fraud alerts and writing alert entries in the distributed ledger. 265: Verification with machine learning-based behavioral anomaly detection module (115) analysis of the entrepreneurial pattern 268: Robotic sampling station after cheese production is complete. (165) taking samples from the final product autonomously; sample storage 20 Time-stamped NFC tagging and analysis with the NFC session module (128) automatic transfer to devices 270: All milking data, quality decisions, blockchain hashes, and verification logs. Forensic expert evidence storage module (120) with redundancy and within the period required by legislation 25 archiving throughout 272: Processing and obtaining the final product of the sample in the spectroscopic analysis module (150). Comparison of obtained composition values ​​with raw material milk analysis profile 276: Single reaction from sample via molecular analysis device interface (170); (i) regional starter culture combination identifier assigned to the animal, (ii) GMO markers, 30 23 (iii) feed source plant DNA signature, and (iv) animal breed genetic markers simultaneously. scanning; signature with quantitative molecular concentration verification module (171) measuring its density 277: Milk-cheese biological chain authentication module (86); at the time of milking Genetic 5 of the regional starter culture combination injected into individual animals culture identified by molecular analysis in the final cheese sample Automatic comparison of the conformity of the signature on the basis of SOK (30) 280: Total milk recorded during milking by the mass balance control module (140) calculating the ratio between the volume and the mass of the final cheese produced; the ratio Checking whether the raw material milk type is within the theoretical upper yield limit. 10 284: All validations in the analytical matching module (50) holistic evaluation; automatic label generation if all verifications are successful. control module (175) machine-readable verification element (91) and touchless electronic microverification element (92) allows label production; otherwise Autonomous cessation of the labeling line and registration of "non-compliant party" 15 processing into the blockchain module (80) 288: Transfer of the labeled product to the ripening chamber and ripening chamber The environmental monitoring module (180) starts tracking by matching the product to the location. 292: Temperature and humidity inside the ripening chamber during the ripening period, carbon dioxide level, room entry and exit logs, and product location within the room 20 synchronization of information to the blockchain module (80) 295: Whey biological authentication module (99); side of cheese production Molecular analysis of the whey sample, which is the product, identified the starter assigned to the animal. Detection of the genetic signature of the culture combination and original with SOK (30) Connecting to milking session 25 296: Derivative product biological-operational hybrid identity chain module (199); DNA (a) — biological identification by molecular detection for derivative products in which integrity is preserved (b) — ensuring continuity; pathway for derivative products where DNA integrity is lost Mass balance of individual animal-derived product line integrity module (188), cryptographic Chain of custody and segregation-based operational identity chain 30 ensuring continuity 24 297: Product lifecycle status manager (95); product verification status It manages three separate statuses: "active", "scanned", and "consumed"; consumed The state change is implemented in the blockchain module based on the events that trigger the transition to the current state. (80) cryptographic processing 298: External analysis identifier (DAT) module (84); 5 to third party laboratory The sample sent has a unique cryptographic link to the original SOK (30). Assignment of identifier; reconciliation of external laboratory results. a single blockchain block is automatically matched via DAT by module (85) processed as Detailed Description of the Invention The invention has implications for dairy farming, food traceability, distributed ledger technology (blockchain), and much more. In the field of layered physical-digital product safety, milking is done on an individual dairy animal basis. data collection, automated pipe routing based on milk quality, biochemical analysis, and machine learning-based quality prediction, biochemical fingerprinting verification, and 15 Fraud anomaly detection and blockchain-based fraud prevention systems It is a system and method for integrated integration. The invention relates to the continuous verification chain from milking to the consumer, as shown in Figure 5. forming the middle rings; individual animal-specific regional starter culture dosage unit and pump (160-162), individual holding tank environmental monitoring (125-126), 20 Operator authentication (127), production boiler internal process parameter monitoring, boiler external process image monitoring module (145), robotic sampling station (165), final product Spectroscopic analysis (150), molecular analysis instrument interface and validation module (170-171), mass balance control (140), automatic label production control module (175) and includes the elements of the maturation chamber environmental monitoring module (180). 25 The system also utilizes a vendor-independent software as a service (SaaS) model, as shown in Figure 8. external analysis identifier (84) and external laboratory result reconciliation (85) The modules are shown in Figure 9 (Figure 9: milk-cheese-whey biological chain of identity). milk-cheese biological chain authentication module with validation architecture (86), cheese groundwater biological authentication module (99) and derivative product biological-operational 30 This is a view of the flowchart between the hybrid identity chain module (199), ), milk-cheese-whey biological chain authentication modules (86, 99, 199), Individual animal-derived product line integrity module (188), wearable animal welfare monitoring module (22), individual animal identification profile module (24) and product lifecycle status The manager (95) includes the elements (Figure 8 vendor-independent software service model (SaaS)) External Analysis Descriptor (DAT) Module (84) with its architecture, external laboratory result 5 reconciliation module (85), multi-vendor data adapter layer (190), vendor-independent Cross-operability orchestration module (191) and two-tier data ownership boundary This is the view of the connection diagram between the identifier (192), ). The system described in the invention is based on the following: cow (Bos taurus), sheep (Ovis aries), goat (Capra aegagrus 10 buffalo (Bubalus bubalis), camel (Camelus), and other dairy-producing domestic mammals. It operates independently of animal species. The system works regardless of breed. (Holstein, Jersey, Simmental, Awassi, Ivesi, Saanen, etc.) all animal breeds applicable. The system works regardless of the target product type; cheese, butter, cream, 15 yogurt, kefir, buttermilk, curd cheese, ice cream, milk powder, and all derivatives produced from milk raw materials. It provides traceability infrastructure for products. System Layers The system described in the invention covers the entire process, from milking to consumer verification. It consists of functionally separated layers (Figure 1): 20 Layer 1 (A) — Milking and Quality Guidance: By robotic milking unit (10) The generated data is used to identify individual animals with RFID or equivalent animal identifiers (11). It is captured by matching. The veterinary record database integration module (19) of the animal It checks the breakthrough time status. Conductivity sensor (13), flowmeter (12) and machine Learning-based quality prediction module (18) outputs, quality-based automated pipe 25 It provides input to the steering mechanism (15). The mechanism directs milk to the target product. Depending on suitability, the individual tank diverter valve (16) or the general tank activates the diverter valve (17). A unique SOK (30) for each milking session. It is assigned. Animal-culture combination assignment module (161) with RFID (11) data. The regionally specific starter culture combination assigned to the animal is called upon by questioning; 30 volume-proportional precision dosing pump (162), instantaneous milk volume measured during milking 26 The system automatically doses the culture combination proportionally into the milk flow. The wearable animal welfare monitoring module (22) monitors activity, rumination time, and body at the time of milking. Measures temperature and behavioral parameters; individual animal identification profile module (24) Demographic, physiological baseline, medical history and descriptive data are collected upon RFID query. It provides the data. 5 Layer 2 (B) — Biochemical Analysis: Milk molecular analyzer interface (40); FT-IR, MIR, NIR, Raman, ultrasonic or microfluidic biosensor-based to the same SOC fat, protein, lactose, SCC, MUN and freezing point values ​​of the milk sample. Analytical matching module (50) measures these results based on SOK milking data. It matches and creates a biochemical fingerprint. 10 Machine learning-based biochemical fingerprint module (55), instant fingerprint Probabilistically assessing the accuracy of a milk source by comparing it to the animal's past baseline. confirms this. Layer 3 (C) — Data Transformation and Blockchain: Environmental sensor network (60) enriched data, carbon by sustainability data calculation module (65), 15 Water, energy, and methane values ​​are processed. Data transformation and loading layer (ETL) (70) signs the data with a cryptographic hash (SHA-256, SHA-3, BLAKE3 or equivalent). Edge computing / local cache module (75) stores data locally in case of internet outage It accumulates. The blockchain record module (80), BatchRegistry or equivalent smart contract It creates an unchangeable record. External analysis identifier module (84) and external laboratory 20 The results reconciliation module (85) enables third-party laboratory integration. Layer 4 (D) — Physical Security Labeling: Double-layered physical security element. (90); machine-readable authentication element (91) — QR code, DataMatrix, hologram, optical a watermark or microscopic surface pattern — structurally integrated beneath this element from the touchless electronic micro-verification element (92) — NFC chip, BLE 25 It consists of a beacon, UHF RFID, PUF, or equivalent. Attempting to strip the top element will affect the bottom one. Permanently disables the electronic element. Machine-readable verification element. (91); a random one will be embedded in the hologram base and change with each attempt to read it. It can be configured to generate a verification code; this allows a static copy to be created. Replay is prevented. For the verification to be considered valid, machine-30 touchless electronic with random code generated by readable verification element (91) the identity of the micro-verification element (92) together in the same verification session 27 It must match; reading any single element alone does not constitute valid validation. It does not create. The one-time token mechanism (100) creates a unique token for each batch. It produces. Automatic label production control module (175) all verifications were successful. Tagging is automatically blocked if it is not cryptographically confirmed. 5 Layer 5 (E) — Consumer Authentication: Sequential read authentication session manager (105), It enables the sequential reading of two validation elements in the same session. Validation and Security module (110) collects IP, GPS, device fingerprint and timestamp information of the enterprise. It monitors. The machine learning-based behavioral anomaly detection module (115) detects suspicious It identifies patterns through unsupervised learning. Product lifecycle status manager 10 (95) — by managing the "active", "scanned" and "consumed" statuses — done in the store Multiple verification attempts (browse mode) should not deplete the token, in reality. The triggering events for the consumption event are (mechanical damage, geographic-temporal anomaly, It enables marking via point-of-sale registration (consumer declaration). Forensic expert opinion. The evidence storage module (120) archives all verification logs in a redundant manner. 15 Layer 6 (F) — Individual Tank Standby and Production Initiation: Standby tank environmental Monitoring module (125), in individual milk holding tank at +4°C temperature approximately 24 During the hourly waiting period, it monitors temperature, records the lid opening log, and tracks the duration. The holding tank CIP cycle verification module (126) checks the tank between successive milkings. It records the in-situ cleaning cycle with conductivity, temperature, and time parameters. 20 Operator authentication and badge management module (127), cheese master's production initiation authorization via RFID, NFC, biometric identification, or mobile QR code-based identification. Verifies with verification elements. Sample storage chain NFC session module (128), for any sample taken at this layer (intermediate sample taken from the holding tank) (including samples) initiates a chain of custody session with time-stamped NFC tagging; 25 the session in question proceeded under the same SOK to the subsequent sampling and analysis stages is transferred. Layer 7 (G) — Process Monitoring Inside the Production Boiler: Individual milk flow meter (14) The transfer volume is measured during the transfer from the holding tank to the production boiler, and The transfer event is processed on the blockchain in connection with the SOK. The smart 30 shown in Figure 6. production boiler data node (130), pH probe, temperature sensor and mixing speed The encoder collects data at predefined intervals (e.g., every 60 seconds). 28 (Figure 6; production boiler data node (130), recipe compliance verification module (135), mass balance control module (140), final product spectroscopic analysis module (150), molecular analyzer (170-171) and label production control This is a view of the functional connection diagram of the module (175), Data is signed with a cryptographic hash and processed into the blockchain module (80). Recipe compliance 5 Verification module (135), compatibility of the boiler curve with the raw material analysis profile. It monitors the production line image monitoring module (145), multiple non-boiler process steps. It records it with a camera. Layer 8 (H) — Automated Sampling and Multi-Analysis Validation: Robotic sampling Taking station (165), core sampling from the final product when cheese production is completed, 10 Automated sampling is carried out using a trier or equivalent technique; the sample is stored in a sample storage chain. By tagging with a time stamp using the NFC session module (128), it can be automatically sent to the analyzer. It transfers the final product spectroscopic analysis module (150), the composition values ​​of the cheese. It measures. Molecular analysis device interface (170), starter culture identity in a single reaction, GMO markers, feed source plant DNA signatures, and animal breed genetic markers are all considered equivalent. Timely scan. Quantitative molecular concentration verification module (171) signature It measures the density. Mass balance control module (140) milk inlet volume and cheese outlet volume. It monitors the ratio between masses. Milk-cheese biological chain authentication module. (86), culture detected in cheese with combination of culture injected during milking It verifies the conformity of its signature based on SOK; whey biological authentication 20 module (99) traces the same culture signature in whey. Layer 9 (I) — Label Production Control and Maturation Monitoring: Automated label production control module (175), double layer if all verifications are successful It allows the production of a physical security element; otherwise, the labeling line would be autonomous. It stops as follows: 25 Maturation chamber environmental monitoring and access control module (180), maturation Throughout the period, temperature, humidity, CO2, room entry and exit logs, and product location are continuously monitored. Synchronizes to the blockchain. Optional cold chain tracking module (185) The shipment can monitor temperature breakage. Cross-Layered Infrastructure (Layer A — Combines I): The 30 layers above All the sensors and data sources are integrated into the blockchain module shown in Figure 2. (80) only in the position of data publisher without direct writing authority 29 It works. The central scanning and logging server (193) provides resources at all layers. in a predefined sequence and frequency (once every second during milking, production boiler) (every 60 seconds during the processes, every 5 minutes during the maturation chamber measurements) It consolidates the data it collects by querying under the milking session ID (SOK) (30). and the cryptographic hash of the consolidated data to the blockchain module (80) as a single record stream 5 It functions as follows. The synchronized time source module (194), shown in Figure 10, controls the entire system. components at the Stratum 1 level GPSDO, atomic reference clock or RFC 5905 with ±10 milliseconds or more precise synchronization from a standard NTPv4 server This takes time; thus, the chronological ordering of all blockchain records. It becomes cryptographically verifiable. This cross-layered architecture, 10 physical destruction or manipulation of any sensor Even in this situation, it ensures the integrity of the blockchain is preserved. Figure 10 shows the N-way parallel individual tank-boiler architecture (1:1:1) of the system that is the subject of the invention. Matching: the appearance of an animal (a holding tank, a production boiler); closed pipe lines, central scanning and recording server (193) and synchronized time 15 It shows the positioning of the source (194) within the system architecture. In Figure 10 The suffixes (indexes) in the form of “125-1, 125-2, …, 125-N” and “130-1, 130-2, …, 130-N” The representations are; individual standby tank monitoring module (125) and individual production respectively. the elements of the boiler data node (130) assigned to each individual animal It refers to separate instances on independent and parallel lines, and the word 20 The subject examples are collectively the individual standby tank monitoring module (125) and respectively. individual production boiler data node (130) represents; where “-1”, “-2”, “-N” The suffix is ​​not a reference number range, but rather a number corresponding to each animal of the same element. Specifies the sequence index of parallel copies. Sequential Read + Single Validation Session Architecture 25 One of the most important technical innovations of the invention is the double-layered physical security element. (90) Physical feasibility encountered during verification on the consumer side The sequential read + single validation session architecture solves the problem. The "simultaneous reading of two elements" approach suggested in previous techniques is practical. This is not feasible; smartphones have their NFC antenna on the back of the device, and the camera on the front. Because it is positioned on the face, both readings cannot be performed physically at the same time. The system in question solves this problem with the sequential read verification session manager (105) It solves it through: ● Step 1 — Session Initiation: User contactless electronic micro-authentication It reads element (92). Sequential read validation session manager (105) limited. A duration (e.g., 60 seconds) generates a valid session token; device fingerprint, GPS 5 It signs with location, IP address, and timestamp. ● Step 2 — Second Factor Reading: User machine within the same session- It reads the readable verification element (91). The phone camera reads the element and The one-time token mechanism (100) with the first element ID is the same session token They are combined under 10. ● Step 3 — Unified Authentication: Authentication and security module (110), session Token + element IDs + GPS + IP + device fingerprint in a single blockchain message. It transmits the data to the module. The smart contract processes both readings in the same session, from the same device. It was cryptographically confirmed that the event occurred from the same location and without exceeding the session duration. truths. 15 ● Step 4 — Life Cycle Status Assessment: Product life cycle The status manager (95) checks the current status of the product. In the store, more than one Many potential consumers can validate the same product; consumption triggers events. The token is not consumed until the event occurs. This architecture is suitable for the following attack scenarios: It provides protection against: 20 ● Scenario A (Label Cloning): The fraudulent agent photographs the machine-readable element; However, a session cannot be initiated without the electronic micro-component. ● Scenario B (Electronic Chip Removal): Removal due to the double-layered element (90) structure permanently disables the initiative element. ● Scenario C (Session Duration Violation): Device fingerprint mismatch verification takes 25 minutes. He refuses. ● Scenario D (Geographic Anomaly): GPS discrepancy causes the verification to fail. ● Scenario E (Biochemical Fraud): ML biochemical fingerprint module (55) It detects milk-product incompatibility. ● Scenario F (Bot Attack): 30 by ML behavioral anomaly module (115) It is detected. 31 ● Scenario G (Milk Mixing): Molecular analyzer interface (170) starter culture It detects density anomalies in the signature. ● Scenario H (Boiler Intervention): Continuous operation of the production boiler data node (130) Records are found to be non-compliant by the prescription compliance verification module (135). ● Scenario I (Efficiency Fraud): Mass balance control module (140) theoretical efficiency 5 It detects the rate that exceeds the upper limit. ● Scenario J (GMO Counterfeiting): Molecular analysis device interface (170) GMO It identifies the markers. ● Scenario K (Maturation Intervention): Module (180) detects unauthorized room entry. It does; monthly random molecular analysis checks the chain of identity. 10 ● Scenario L (Fake Sample): Sample storage chain NFC session module (128) It prevents samples from being brought in from outside. ● Scenario M (Unauthorized Operator): Operator authentication module (127) It prevents unauthorized initiation. ● Scenario N (Cross-Contamination): CIP cycle verification module (126) 15 It documents inadequate cleaning. ● Scenario O (Milk-Cheese Identity Disconnect): The milk-cheese biological identity chain. The verification module (86) detects the incompatibility. ● Scenario P (Whey Fraud): Whey biological identity The verification module (99) generates a warning in case of incompatibility. 20 ● Scenario Q (Post-Distillation Derivative Product Fraud): Derivative product biological- Operational hybrid identity chain module (199) individual animal-derived product line It questions the operational proof of integrity of the module (188). ● Scenario R (Multiple Validation Exhaustion): Product lifecycle status The manager (95) only allows the state to be consumed with certain trigger events. 25 In a preferred application of the invention, the operator or Intervention vectors that third parties may carry out and responses to these vectors. The protection mechanisms provided by the system are consolidated in the following summary table. It is presented as follows: 32 Operator / Third Party Party Intervention Vector System Protection Its mechanism Related Element(s) Move into the process start or delayed registration Operator authentication automatic timestamp; 24 maximum waiting time in hours control 127, 125 Milk is wrong (to another animal) (belonging to) the cauldron direction Closed, sealed, and individual. animal-specific pipeline architecture — physically It cannot be done 125, 130, 80 Individual animal to his milk animal milk mixing Multiple sensors (40, 55) + ultimate product spectroscopic analysis (150) with raw material-product compatibility score 40, 55, 86, 150, 171 Non-prescription heat process, pH or to mix up deviation Hashed recipe + prescription in the compliance verification module tolerance control 130, 135 Maya, rennet or starter culture manual amount intervention Automatic tracer dosing sealed closed system housing — operator physically inaccessible 160, 161, 162 Cedarlama, molding or pressing in your steps unlawful intervention Multiple non-boiler processes camera + AI based Continuous anomaly detection monitoring 145 33 The cheese produced amount more than to be shown (production fraud) Milk input volume and final cheese theoretical efficiency between masses upper limit control 14, 140 "Production finished" announcement. then party mixing Automatic from the final product sampling + spectroscopic + molecular raw material profile through analysis harmony 165, 150, 170, 171, 86 Operational Flow of the System Subject to the Invention The steps involved in the process are as follows: Automatic data of individual animals via the robotic milking unit interface. capture and unique SOK assignment (200), Querying the animal-culture combination assignment module (161) with RFID (11) data 5 and the center of the unique regional starter culture combination assigned to the animal. Calling from the module (202), By querying the veterinary record database (19), it can be determined whether the animal is in the expulsion period. checking that it is not present; during the breakthrough period, the milk goes directly into the general tank. Direction 208 Instantaneous milk volume measured during milking (flowmeter data 12) 10 regional starter culture by proportionally sensitive dosing pump (162) The combination is automatically injected into the milk stream, and the injection event is SOK. (30) together with the blockchain record module (80) is processed cryptographically (205), The suitability of the product for the target crop is determined by evaluating real-time sensor data during milking. delivery and automatic pipe directing of milk to individual or general tank (210), 15 After the milk is transferred to the individual holding tank, the holding tank undergoes environmental monitoring. module (125) +4°C temperature stabilization control, cover opening log and 24 hour start the waiting time counter (212), 34 Activity, rumination time at the time of milking of the wearable animal welfare monitoring module (22), measuring body temperature and behavioral parameters and the well-being score with SOK (30) by connecting to the blockchain module (80) processing (213), Cheese production suitability with machine learning-based quality prediction module (18) Probabilistic calculation of the score (215), 5 After the daily milking process is completed, the waiting tank monitoring module (125) to put the tank into "ready for production" status (218), Processing of the milk sample from the same milking session in the milk analyzer (40) (220), RFID from the cheese master's (operator's) badge authentication module (127), Production with NFC, biometric identification, or mobile QR code-based authentication 10 initiating the process; operator ID, authorization status, and initiation time. The operator's stamp is cryptographically signed on the blockchain module (80). to be recorded as signature (222), With the machine learning based biochemical fingerprint module (55) of the milk source probabilistic verification (225), 15 Transfer during the transfer of milk from the individual holding tank to the production boiler. Measuring the volume with the flow meter (14) of the smart production boiler data node (130) activation and transfer event to the blockchain module in connection with SOK (30) (80) recording (228), Matching milking data with analysis results based on SOC and the matching of 20 cryptographic verification (230), The pH probe, temperature sensor and inside the smart production boiler data node (130) The scrambling speed cryptographically reads encoder data at predefined intervals. It retrieves the hash (SHA-256, SHA-3, BLAKE3 or equivalent) and sends it to the blockchain record module. (80) operation; simultaneously the prescription compliance verification module (135) win 25 (232) Carbon footprint and water per batch with the sustainability data calculation module (65) Calculation of consumption, energy use and methane emission values ​​(235), Production line image monitoring module (145) multiple camera non-boiler process steps by continuously recording data; with AI-based process anomaly detection algorithms 30 35 Detection of deviations from the process; image hashes into the blockchain module (80) processing (236), Barn interior and exterior images are collected 24 / 7 continuously by the environmental sensor network (60). The values ​​of meteorological parameters measured during the milking session are SOK (30) By temporally matching it, a batch-specific environmental context fingerprint is obtained. (237) processing into the blockchain module (80), Processing the matching data packet into the authorized distributed ledger network and creating an immutable record. creation (240), Edge computing / local cache module (75) interrupts internet connection When it is accessed, the data is cached locally in a cryptographically signed form and 10 Automatic synchronization to the blockchain network when the connection is re-established (245), Applying a double layer of physical security element (90) to the final product — machine- Readable verification element (91) with touchless electronic microverification structural integration of element (92) (250), The microstructured machine-readable verification element (91) of the final product packaging 15 Information on batch-specific one-time token mechanism (100) on the verification surface Implementation as embedded (251), The touchless electronic micro-verification element (92) is machine-readable under the verification element (91); the element is permanently disabled by peeling off the label. structural integration in such a way as to leave (252), 20 Initiating a sequential read verification session: the user first uses a touchless electronic device. Creating a session token by reading the micro-authentication element (92), then limited machine-readable verification element (91) reading (255) during the period, Consumer verification: sequential read control, session duration verification, one-time use. Token verification and geographic anomaly check (260), 25 Physically impossible simultaneous location determination (261), Generating a fraud warning and writing a warning entry in the distributed ledger (262), Verification with machine learning-based behavioral anomaly detection module (115) analysis of the entrepreneurial pattern (265), 36 After the cheese production is completed, the robotic sampling station (165) autonomous sampling of the final product; sample storage chain Time-stamped NFC tagging and analysis with NFC session module (128) automatic transfer to their devices (268), All milking data, quality decisions, blockchain hashes, and verification logs are subject to forensic analysis. with the expert witness evidence storage module (120) and within the time required by legislation. archiving throughout (270), The sample is processed in the final product spectroscopic analysis module (150) and the obtained Comparison of composition values ​​with raw material milk analysis profile (272), In a single reaction from the sample via the molecular analysis device interface (170); (i) 10 (ii) regional starter culture combination identifier assigned to the animal, (iii) GMO markers feed source plant DNA signature, and (iv) animal breed genetic markers simultaneously scanning; signature with quantitative molecular concentration verification module (171) measurement of density (276), Milk-cheese biological chain authentication module (86); individual 15 at milking time genetic identity of the regional starter culture combination injected into the animal culture signature detected in the final cheese sample through molecular analysis Automatic comparison of its compatibility based on SOK (30) (277), The total milk volume recorded during milking by the mass balance control module (140) Calculating the ratio between the mass of the raw material milk and the mass of the final cheese produced; the ratio is 20% milk. Checking whether it is within the theoretical upper limit of efficiency for the type (280), Holistic evaluation of all validations in the analytical matching module (50); If all verifications are successful, the automatic label production control module (175) machine-readable verification element (91) and touchless electronic micro verification element (92) allows label production; otherwise label line 25 autonomous stopping and recording of "non-compliant party" in the blockchain module (80) processing (284), The labeled product is transferred to the ripening chamber, and the ripening chamber environment... The tracking module (180) starts the tracking by matching the product-location (288), 37 During the ripening period, the temperature and humidity inside the ripening chamber, carbon dioxide level, room entry and exit logs, and the product's location within the room. Synchronization of information to the blockchain module (80) (292), Whey biological authentication module (99); byproduct of cheese production Molecular analysis of the whey sample revealed the presence of starter culture 5 assigned to the animal. Detection of the genetic signature of the combination and the original milking with SOK (30) connecting to the session (295), Derivative product biological-operational hybrid identity chain module (199); DNA (a) — biological identification by molecular detection for derivative products in which integrity is preserved ensuring continuity; pathway for derivative products where DNA integrity is lost (b) — 10 Mass balance of individual animal-derived product line integrity module (188), cryptographic Chain of custody and segregation-based operational identity chain. ensuring continuity (296), Product lifecycle status manager (95); product verification status "active", It manages under three separate states: "scanned" and "consumed"; the "consumed" state has 15 Change of state on events triggering the transition to the blockchain module (80) cryptographic processing (297), External analysis identifier (DAT) module (84); sent to third-party laboratory a unique identifier cryptographically linked to the sample with the original SOK (30) appointment; external laboratory result reconciliation module (85) 20 automatically matched via DAT as a single blockchain block. processing (298). The system starts working when a dairy animal enters the robotic milking unit (10). RFID (11) defines the animal; veterinary record database integration module (19) breakthrough queries duration status (205); individual animal identification profile (24) and wearable welfare 25 Monitoring module (22) data is linked under milking session ID (SOK) (30). If the animal is not in the breakthrough period, the animal-culture combination assignment module (161) It retrieves the regional starter culture combination assigned to the animal from the central module. (202) (Figure 3). The culture combination in question is autochthonous, specific to the production location. 30 LAB strains isolated from microflora and listed in the EFSA QPS list It consists of a volume-proportional precision dosing pump (162), from the flowmeter (12). It takes instantaneous milk volume data as input and adjusts the culture combination proportionally to the milk flow. 38 It automatically injects as (208). The injection event is with SOK to the blockchain module (80) It is processed cryptographically. Environmental sensor network (60) collects barn indoor and outdoor meteorological parameters 24 / 7; with SOK By being matched temporally, the environmental context is processed into the blockchain as a fingerprint. (237). 5 Quality-based automatic pipe routing mechanism (15) for individual or general tanks It directs (210). After the milk is transferred to the individual holding tank, as shown in Figure 4. The visible waiting tank environmental monitoring module (125) monitors the +4°C temperature, lid starts the startup log and the 24-hour waiting time counter (212). Milk molecular analyzer interface (40) processes milk sample (220); analytical matching 10 module (50) and ML biochemical fingerprint module (55) milk belonging to the animal calculates the probability (225). When daily milking is completed, the standby tank monitoring module (125) switches the tank to "for production". It switches to the "ready" status (218). Operator (cheese maker) operator authentication from module (127) RFID, NFC, biometric identification or mobile QR code based identification 15 It performs identity verification with verification elements; the operator signature is transferred to the blockchain. recorded (222). Milk is transferred from the individual holding tank to the production boiler; operator or sealed in such a way that it cannot be physically interfered with by a third party. and is transferred through a sealed pipeline; this closed pipeline contains each 20 from the lines of other animals, exclusively for individual tank-boiler pairs. physically separated and access points with electronic lock or seal sensor It is equipped. The transfer volume is measured by flow meter (14) (228); any unauthorized The attempt to open is processed as an anomaly record in the blockchain module (80). Smart production boiler data node (130) pH, temperature and mixing data in advance 25 with cryptographic hashes (SHA-256, SHA-3, BLAKE3 or equivalent) at defined intervals blockchain jobs (232). Prescription compliance verification module (135) win curve It checks the compliance with the raw material analysis profile. Production line image monitoring module. (145) records the non-boiler process steps with AI-based process anomaly detection. (236). Throughout all stages of the workflow, the sensors in the milking line (12, 13) measure the milk molecular weight. Analyzer interface (40), standby tank monitoring module (125), production boiler data node (130), maturation chamber monitoring module (180), environmental sensor network (60) and 39 all sensors and data including the final product spectroscopic analysis module (150) The resources only operate in the role of a data publisher; in the blockchain module (80) They do not have direct write permissions. Central scanning and logging server (193), word the subject collects resources by querying them in a predefined order and frequency. consolidates the data under the milking session ID (SOK) (30) and its cryptographic hash is 5 It functions as a single record stream to the blockchain. Synchronous time source module (194); GPSDO, atomic reference clock or RFC 5905 NTPv4 server ±10 milliseconds. or provides more precise time synchronization; thus, events at all stages The chronological order is made cryptographically verifiable. When cheese production is complete, the robotic sampling station (165) will autonomously collect 10 samples. performs sampling from the final product (268); sample storage chain NFC session module (128) establishes a chain of custody. In the sample spectroscopic analysis module (150) and processed in molecular analysis device (170) (272, 276); quantitative molecular concentration The verification module (171) measures signature density. Milk-cheese biological identity chain. Verification module (86) Detection in cheese with combination of culture injected at milking 15 compares the obtained culture signature on the basis of SOC (277). Whey biological identity The verification module (99) searches for the same culture signature in the whey (295). Derivative product in its production, derivative product biological-operational hybrid identity chain module (199) DNA For products whose integrity is preserved, the biological detection method is obtained by distillation. For products where DNA is lost, the individual animal-derived product line integrity module is 20. (188) uses the operational identity chain path (296). Mass balance control module (140) controls the milk volume-cheese mass ratio (280). In third-party laboratory integration, each sample taken undergoes external analysis. cryptographically with the original SOK (30) by the identifier (DAT) module (84). A unique identifier is assigned to each milking batch. More than 25 from a single milking batch. multiple samples sent to multiple independent laboratories simultaneously or sequentially If submitted, a separate DAT is assigned to each sample, and the relevant DATs are consolidated within a DAT pool structure under the same original SOK (State Operating System). The results from each laboratory are processed; external laboratory results reconciliation module (85) It is matched with the original SOK via the relevant DAT; all results are multi-source 30 single traceability block to blockchain module (80) as analysis consolidation record It is processed in its structure (298). 40 In veterinary integration, multiple veterinary drugs can be administered to the animal simultaneously. (antibiotics, antiparasitic, anti-inflammatory, hormone and similar) administered In these cases, the veterinary record database integration module (19) for each drug It independently calculates the defined breakthrough period; the maximum of these breakthrough periods It designates the longer one as the "effective breakthrough period"; 5 until the effective breakthrough period ends. It ensures that the milk is automatically directed to the general tank diverting valve (17). Each treatment event is documented with the electronic signature of the administering veterinarian or the Turkish Veterinary Registry (TC Türk Veterinar). The Physicians' Association registration number is cryptographically entered into the blockchain module (80). is processed. The analytical matching module (50) evaluates all validations holistically (284). 10 If all verifications are successful, the automatic label production control module (175) double layer Approves the application of the physical security element (90) to the product packaging; otherwise The tagging pipeline is autonomously halted, and the "non-compliant party" record is entered into the blockchain. Machine-readable verification element (91) and contactless electronic micro on the packaging Verification element (92) is applied (250-252). Maturation chamber environmental monitoring 15 module (180) records the process (288, 292). Sequential reading in consumer verification. Verification session manager (105) and one-time token mechanism (100) are activated. enters (255-260); product lifecycle status manager (95) the product status is "active", It manages as "scanned" or "consumed" (297). All data is preserved for forensic expert evidence. It is archived redundantly with module (120) (270). 20 System Elements The system described in the invention includes the following elements: ● via application programming interface (REST, GraphQL, gRPC or equivalent) robotic milking unit that was questioned (10), ● Electronic identifier that uniquely identifies the animal (RFID, NFC, BLE, 25 (UWB, LoRa, biometric or equivalent) (11), ● teat flowmeter (12) which measures the instantaneous milk flow rate for each teat. ● milking line electrical conductivity sensor (13), ● Flow meter that measures the volume of milk transferred from the holding tank to the production tank. (14), 30 41 ● Quality-based automation as a rule engine that evaluates real-time sensor data. pipe guiding mechanism (15), ● individual tank diverting valve opened in the "appropriate" decision of the mechanism (15) (16), ● General tank orientation opened upon the decision of the mechanism (15) "not suitable" 5 valve (17), ● multiple with federated learning or equivalent data-privacy protection protocol Machine learning-based quality prediction module that can learn from farms (18), ● Querying breakthrough time data via veterinary record database integration Veterinary registration database integration module (19), 10 ● Data that queries the robotic milking unit via the application programming interface capture module (20), ● Activity, rumination, etc., are monitored continuously on the animal using wearable sensors. Connecting body temperature, estrus, and behavioral data to the blockchain using SOK (Senior Data Acquisition). functioning wearable animal welfare monitoring module (22), 15 ● demographic and physiological baseline, medical history and for each individual animal. keeping identifying data integrated and summarized in consumer verification individual animal identification profile module which can be presented in the form (24), ● A unique alphanumeric identifier is automatically assigned to each milking session. Session ID (SOK) (30), 20 ● milk composition analysis using FT-IR, MIR, NIR, Raman, ultrasonic or milk using any of the microfluidic biosensor technologies molecular analyzer interface (40), ● Matching lab results based on SOK (Source of Occurrence) and creating a biochemical fingerprint analytical matching module (50), 25 ● Machine trained on the historical biochemical profile specific to each animal learning-based biochemical fingerprint module (55), ● MQTT, AMQP, CoAP, OPC-UA or equivalent machine-to-machine communication protocol environmental sensor network (60) that collects barn interior and exterior parameters 24 / 7, ● Verifiable sustainability under EU CSRD / CBAM regulations 30 Sustainability data calculation module (65) which enables reporting. 42 ● Raw data is processed using a cryptographic hash algorithm (SHA-256, SHA-3, BLAKE3 or equivalent) signing data transformation and loading layer (ETL) (70), ● In case of internet connection interruption, data is stored locally with a cryptographic signature. caching edge computing / local cache module (75), ● BatchRegistry or equivalent batch register smart contract with cryptographic hash and 5 blockchain record module that processes metadata into the chain (80), ● The sample sent to third-party laboratories was cryptographically analyzed using the original SOK. External Analysis Descriptor (DAT) assigning a unique identifier linked as module (84), ● Automatically combine the third-party laboratory result with the original SOK via DAT 10 External lab results reconciliation module (85) that processes the blockchain by matching ● final genetic identity of the culture combination injected during milking milk-cheese comparison of culture signature compatibility in cheese based on SOC biological chain authentication module (86), ● machine-readable verification element (91) and contactless electronic micro 15 double-layer physical as mechanical integration of the verification element (92) security element (90), ● QR code, DataMatrix, hologram, optical watermark, or microscopic surface pattern machine-readable verification containing a batch-specific, single-use token. element (91), 20 ● NFC chip, BLE beacon, UHF RFID, PUF or equivalent contactless electronics Contactless electronic micro-authentication structured as identity technology. element (92), ● The product's consumer verification lifecycle is "active", "scanned" and "consumed". Product lifecycle status 25, which is managed under three separate situations. Manager (95), ● Animal-assigned culture detected by molecular analysis of whey sample. whey bioidentifier that detects the genetic signature of the combination verification module (99), ● 30 disposables that work with the sequential read validation session manager (105) token mechanism (100), 43 ● A limited-time session token that reads two authentication elements sequentially. Sequential generation of devices signed with fingerprint + GPS + IP + timestamp. Read verification session manager (105), ● Verification attempt that records IP and satellite location data. security module (110), 5 ● Machine learning that analyzes patterns of validation attempts learning-based behavioral anomaly detection module (115), ● Forensic systems that archive all data in a redundant manner for the legally required period. Expert witness evidence storage module (120), ● 24-hour waiting period for individual animals in a holding tank at +4°C. Waiting tank environmental monitoring module (125) which monitors during the period, ● holding tank that measures the CIP cycle of the holding tank between successive milkings CIP cycle verification module (126), ● Operator ID verifying authorization to start production by the cheese master. Verification and badge management module (127), 15 ● establishing a chain of custody with a timestamped NFC tag assigned to the sample Sample storage chain NFC session module (128), ● pH probe, temperature sensor and mixing encoder inside the production tank Smart production boiler data that collects data at predefined intervals node (130), 20 ● Recipe alignment that checks the alignment of the boiler curve with the raw material analysis profile. verification module (135), ● mass that controls the ratio between the total milk input volume and the final cheese mass. Balance control module (140), ● Production line image 25, monitoring non-boiler process steps with multiple cameras and AI. monitoring module (145), ● NIR, FT-IR, MIR, Raman, hyperspectral, ultrasound, mass spectrometry or Final product spectroscopic analysis module using equivalent technology (150), ● EFSA QPS list isolated from autochthonous microflora specific to the production site The regionally specific starter culture shown in Figure 7, formed from LAB strains, is 30. Dosing unit (160), (Figure 7 regional specific starter culture dosing unit (160), animal-culture combination assignment module (161) and volume- 44 positioning of the proportional precision dosing pump (162) on the milking line (is the appearance) ● In the central module, each milking animal has a unique LAB based on RFID. animal-culture combination assignment module (161), ● Inject the culture combination into the milk flow in proportion to the instantaneous milk volume. 5 volume-proportional precision dosing pump (162), ● Robotic system for autonomous sampling of holding tank, production boiler and final cheese. Sampling station (165), ● Starter culture, GMO, feed DNA and animal breed genetics all in a single reaction. Simultaneously screening markers; PCR / dPCR / CRISPR-Cas / isothermal 10 molecular amplification / nanopore sequencing or equivalent technology Analyzer interface (170), ● Quantitative measurement of signature density using Ct value or equivalent quantitative indicator molecular concentration verification module (171), ● An automated 15-second process that allows label production if all verifications are successful. label production control module (175), ● monitoring the environmental parameters of the maturation chamber and the chamber entry-exit logs. maturation chamber environmental monitoring and access control module (180), ● Cold chain tracking module optionally integrated into the final product packaging. (185), 20 ● In derivative products produced from biologically verified whey batches segregation through physical valve systems and cryptographic line-batch matching individual animal-derived product line integrity module (188), ● Vendor-independent adapter modules for data from third-party equipment. Multi-vendor data adapter layer (190), 25 ● Enables the simultaneous operation of multiple systems from different manufacturers. Vendor-independent cross-operability orchestration module (191), ● Third-party vendor raw data layer and system proprietary value layer a two-tier data ownership boundary delimiter that establishes a clear architectural distinction between them (192), 30 ● sensors in the milking line (12, 13), milk molecular analyzer interface (40), waiting tank environmental monitoring module (125), smart production boiler data node 45 (130), maturation chamber monitoring module (180), environmental sensor network (60) and all sensors including the final product spectroscopic analysis module (150) It collects data by querying data sources in a predefined order and frequency. consolidating data under milking session ID (SOK) (30) and consolidating by obtaining the cryptographic hash of the data (SHA-256, SHA-3, BLAKE3 or equivalent) 5 central scanning and acting as a single record stream to the blockchain module (80) registration server (193), ● Timestamps used by all system components; Stratum 1 GPS-disciplined oscillator (GPSDO) at the atomic reference clock level (rubidium, cesium), Galileo HAS time service or RFC 5905 standard 10 ±10 milliseconds or more from a single central source containing an NTPv4 server. Synchronized time source module (194) which is provided by precise synchronization, ● Whey is divided into standard and premium streams according to quality thresholds. segregated whey quality segregation and premium flow routing module (195), 15 ● operational parameters of each derivative product line linked to the source SOC derivative product pipeline process tracking and session ID continuity recorded as such. module (196), ● A double-layered physical security feature has been adapted to the packaging of derivative products. Multilayer packaging adapted for the derivative product using form factor 20 verification layer (197), ● Multiple end product categories from a single milking batch are produced at the same SOK (Source of Milking). Multiple product cuvée registration and verification enabling chaining under one roof. mechanism (198), ● For derivative products in which DNA integrity is preserved, the biological detection route (route a), 25 Operational identity chain for derivative products where DNA integrity is lost. Derivative product biological-operational hybrid identity chain using route (route b) module (199). Preferred Application Examples The feasibility of the system described in the invention is demonstrated with the following application examples (30). It is shown: 46 Application Example 1 — Premium Dairy Farm (Jersey Cows) Individual scale purebred Jersey cows a system implemented on a farm consisting of cows; a separate milk from each cow by transferring to individual holding tanks and individual production boilers, one cow per unit. In the context of cheese, it enables the production of high value-added artisan cheeses. It provides. In the preferred configuration of the application example in question; 5 ● Robotic milking unit (10) as Lely Astronaut A5 Next; milking data T4C It is retrieved via the REST API. The system architecture is DeLaval VMS V300. Also compatible with GEA DairyRobot R9500, BouMatic or equivalent robotic milking systems. configurable; vendor selection multiple vendor data adapter layer (190) It is independent of [the source]. 10 ● FOSS MilkoScan FT3 (FT-IR) as milk molecular analyzer interface (40) technology); final product spectroscopic analysis module (150) as FOSS FoodScan 2 Dairy (NIR technology) is used. ● Environmental sensor network (60) with Raspberry Pi based MQTT protocol is working. 15 ● Hyperledger Fabric permissioned blockchain as blockchain record module (80) It is in use; the BatchRegistry smart contract is written in Go. Quorum, Also compatible with Corda, IPFS, Arweave, or equivalent distributed ledger technologies. It is configurable. ● Regionally specific starter culture library, 20 from Çanakkale / Bayramiç region. It contains approximately 50 isolated autochthonous LAB strains; one per cow A unique combination of 5-7 strains has been assigned. ● Watson-Marlow peristaltic pump as volume-proportional dosing pump (162) It is used. ● Production boiler data node (130), 25 located inside the individual boiler Endress+Hauser CPS11D pH probe, Pt100 temperature sensor, and servo motor. It contains an encoder. ● Roche LightCycler 480 as a molecular analysis instrument interface (170) II; 24 target markers can be scanned simultaneously in a 384-well capacity. BioRad CFX, Applied Biosystems QuantStudio or CRISPR-Cas, isothermal 30 Equivalent technologies such as amplification and nanopore sequencing can also be used. 47 ● Robotic sample collection station (165), based on Universal Robots UR5 cobot It operates as a core sampling system. ● Maturation chamber monitoring module (180), for long-term maturing products It operates through monthly molecular analysis checks. ● Individual animal identity profile module (24) demographic (date of birth, 5 for each cow family tree, name), physiological baseline, medical history and visual records integrated It maintains this as the basis of the product story in consumer validation. It constitutes. ● Ear tag or as a wearable animal welfare monitoring module (22) Yoke-based SmartTag, Allflex, MooMonitor+ or equivalent sensors 10 It is used. ● Whey quality segregation modulus (195) and derivative biological- distillation of whey with operational hybrid identity chain module (199) individual animal-derived product lines for ultra-premium product lines produced via The integrity module (188) is integrated. 15 Application Example 2 — Goat Herd (Saanen Goats) A herd consisting of Saanen goats The system applied in the herd involves transforming the milk into different target products such as cheese, yogurt, and kefir. quality-based automatic pipe routing mechanism for routing (15) It involves running the system with configurable decision rules. The system is DeLaval VMS V300. Integrated with robotic milking unit (10); ML quality estimation module (18) Saanen 20 It performs baseline learning specific to the race. In this application, the system, individually Instead, it can be operated with herd-level traceability; regional starter culture combination. Applicable at herd level; molecular analysis device interface (170) GMO and feed It stands out with its source scanning function. Application Example 3 — Sheep Flock (Awassi Sheep) A flock of 25 Awassi sheep a system applied in a herd; geared towards traditional cheese and curd production It is configured. The system works with GEA DairyProQ robotic milking unit (10); ML biochemical fingerprint module (55) Awassi sheep specific lactation curve and It learns the biochemical baseline. Sustainability data calculation module (65), The EU uses herd-based metric calculations for CSRD reporting. 30 Application Example 4 — Software as a Service (SaaS) Licensing - Subject of Invention The system's core traceability architecture (SOK assignment engine, multi-vendor data adapter) 48 layer (190), external analysis identifier DAT module (84), external laboratory results reconciliation module (85), blockchain record module (80), double-layered physical security element (90), product lifecycle status manager (95); self-milking, analysis or A third party operating solely under a SaaS license without possessing laboratory equipment. The third party may submit the product to farms, dairies, processing plants and laboratories. side operator; existing robotic milking system, composition analyzer or laboratory data from the device is transmitted to the system via the multi-vendor data adapter layer (190). The loads; analysis results are cryptographically linked to the original SOK via the DAT module (84); external laboratory results reconciliation module (85) automatically matches results It works on the blockchain. 10 Scope of the Invention — Technological Breadth and Future Resilience The invention is limited to a specific trade product or technology name, provided that the elements specified in the description are included. that is not the case, cross-working alternatives in the current state of technology and in the future 15 The following scope expansion definitions have been made: (a) Artificial intelligence and machine learning based modules (18, 55, 115, 145): Invention AI and machine learning-based modules included; supervised learning algorithms, unsupervised learning algorithms, deep learning architectures (including convolutional neural networks, recurrent neural networks, and transformer architectures), Vision-20 language models (VLM), federated learning protocols, differential privacy applications, homomorphic encryption-based training, explainable artificial intelligence (XAI) methods and machine learning paradigms that may emerge in the future It is interpreted in a way that encompasses everything. (b) Blockchain and distributed ledger technologies: Blockchain record 25 within the scope of the invention module (80); public blockchains, permissioned distributed ledgers (Permissioned blockchain), corporate identity-based consortium chains, zero-knowledge proof. (zero-knowledge proof, zk-SNARK, zk-STARK, zk-rollup) based chain structures, reduced computational intensity consensus mechanisms (Proof of Stake, Practical Byzantine Fault Tolerance and equivalents) or hybrid combinations thereof 30 It is interpreted in a way that encompasses. On the data storage side; centralized server architectures, Distributed file systems (IPFS, Arweave, Filecoin and equivalents) and hybrid architectures 49 It is included within the scope of cryptographic hash algorithms such as SHA-256, SHA-3, and BLAKE3. Quantum-safe hash functions and their equivalents are included. (c) Biochemical and molecular analysis technologies (40, 150, 170): Within the scope of the invention Milk and cheese analysis instruments; Fourier transform infrared spectroscopy (FT-IR), near infrared spectroscopy (NIR), mid-infrared spectroscopy (MIR), Raman spectroscopy, 5 ultrasonic analysis, microfluidic biosensors, mass spectrometry (LC-MS, GC-MS, LC-MS-MS), nuclear magnetic resonance (NMR), hyperspectral imaging, and It includes equivalent molecular analysis techniques that may emerge in the future. Also DNA. molecular verification techniques based on; polymerase chain reaction (PCR), quantitative PCR (qPCR), digital droplet PCR (ddPCR), CRISPR-Cas based molecular detection, 10 isothermal amplification (LAMP, RPA), next-generation sequencing (NGS), nanopore sequencing and equivalent DNA-based analysis methods that may emerge in the future It is interpreted in a way that encompasses everything. (d) Consumer verification interfaces (90, 91, 92, 100, 105, 110): Dual within the scope of the invention. layered physical security element; machine-readable authentication element (91) 15 QR code, DataMatrix code, microstructured hologram, optical watermark, microscopic surface pattern and equivalent machine-readable identifiers; contactless electronic micro-verification. NFC microchip, BLE beacon, UHF RFID, in terms of element (92) cannot be physically cloned It includes the function (PUF) and equivalent non-contact electronic identifiers. The invention Consumer verification interface within the scope of; smartphones, tablets and mobile devices; 20 Augmented reality (AR) and virtual reality (VR) glasses and headsets; audio artificial intelligence intelligence assistants; smartwatches and wearable devices; and those that may emerge in the future. It can be structured to include consumer interaction platforms. (e) Animal identification and machine-to-machine communication protocols (11, 60): Invention Animal identifier within the scope of; low frequency or high frequency RFID, NFC, 25 BLE (Bluetooth Low Energy), UWB (Ultra-Wideband), LoRa, biometric identification. (including facial, retinal, and nasal pattern identification) and equivalent wireless identification technologies. It is interpreted in this way. Machine-to-machine communication between environmental sensor network (60) and system components MQTT, AMQP, CoAP, OPC-UA, HTTP / HTTPS, LoRaWAN, NB-IoT, 5G mMTC and 30 It includes equivalent protocols; the collection frequency depends on the system usage scenario. It is structured accordingly. 50 (f) Configurability of the system's traceability mode: The system within the scope of the invention; Traceability mode on an individual animal basis, animal group (e.g., lactation period, barn) traceability mode can be based on unit (race) or herd (herd) It can be run in any of three basic configurations; Configuration selection, production scale and product positioning are the basis of the system administrator 5. It can be modified via the interface. This allows the system to offer micro-scale premium options. from artisan production to large-scale industrial production, across a wide spectrum. applicable. (g) Synchronous time source module (194): Synchronous time within the scope of the invention Source: Stratum 1 level GPS-disciplined oscillator (GPSDO), atomic 10 Reference clock (rubidium, cesium), Galileo HAS (High Accuracy Service) time service. Network Time Protocol (NTPv4) server according to RFC 5905 standard, PTP IEEE 1588 Precision Time Protocol and equivalent precision time synchronization technologies It is interpreted in a way that encompasses everything. (h) Veterinary registry database integration module (19): Invention 15 Veterinary registration database integration module within the scope of; Turkish Veterinary Turkish Veterinary Medical Association (TVHB) national veterinary registration system, EU OIE-WAHIS, FAO-ADIS international veterinary registration systems, animal hospital management systems (HBYS), e-veterinary platforms, blockchain-based distributed veterinary registry 20 It is interpreted in this way. Hardware Security Layer (Trusted Execution Environment) In a preferred application of the invention, sensors in the milking line transmit signals to the production boiler. from the data node (130), from the waiting tank monitoring module (125), maturation chamber All raw 25 from the monitoring module (180) and robotic sampling station (165) Before the data undergoes cryptographic hashing and writing to the blockchain, the hardware within a Trusted Execution Environment (TEE) based on It can be processed. The TEE infrastructure in question includes Intel Software Guard Extensions (Intel SGX), ARM TrustZone, AMD Secure Encrypted Virtualization (AMD SEV), and equivalents. It can be implemented to include hardware security technologies. This allows for the Edge 30. Even if the devices are physically seized, the sensor data is processed. External interference with the memory area is prevented at the hardware level; hash 51 Data integrity, which is subjected to the signing process, is cryptographically verified before being processed into the blockchain. This is guaranteed by this approach, which protects against side-channel attacks and insider threats. It extends the system's security shield against these scenarios down to the hardware layer. Expansion of Animal Welfare Monitoring In a preferred application of the invention, veterinary record database integration 5 module (19); beyond the classical withdrawal period query, This can be expanded to include animal welfare indicators. The welfare in question... indicators; rumination time, lying down and standing up obtained from the robotic milking unit (10) pattern, stress behavior data during milking; subcutaneous, ear-attached or neck-attached 10 obtained from the module (22) of wearable animal tracking devices in the form of a collar measured body temperature, cortisol level, heart rate, activity index, rumination duration and estrus detection data; and from barn camera-based behavioral analysis systems. This data may include metrics on social interaction obtained. This information contributes to the animal's welfare score. is calculated as and associated with the milking session ID (SOK) (30) on the blockchain It is processed into module (80). This expansion is in accordance with EU animal welfare regulations 15 (Directive 98 / 58 / EC and its current revisions) pasture-fed, free-range, organic production It provides verifiable welfare reporting capabilities within the scope of its certifications; also transparent information about the animal's living conditions through the consumer verification interface It allows for the provision of information. Individual Animal Identification Profile Module Expansion 20 In a preferred application of the invention, the system provides information for each individual animal. demographic information (date of birth, parental identity, family tree, racial genetic profile), physiological baseline information (biochemical fingerprint, behavioral baseline, well-being score) medical history (history, lactation curve), medical history information (vaccination records, treatment history, breakthrough period events) and descriptive information (animal name — for example "Sarıkız" —, 25 visual records, history, production performance) under an integrated data structure The individual animal identification profile module (24) may contain the said profile, RFID (11) Upon inquiry, it can be shared with the relevant system modules and the final product consumer In its verification, it is summarized as part of the personalized product story. can be offered. This mechanism allows for premium products based on individual animals. 30 positioning (for example, "Sarıkız, a Jersey cow living in Bayramiç") 52 "produced from milk") artificially links consumer trust to a tangible animal identity. It makes it possible to verify it scientifically, not just theoretically. Environmental DNA (eDNA) Based Environmental Monitoring Extension In a preferred application of the invention, environmental monitoring and access to the maturation chamber are required. control module (180) and robotic sampling station (165); maturation chamber 5 from the air, from the surfaces, and especially from the surface of the ripening cheese rind. will sample environmental DNA (eDNA) from the layer can be expanded in this way. The eDNA samples in question are local in the maturation chamber. microbiota composition (Lactic Acid Bacteria strains, mold flora, yeast) composition, environmental bacterial profile) next-generation sequencing (NGS) or 10 Characterized by targeted 16S rRNA / ITS metabarcoding methods. The cryptographic hash of the obtained microbiota profile (SHA-256, SHA-3, BLAKE3 or equivalent), blockchain together with timestamp and milking session ID (SOK) (30) It is processed into the module (80). In this way, the "biological fingerprint" of the maturation medium is continuously recorded. This is recorded; in long-term ripening cheeses, the environment is unauthorized 15 change, transport the product or transfer it to a different ripening area In this case, an anomaly is detected through microbiota profile deviation; also, PDO / PGI "Terroir" (geographic origin, biological identity) is a scientifically based document used in registration processes. It can be presented as such. Multi-Vendor Cross-Interoperability and Vendor-Independent Data Adapter Architecture 20 Expansion In a preferred application of the invention, the system's data capture module (20) performs analytics. matching module (50), data conversion and loading layer (70), edge computing / local cache module (75) and blockchain record module (80) components The core architecture it created; 25 from third-party farm and dairy equipment. operational data vendor-independent multi-vendor data adapter layer (190) It can be configured to receive it via. The adapter layer in question (190); existing and the application of any equipment manufacturer that may emerge in the future detachable in a way that is compatible with programming interfaces (APIs) It is expandable via (pluggable) connection modules; each adapter has 30 53 The module converts the relevant vendor's data format into the system's common internal data schema. It includes a normalization layer. The adapter layer in question (190) is (i) REST-based web from robotic milking systems services, SOAP protocols, GraphQL, gRPC, OPC-UA industrial communications, proprietary milking via vendor protocols or direct database query interfaces 5 session data (animal ID, milking start and end timestamps, milked milk volume, electrical conductivity, blood / protein indicators, milking speed, individual udder (ii) milk composition data including but not limited to quarterly data); Fourier transform infrared (FT-IR), near infrared (NIR), mid- infrared (MIR), Raman spectroscopy, mass spectrometry, ultrasonic analysis, 10 microfluidic biosensor or any existing one based on an equivalent measurement principle or spectroscopic measurement data (fat, protein, etc.) from devices with subsequent technology. lactose, somatic cell count, urea, free fatty acids, casein fractions, freezing point, (including but not limited to microbial load) SQL based database queries, web service endpoints, vendor-provided SDK 15 via libraries or direct file exchange formats; (iii) environmental activity and rumination based on sensors, ear tags or collars from viewers, from barn-based video-based AI-powered behavioral analysis systems and any successor technology that performs equivalent tracking functionality such as MQTT, AMQP, CoAP, OPC-UA, HTTP / HTTPS, LoRaWAN, NB-IoT or their successor transmission methods 20 It can be configured to receive real-time telemetry through its standards. Vendor-independent cross-operability orchestration module (191); within the same enterprise Multiple robotic milking systems from different manufacturers, multiple milk compositions simultaneous operation of the analyzer and mixed environmental sensor infrastructure It allows for this. Data from all of these sources are grouped in a common internal data schema. 25 normalized and combined under the same milking session ID (SOK) (30) and a single The traceability chain is written to the blockchain module (80). In this way, the basic system Its architecture can function without exhibiting technical dependency on any single vendor; vendor when modified, when run simultaneously with multiple vendors, or when all vendors Even when integrations are terminated, the system's proprietary value generation function remains 30 It continues uninterrupted. The invention is a two-layer data ownership boundary descriptor (192) with the following two separate data It establishes a clear architectural distinction between the layers: (i) third-party vendor raw data layer 54 — produced by equipment belonging to the relevant vendor and used by the manufacturer / vendor. The raw operational data is subject to the terms of the contract, and the system processes this data. It has read-only access and cannot write to vendor systems. (ii) does not perform; (ii) system proprietary value layer — raw vendor data Derived datasets produced by normalization, milking session ID (SOK) (30) 5 The combined records obtained through matching and cross-source correlation mechanisms, Decisions produced by the quality-based automatic pipe routing mechanism (15), immutable traceability records written to distributed ledger (80), machine learning The final score generated by the base modules (18, 55, 115) and the justifiable reasoning for the decisions. These are session data generated by the consumer authentication interface. The architectural distinction in question is: 10 the system proprietary value layer, from any vendor's raw data layer that it constitutes independent intellectual property and is subject to contract or integration changes It defines that it demonstrates continuity independently. The adapter layer (190) and the cross-operability orchestration module (191) in question; It is not limited to vendor protocols existing at the time of application. The current 15 next generation transmission and protocols that can replace or complement these protocols. data exchange technologies — quantum secure transmission layers, federated learning edge-computing based data sharing, edge-computing based data preprocessing, semantic web ontologies, distributed data marketplaces, and any successor technologies that perform equivalent functions. including — can be expanded to include. 20 External Analysis Descriptor (DAT), External Laboratory Result Reconciliation and Vendor- Independent Software as a Service (SaaS) Model Architecture In a preferred application of the invention, the system can be physically provided to third-party laboratories. The samples sent are digitally linked with the laboratory results. External Analysis Descriptor (DAT) module (84) 25 which enables automatic connection and can be expanded to include an external laboratory results reconciliation module (85). The modules in question allow the system to have milking or laboratory equipment. a software service that does not require anything, based solely on core traceability architecture a vendor-independent orchestration platform that can be licensed under the SaaS (SaaS) model It forms the basis. 30 External Analysis Descriptor (DAT) module (84), to be sent to a third-party laboratory Each sample taken is cryptographically marked with a milking session ID (MSD) (30). 55 a unique identifier linked (e.g., SHA-256 summarized and abbreviated 12) It assigns a 25-digit alphanumeric code. This identifier is labeled as a barcode on the sample packaging. QR code, NFC tag, DataMatrix code or equivalent machine-readable identification element This is physically marked as a DAT assignment event, assignment timestamp, and sample. 5 along with metadata (module from which the sample was taken, quantity, type, storage conditions) The blockchain module (80) is processed cryptographically. In this way, the third party The analysis to be performed by the laboratory cannot be changed before the analysis begins. It is linked to the original SOK in the record. External laboratory results reconciliation module (85), analysis of third-party laboratory 10 that can upload the result to the system along with the relevant external analysis identifier (DAT). a standardized application programming interface (REST, GraphQL or (equivalent) provides the interface in question; microbiological analysis, heavy metal screening, antibiotic residue screening, mycotoxin screening, prion screening, allergen screening, In-depth screening of GMOs, isotopic composition analysis (e.g., geographic origin) to determine the isotope ratios of δ¹³C, δ¹⁵N, δ¹⁸O and equivalent external analysis types 15 The results can be loaded. The module uses the returned result via DAT with the original SOK (30). It matches and cryptographically verifies the compatibility, and sends the matched data to the blockchain module. (80) functions as a single traceability block. This mechanism allows the third-party laboratory to The level of security on the system is increased using cryptographic DAT without requiring manual data entry. It provides this through the natural integration of the supply chain. 20 In a preferred application of the invention, the external analysis identifier (DAT) module (84) and external laboratory results reconciliation module (85); single milking session ID (SOK) (30) Multiple samples taken from a party below multiple independent third parties scenario where the parties send the documents to the laboratory simultaneously or sequentially It has been expanded to include. In this application, a separate 25 for each sample. A unique DAT is assigned; these DATs form a DAT pool under the same original SOK. The results from each laboratory are consolidated within the (DAT pool) structure. Matched with the original SOK via DAT; all results are multi-source under the same SOK. as multi-source analysis consolidation record The blockchain module (80) is processed in a single traceability block structure. This mechanism, 30 especially in high value-added export products (e.g. PDO / PGI cheeses, (premium distilled beverages) test results from multiple independent accredited laboratories. 56 Consolidating cross-validation results under a single traceability record. It provides the opportunity. The structure in question includes the system's milking system, milk or cheese analysis equipment, or a vendor-independent solution that does not require having laboratory infrastructure It allows the establishment of an orchestration platform. In this configuration, the system has 5 operator; (i) SOK (30) assignment motor, (ii) third-party milking system adapter layer (190), (iii) external analysis descriptor (DAT) module (84), (iv) external laboratory results reconciliation module (85), (v) blockchain record module (80), (vi) two-layer data ownership border identifier (192) and (vii) double layer physical security element (90) The core architecture, consisting of its components, is implemented through a software-as-a-service (SaaS) model with third-party 10 It can license to farms, dairies, processing plants or laboratories. The licensee third party The party shall provide its own milking system, its own milk / cheese analysis equipment, and its own (or contracted) Using its external laboratory, it developed the system's core traceability architecture in-house. can operate it on its lines. The system operator, on the other hand, does not have to make any physical hardware investment. For a fee only on software services, a global, vendor-independent 15 It can provide traceability infrastructure. This vendor-independent orchestration platform connects farms, dairies, and laboratories. each actor in the retail chain invests in its own traceability architecture. It enables the creation of an integrated traceability chain without requiring manual intervention. The same At the time, the system's proprietary value layer, any vendor's hardware or 20 It is protected as intellectual property independent of software infrastructure and hardware or The laboratory operates continuously, independent of contract changes. Whey-Based Derivative Product Lines and Multi-Product Cuvée Expanding Traceability In a preferred application of the invention, quality-based automated pipe routing 25 The working principle of the mechanism (15) is; cheese, butter, yogurt or similar primary milk This can be extended to the processing of whey, a byproduct of the product's production. In this application, the whey is processed to improve the quality of the source milk session. parameters (fat percentage, protein percentage, somatic cell count, microbial load, Electrical conductivity and urea concentration carry an inherited quality score, and cheese 30 by groundwater quality segregation and premium flow redirection module (195) Based on predefined threshold values, it is automatically evaluated and at least two 57 can be subjected to segregation into separate streams: (a) standard stream — animal feed, environmental (b) premium flow — value added for discharge or generic bio-refinery applications. To be directed to derivative product lines. Segregation, automatic valve systems and This is done in real time via electronic control units and each By connecting to the blockchain module (80) with the flow decision milking session ID (SOK) (30) 5 It is processed cryptographically. Premium whey flow to numerous different value-added processing lines. It can be directed. The processing lines in question include, but are not limited to: (a) fermentation and distillation lines (for vodka, gin, whisky, brandy and other distilled alcoholic beverages) for its production); (b) fermentation-based non-alcoholic or low-alcohol beverage lines (whey-based beer, (c) protein concentration and isolation; (kefir, kombucha type functional drinks); lines (whey protein concentrate – WPC, whey protein isolate – WPI, hydrolyzed peptide (d) functional beverage lines (lactose reduced 15 (e) beverages, electrolyte drinks, rehydration products, ricotta-based drinks; confectionery, bakery and food ingredient lines (lactose syrups, demineralized whey powder, (f) baby and special nutrition product lines (humanize whey protein components, infant formula components); (g) pharmaceutical and nutraceutical component lines (lactoferrin, immunoglobulin extracts, 20 (h) cosmetic and dermocosmetic ingredient lines; (i) agriculture and livestock inputs (organic fertilizer, feed additives); (j) bio-refinery and bio-fuel lines (bioethanol, biogas, anaerobic fermentation inputs); (k) equivalent added Any existing or subsequent processing line that serves a valuable transformation function. Derivative product line process monitoring and session ID continuity module (196); 25 for each process operational parameters of the line — input volume, processing time, processing conditions (temperature, pressure, pH, type of microorganism or enzyme used), the resulting product physico-chemical properties, packaging parameters and distribution metadata — in connection with the milking session ID (SOK) (30) of the source whey batch It records in real time and processes it cryptographically into the blockchain module (80). 30 Thanks to this mechanism, a portion of the milk obtained from a single milking session is retained. the primary product (cheese, butter, yogurt or similar dairy product) and the remainder as derivatives. 58 The entire production network where whey-based products are transformed into one or more final products is a common element. It is made traceable on the identity chain. Multilayer packaging verification layer adapted for the derivative product (197); invention the double-layered physical security element (90) defined in the main system — machine- Readable verification element (91), contactless electronic microverification element 5 (92), one-time token mechanism (100) and sequential read verification session The structure containing the manager (105) — also fits the packaging of whey-based derivative products. The subject of the validation layer depends on the nature of the derivative product (liquid beverage bottle, powdered protein). packaging, cream or oily ingredient packaging, distilled alcoholic beverage bottle and equivalent (packaging forms) can be adapted in terms of form factor; however, the validation principle is 10 It remains the same: a QR code embedded in the hologram base that generates a random code on each read; The NFC chip, which was damaged in the hologram interference, is a one-time event on the blockchain. (time) consumed verification token; and the entire structure including geographic anomaly detection of the product. It confirms its originality. Multiple product cuvée registration and verification mechanism (198); a 15 of a particular milking batch a portion of it is derived from the primary dairy product, and the remaining portion is derived from one or more whey-based derivatives. If converted into a product, all the final products obtained are from the same milking session. Chains under identity (SOK) (30). The multi-product source traceability in question (multi- (product source traceability), any activity carried out by the end consumer the verification action — on the primary dairy product packaging or derivative whey-based product 20 machine-readable verification element (91) on the packaging, contactless electronic micro Reading of the verification element (92) or equivalent verification element — source milking session, and therefore individual animal identity, milking time and milk quality It allows for backward access to its parameters. Traditional food Unlike traceability systems, this involves more than 25 samples from a single batch of raw materials. This mechanism enables multiple end-product categories to share verifiable provenance. It is provided. The multi-layered verification layer (197) and the accompanying consumer The verification interface is not limited to the current technology generation. Whey-based derivative Due to their nature, these products have a long shelf life (for example, 10-30 years in collectible distillates, 30 because protein components can have a long shelf life (2-5 years), the product Verification during the period between release to sale and final consumer verification. The technology is likely to change significantly. Taking this into account, the system; 59 can replace or complement existing validation layers next-generation authentication technologies — based on quantum random number generators verification, biometric consumer authentication, DNA-based molecular labeling, on the product Spectroscopic content verification of liquid or powder, microscopic surface pattern (physical Fingerprint recognition, IoT sensor-based transport and storage anomaly detection, artificial intelligence 5 performing behavioral anomaly analysis and equivalent verification based on the function It can be configured to include any subsequent technology. Milk-Cheese-Whey Biological Chain of Identity Verification Architecture In a preferred application of the invention, the system assigns regionally specific criteria to the animal. from the injection of the starter culture combination into the milk stream at the time of milking (208 10 (processing step) starting with the final cheese, whey and, if any, the whey from the back-screening of derivative products obtained from its water through molecular analysis It establishes a biological identity chain that extends beyond the animal. This identity chain is specific to the animal. the assigned starter culture combination functions as a kind of biological digital signature It is based on; the identity of the combination injected in milking is in the blockchain module (80) 15 It is written together with SOK (30), the same as the sample taken from the final product after production. A mathematically validated milk-cheese combination when identified. The biological identity chain is thus obtained. Verification of this chain of identity through the final cheese, milk-cheese biological The identity chain verification is performed by the module (86). The module; milking 20 culture injected into the milk stream by precision dosing pump (162) at the stage By reading the combination ID from the blockchain, molecular by molecular, from the final cheese. Culture combination ID detected by the analyzer interface (170) and SOK (30) It makes a direct comparison based on the principle of "milk-cheese biological identity chain". The "verified" record is written to the blockchain; in case of discrepancy, "identity chain break" occurs. 25 An anomaly record is created. In addition, quantitative molecular concentration verification is performed. module (171), Ct (Cycle threshold) value or equivalent quantitative indicator signature It measures the density; this density value is the theoretical concentration at the time of injection. Comparison with the original product results in the scientific detection of adulteration through dilution or mixing. is done. 30 The same chain of authentication is also verified via whey. Whey biological authentication module (99); automatically obtained from whey 60 Milking with molecular analysis device interface (170) on the sample animal-specific starter culture combination injected into milk flow at this stage It enables the identification of the identity. The identified identity is identical to the original SOK (30). are matched; the match result is processed into the blockchain module (80); in case of incompatibility, "milk- An anomaly record is created for "cheese-whey biological chain break". This 5 Thanks to this mechanism, whey can be substituted from a different source or Mixing it with a different batch is scientifically detected. For derivative products where the chain is extended via whey, the derivative product is biological- The operational hybrid identity chain authentication module (199) follows two separate authentication paths: (a) For derivative products in which DNA integrity is preserved: Whey protein concentrate (WPC), 10 whey protein isolate (WPI), fermented whey beverages, ricotta, hydrolyzed peptide powders, and on equivalent production lines; the production process will preserve DNA integrity. Since this was carried out, molecular analysis was performed on a sample taken from the final product. Starter culture combination identity detection is performed with the device interface (170) and the original A one-to-one match is made with SOK (30). The result is processed into the blockchain; in case of discrepancy, 15 An anomaly record is created. (b) For derivative products where DNA integrity is lost: Distillation, ultrafiltration, DNA integrity is lost due to high heat treatment or equivalent processes derivative products (vodka, gin, whisky, brandy and equivalent distilled alcoholic beverages; purified lactose syrups; some highly processed protein components); 20 Biological detection is physically impossible. In this case, module (199) is to ensure the continuity of the operational identity chain. It implements a three-layered verification framework: (i) mass balance control module (140) Mathematical verification that it is not mixed with another batch of whey. The ratio between the inlet volume and the final distillate volume is within the theoretical distillation yield and is 25. (ii) verification that there is no sample storage chain NFC session module (128) from whey to the final distillate, all process steps (iii) cryptographic chain of custody protection; and (iii) party tracking to the blockchain module (80). and the uninterrupted continuation of the original SOK (30) connection. In both cases, the final derivative product packaging is a double-layered physical security element (90) 30 by labeling it so that consumers can trace its individual animal identity. This hybrid architecture ensures that DNA integrity is not lost after distillation. 61 Even in these cases, it is possible to keep the derivative product traceable to the correct milking session. It is the only integrated solution that makes it possible. Individual animal-derived product line integrity module (188); biologically verified a batch of whey used only in the derivative production process It enables processing in an individual / segregated production line. This line is similar to other cheeses. 5 from groundwater batches with physical valve systems and cryptographic line-batch matching It is isolated. CIP cycle verification module (126), complete cleaning during line transitions. It records the data on the blockchain. Thanks to this architecture, an individual animal can be tracked. It is ensured that only one batch of attributable derivative products is obtained; for example, a single 10 of the whey from the milk of a Jersey cow in an individual distillation line Ultra-premium products like "single cow vodka" obtained through processing are scientifically tested. It becomes verifiable. Product Lifecycle Status Manager and Scanning-Consumption Separation In a preferred application of the invention, the one-time token mechanism (100), 15 that manage the consumer validation lifecycle of the final product under at least three separate scenarios. It is run in conjunction with a product lifecycle status manager (95). The mechanism; the product is on the store shelf or in the consumer's hand, before a purchase decision is made. It first takes into account the fact that it can be scanned multiple times for verification purposes, and this "scan" It distinguishes the act of consumption from the actual act of consumption. These three situations are defined as follows: 20 (i) Active status: Product manufactured, with double-layered physical security element (90) tagged, unique token record created on blockchain module (80); However, it has not yet undergone any verification process. In this case, the product, It is considered ready to be verified by any consumer. (ii) Scanned status: The product has been scanned one or more times using non-contact electronic devices. 25 micro-verification element (92) and / or machine-readable verification element (91) This has been verified by scanning; the system scans each scan attempt using metadata (device fingerprint). The trace, GPS location, IP address, timestamp) is processed into the blockchain module (80); However, the token is not marked as depleted. In this case, the product is available to other consumers as well. It is in an accessible state where verification can be performed. 30 62 (iii) Consumed status: The product packaging has been opened or the consumer has clearly seen that it has been consumed. Proven ownership of; single-use token mechanism (100) blockchain It has been permanently set to "consumed" status. What will happen after this status... Confirmation attempts produce the response "product sold out". At least one of the following events triggers the transition to the "consumed" state: 5 must be found: ● (a) as a result of mechanical damage to the double-layered physical security element (90) inaccessibility detected by the system on the next verification attempt the signal — for example, the NFC chip being deactivated due to the hologram being peeled off. if it remains, the NFC response cannot be received on the next reading attempt, and the system fails to work for 10 seconds. interpreting this situation as "opened packaging"; ● (b) geographic location of previous verification attempts (e.g. retail) (point) at a different location (e.g., the consumer's home) and at a predefined time Verification performed outside the window — the system's location / time interpreting the jump as a post-purchase consumption event; 15 ● (c) Record received via point-of-sale terminal integration — cashier The process of scanning the product's barcode for sale is recorded in the system via the POS interface. reaching; ● (d) "purchase" explicitly made by the consumer through the verification application The statement "I received it" or "I opened it". All of these status changes are related to Blockchain 20. The module (80) is processed cryptographically and throughout the product's lifecycle It is recorded in an unalterable way. Thanks to this mechanism, in the store Verification (screening) of a product on the shelf by multiple potential consumers, It does not prevent the actual consumption of the product; at the same time, the actual consumption event Since it can be clearly marked, the protection level against counterfeiting attempts is 25. It won't fall. Due to design flexibility, different trigger events are used for different product types. Combinations can be configured; for example, (a) and (b) for distilled alcoholic beverages. sufficient triggers, (a) sufficient on their own for premium cheese products, For ultra-premium products in the collection, (d) explicit declaration is preferred. Veterinary Integrated Registry System Expansion 30 63 One preferred application of the invention is veterinary record database integration. module (19); a comprehensive beyond the classic single-drug breakthrough time inquiry The veterinary registry infrastructure has been expanded. The module in question; (a) simultaneous use of multiple drugs breakthrough time calculation sub-module, (b) veterinary electronic signature and authentication submodule, (c) treatment history recording submodule, (d) vaccination schedule integration submodule 5 It consists of module (e) quarantine / isolation status management sub-module. Multidrug concomitant breakthrough time calculation submodule; simultaneous administration to the same animal. multiple veterinary drugs (antibiotics, antiparasitics, anti-inflammatory drugs, hormones) (and similar situations) the defined breakthrough period for each drug when applied. It calculates independently; the longest of these breakthrough periods is designated as "effective breakthrough 10". It defines the "effective breakthrough period" as the waiting period for milk. tank monitoring module (125) and individual production boiler data node (130) The redirection is prevented; the milk is automatically directed to the general tank redirection valve (17) Guidance is provided. Veterinary electronic signature and authentication sub-module; practitioner 15 for each treatment event. the veterinarian's electronic signature, digital certificate, or the Turkish Veterinary Medical Association (TC) (TVHB) mandates registration with a registration number. Identity verification. Unsuccessful treatment records are not accepted into the system; successful verifications are accepted into the blockchain. The module (80) is processed by taking the cryptographic hash. Treatment history recording submodule; drug name for each treatment administered to the animal, ATC 20 code (Anatomical Therapeutic Chemical classification), application dose, application date and Route of administration (oral, parenteral, intramuscular or equivalent) information for individual animals It stores all treatment events in connection with the identity profile module (24). The identity (SOK) (30) is processed into the blockchain module (80) as reference data beforehand. The vaccination schedule integration sub-module includes the animal's vaccination history and the planned 25... It records the vaccination schedule and application status; from the planned vaccination date The system will generate an operator warning if milking occurs first. Quarantine / isolation Situation management sub-module; suspected or confirmed diagnosis of infectious disease. In this case, it manages the quarantine or isolation status of the animal; quarantine Milk from animals in this condition is automatically directed to the general tank 30. It is directed to valve (17) and the change of state is recorded on the blockchain. 64 Thanks to this expanded veterinary registry system, the EU Veterinary Medicines Regulation (Regulation EU 2019 / 6), Turkish Ministry of Agriculture and Forestry, Veterinary Medicines Regulations and Codex Alimentarius MRL (Maximum Residue Limit) requirements Compliance is verified in a verifiable manner. Closed Pipeline and Operator Physical Access Isolation Architecture 5 In a preferred application of the invention, an individual license is assigned to each individual animal. standby tank monitoring module (125) and individual production boiler data node (130) Milk transfer between them; physical intervention by the operator or a third party. through a pipeline that is closed, sealed and leakproof in such a way that it cannot be accessed This is implemented. The closed pipeline in question has 10 for each individual tank-boiler pair. It is physically separated from the lines of other animals in an exclusive way; multiple In applications involving animals, they are configured as parallel, independent lines. All access points in the closed pipeline (valve, connection port, sampling port) with an electronic lock, seal sensor, or equivalent unauthorized access detection device It is equipped with sensors that detect any unauthorized opening attempt and immediately report it. report to the central scanning and recording server (193); the relevant event is reported to the blockchain module (80) This is processed as an anomaly log, and the verification flow for the affected party is suspended. Before the milk enters the individual holding tank (125) on the individual milking line regional specific starter culture dosing unit (160), animal-culture Combination assignment module (161) and volume-proportional precision dosing pump (162) also 20 Similarly, they are isolated from operator access. These units are sealed and... It is positioned in a hygienic (sanitary) closed container; culture selection of combination, determination of dosage and injection the timing being performed exclusively automatically by the system It provides. The operator is only authorized to initiate the process; culture prescription, dosage 25 Manual intervention in the parameter or injection timing is not permitted. Thanks to this architecture, operator intervention in cheese production is structurally eliminated. The configuration obtained is such that it is prevented; the milk is directed to the wrong vat, mixing with other animal milk or manually preparing the culture recipe The alteration or counterfeiting is made physically impossible. This situation applies to cheese 30 65 the highest level of protection against human error and operator-based fraud in its production. It differs from existing technology by providing structural protection. Centralized Passive Reading Architecture and Synchronized Time Source In a preferred application of the invention, sensors in the milking line (12, 13) measure the milk molecular analysis device interface (40), individual waiting tank environmental monitoring module 5 (125), smart production boiler data node (130), maturing chamber monitoring module (180), including environmental sensor network (60) and final product spectroscopic analysis module (150) all sensor and data sources can be written directly to the blockchain module (80). to operate solely as a data publisher without authorization It is structured. 10 The system includes a single central scanning and logging server (193). This server contains all data sources in a predefined sequence and frequency (e.g., 1 during milking) once per second, every 60 seconds during production boiler processes, maturation chamber It queries the measurements (every 5 minutes); the data it collects is recorded as Milking Session Identifier (MSI). (30) consolidates the consolidated data under; cryptographic hash of consolidated data (SHA-256, SHA-3, 15 It processes the blockchain module (80) as a single record stream by taking BLAKE3 or equivalent. Thanks to this architecture, any sensor cannot be physically destroyed, Manipulating or altering it does not affect blockchain integrity; because nothing The sensor does not have direct blockchain writing authority. An attacker could gain access to a single sensor. Even if it passes, the cross-consistency checks of the central scanning and logging server 20 (e.g., consistency of milking volume with holding tank level change; production boiler thermal) It detects anomalies (consistency between process temperature and ambient temperature). Timestamps used by all system components; a single central point. The time in question is provided by the synchronous time source module (194). Source: Stratum 1 level GPS-disciplined oscillator (GPSDO), atomic 25 Reference time (rubidium or cesium), or Network Time according to RFC 5905 standard. Includes Protocol (NTPv4) server. All components are sourced from that source ±10 It takes milliseconds or more precise synchronization to get the time. Thanks to this synchronized time source, different components of the system The chronological order of incoming events can be verified cryptographically; for example, milking 30 session identity generation occurs before starter culture dosing, production 66 the milking process begins after the milking is complete and the final product labeling all verifications were done chronologically on the blockchain. It becomes verifiable. When a synchronization deviation is detected, the system automatically It creates an anomaly log and suspends the verification flow.

Claims

67 REQUESTS 1. The invention relates to dairy farming, food traceability, distributed ledger technology (blockchain), and In the field of multi-layered physical-digital product safety, milking is done on an individual dairy animal basis. data collection, automated pipe routing based on milk quality, biochemical analysis, and 5. Regarding the integrated integration of blockchain-based fraud prevention systems. any of the following milk-producing mammals: cows, sheep, goats, buffaloes, camels, and other dairy animals applicable to anyone, regardless of race or gender; ● via application programming interface (REST, GraphQL, gRPC or equivalent) robotic milking unit that was questioned (10), ● Electronic identifier that uniquely identifies the animal (RFID, NFC, BLE, 10 UWB, LoRa, biometric identification, or equivalent wireless pet identification. technology) (11), ● milking line electrical conductivity sensor (13), ● milk composition parameters (fat, protein, lactose, somatic cell count, urea, measuring freezing point and equivalent biochemical parameters) and FT-IR, MIR, 15 NIR, Raman spectroscopy, ultrasonic analysis, microfluidic biosensors, or milk using any of the equivalent milk biochemistry analysis technologies It is a system containing a molecular analysis device interface (40): ● As a rule engine that evaluates real-time sensor data during milking; suitable or individual tank diverter valve (16), if not suitable, general tank 20 Quality-based automatic pipe routing that opens the diverting valve (17) mechanism (15), ● individual tank diverting valve opened in the "appropriate" decision of the mechanism (15) (16), ● General tank redirection opened in the decision of the mechanism (15) "not suitable" 25 valve (17), ● Data that queries the robotic milking unit via the application programming interface capture module (20), ● Milking session ID (SOK) (30) assigned to each milking session, ● Analytical matching module that matches lab results based on SOK (50), 30 68 ● Raw data is processed using cryptographic hash algorithms (SHA-256, SHA-3, BLAKE3, quantum-secure hash functions or equivalent cryptographic hashers) Signing data transformation and loading layer (ETL) (70), ● BatchRegistry or equivalent batch record-based smart contract with cryptographic capabilities Blockchain record module (80) that processes the summary and metadata onto the chain, 5 ● Machine-readable authentication element (91) — QR code, DataMatrix, hologram, optical watermark, microscopic surface pattern or equivalent machine-readable including the identifier — and the non-contact electronic microverification element (92) — NFC chip, BLE beacon, UHF RFID, physically clonable function (PUF) or equivalent contactless electronic identifier including — mechanical 10 a double-layered physical security element with integration (90); the said machine-readable element of contactless electronic micro-verification (92) structurally integrated under the verification element (91) and machine- Readable verification element remains mechanically intact without being touched. 15 ● The only one marked as "consumed" on the blockchain upon the first successful verification token mechanism for use (100), ● verification attempt using IP address and satellite location data (GPS, Galileo, GLONASS, Beidou or equivalent) recording verification and security module (110) is characterized by its inclusion. 20 2. A system that complies with Claim 1, and whose feature is that it measures the instantaneous milk flow rate for each teat. It includes a nipple flowmeter (12).

3. A system that complies with Claim 1, and whose features include MQTT, AMQP, CoAP, OPC-UA or Equivalent machine-to-machine communication protocol to monitor barn internal environmental parameters (temperature, humidity, pressure, CO2 levels, air quality, lighting) and external meteorological 25 Collecting parameters (temperature, humidity, pressure, wind, precipitation) 24 / 7 without interruption; by temporally matching the collected data with the milking session ID (SOK) (30) The blockchain module (80) includes an environmental sensor network (60) that processes raw data.

4. A system that complies with Claim 1, characterized by being trained on historical milking data, federated learning or equivalent data-privacy-protecting machine learning protocol 30 (differential secrecy, homomorphic encryption-based training, etc.) data from multiple farms. can learn the cheese production suitability score probabilistically while maintaining confidentiality. 69 calculating and outputting quality based automatic pipe routing mechanism (15) It includes a transmitted machine learning-based quality prediction module (18).

5. A system that conforms to Claim 1, characterized by its historical biochemical data specific to each animal. The result of the instant milk molecular analyzer interface (40) trained on the profile A threshold 5 system calculates the probability that the milk belongs to the animal by comparing it to a past baseline. A machine learning-based biochemical fingerprint module that generates alerts based on six probabilities. (55) is included.

6. A system that conforms to Claim 1, and whose feature is the patterns of validation attempts. It analyzes through unsupervised learning and can adapt to new fraud methods. It includes a machine learning-based behavioral anomaly detection module (115). 10 7. It is a system that complies with Claim 1, and its feature is a one-time token mechanism (100). integrated working; touchless electronic micro-verification element (92) and machine- readable validation element (91) sequentially and in the same validation session a device that generates a limited-time session token that allows it to be read. fingerprint (device fingerprint), satellite location data, IP address and timestamp with 15 Signed by; both readings in the same session, from the same device, from the same location and session Sequential read validation that cryptographically verifies that it occurred without exceeding the time limit. It includes a session manager (105).

8. It is a system compliant with Claim 1, and its feature is that it is integrated with a veterinary record database. The withdrawal period (withdrawal 20) for animals undergoing antibiotic or hormone treatment. (period) information is queried; during the breakthrough period, milk is automatically transferred to the general tank. redirection to the redirection valve (17) and the status code to the blockchain Veterinary record database integration module (19) that enables recording It includes.

9. A system that complies with Claim 1, and whose features include environmental sensor data and milking 25 Carbon footprint, water consumption, energy usage and batch-based parameters Methane emission values ​​are calculated in accordance with the EU CSRD / CBAM regulations. Sustainability data that enables verifiable sustainability reporting. It includes the calculation module (65).

10. A system that complies with Claim 1, and whose feature is that all milking data, quality decisions, 30 Blockchain hashes and verification logs are kept redundant for the regulatory period. It includes a forensic expert evidence storage module (120) that archives the evidence in this way. 70 11. A system compliant with Claim 1, characterized by quality-based automatic pipe routing. mechanism (15); cheese, butter, cream, yogurt, kefir, ayran, curd, ice cream, milk for all derivative products produced from powder and milk raw materials, according to product type. Configurable quality thresholds (fat percentage, protein percentage, somatic cell count (SCC)) It is structured to work with spectroscopic profile. 5 12. It is a system that complies with Claim 1, and its feature is that it can function when the internet connection is interrupted. In these cases, the connection caches the data locally in a cryptographically signed format; Edge computing that automatically synchronizes to the blockchain network when it is re-established. It includes a local cache module (75).

13. A system that complies with Claim 1, and whose characteristic is that it is autochthonous, specific to the production location. isolated from microflora and listed in the EFSA QPS (Qualified Presumption of Safety) list. unique strains created from the Lactic Acid Bacteria (LAB) found in the region. including a library of combinations; improving sensory characteristics in the final product and The primary purpose of fermentation technological function is to use regionally specific starters. It includes a culture dosing unit (160). 15 14. It is a system in accordance with Claim 48, and its feature is that each milking animal has a central module. Assigning a unique LAB combination based on RFID (11) data; RFID during milking animal-culture combination that calls up the combination assigned to the animal upon querying instantaneous milk volume from the assignment module (161) and the flowmeter (12) during milking. By taking the data as input, the culture combination assigned to the animal is individually measured in milk. Instantaneous milk transfer onto the pipeline before entering the tank, without human intervention. Volume-proportional precision dosing pump that automatically doses in proportion to its volume (162) It includes.

15. A system that complies with Claim 1, characterized by the individual animal being kept in a holding tank at +4°C. Temperature, lid opening log and 25 during approximately 24 hours of waiting period at the temperature. It monitors the duration of the process; it automatically detects temperature deviations or unauthorized lid opening. The tank is marked "ready for production" when the daily milking is complete, creating an anomaly record. The waiting tank that switches to this state contains an environmental monitoring module (125).

16. This is a system compliant with Request 15, characterized by a waiting period between successive milkings. Clean-in-place cycle of the tank, conductivity, temperature and time 30 measuring parameters; when insufficient or improper cleaning is detected, the tank is labeled "appropriate". 71 and cross-contamination risk to the blockchain module (80) The functioning holding tank contains the CIP cycle verification module (126).

17. It is a system that conforms to Claim 1, and its characteristic feature is that the cheese is produced by a cheese master (operator). RFID, NFC, and biometric identification (fingerprint, facial recognition) are used to initiate the process. 5 of the authentication elements include iris scanning or mobile device QR code-based authentication. verifying identity with anyone; checking operator authorization status. the operator signature and the start timestamp are entered into the blockchain module (80) Cryptographically operated operator authentication and badge management module (127) is included.

18. A system conforming to Claim 1, characterized by a pH probe inside the production vessel, 10 temperature sensor (Pt100, Pt1000, thermistor or equivalent) and mixing speed encoder It collects data at predefined intervals (e.g., every 60 seconds); recording the fermentation moment timestamp; data is cryptographically hashed (SHA-256, Smart blockchain module (80) that processes by signing with SHA-3, BLAKE3 or equivalent) It contains the production boiler data node (130). 15 19. A system conforming to claim 18, characterized by its boiler curve (pH rate of change, thermal process profile) raw material milk with milk molecular analyzer interface (40) profile Checking compliance within a predefined tolerance band; detecting deviations. It includes a prescription compliance verification module (135) which suspends the verification flow.

20. It is a system that complies with Claim 1, and its feature is that the total milk recorded during milking is 20. calculating the ratio between the input volume and the final cheese mass obtained; this ratio comparing it to the scientifically determined theoretical upper yield limit for the raw material milk type; Mass balance that creates an anomaly record of "yield fraud" if the limit is exceeded. It includes the control module (140).

21. It is a system that complies with Claim 1, and its feature is that it excludes non-boiler process steps (telemen 25 (Production, molding, pressing, brining) continuously recorded with multiple cameras; AI-based process anomaly detection algorithms (convolutional neural networks, Transformer-based visual models (vision transformer or equivalent) through the process automatic detection of deviations; processing of image hashes into blockchain module (80) The production line includes a vision monitoring module (145). 30 22. It is a system that complies with Claim 1, and its characteristic feature is that it determines the compositional parameters of the final cheese (fat, (measuring protein, moisture, total solids, ash and equivalent parameters) and NIR, FT-IR, 72 MIR, Raman, hyperspectral imaging, ultrasound, mass spectrometry, or equivalent. using any of the cheese composition analysis technologies; measured values Expected ratio of raw material milk to the interface profile of the molecular analysis device (40) compares within a relationship; suspends the verification flow upon detection of discrepancies. The final product includes a spectroscopic analysis module (150). 5 23. A system conforming to Claim 1, characterized by its holding tank, production boiler and final autonomously sampling cheese (core sampling, Trier sampler, automatic) (including pipetting or equivalent autonomous sampling techniques) field; milk molecular analysis device interface (40), final product spectroscopic analysis module (150) and molecular Robotic 10 that automatically distributes to molecular analysis device interface (170) devices It includes sampling stations (165).

24. A system in accordance with Claim 23, characterized by a time stamp assigned to the sample taken. A chain of custody session was established between the sample and the analysis devices via an NFC tag. locking; compatibility of NFC tag with SOK (30) upon entry of sample into the analysis device inspector; by preventing the initiation of analysis in case of discrepancy, fake sample 15 The sample storage chain that prevents its insertion is that it includes an NFC session module (128).

25. A system that conforms to claim 1, and whose characteristic is that, in a single reaction; (i) to the animal (i) assigned regional specific starter culture combination identifier, (ii) GMO markers (Including CaMV 35S promoter, NOS terminator, MON810, Roundup Ready soy) (iii) feed source plant DNA signature (Zea 20 (iv) animal breed genetics (including mays, Glycine max, pasture grass panel), and (iv) animal breed genetics simultaneous screening of markers (including mtDNA, race-specific SNP panels); polymerase chain reaction (PCR), digital PCR (dPCR), CRISPR-Cas based molecular detection, isothermal amplification (LAMP, RPA), nanopore sequencing or equivalent Molecular analysis device using time-based multi-target molecular screening technology 25 It includes the interface (170).

26. A system conforming to claim 25, characterized by being a molecular analysis device. The Ct (Cycle threshold) value or equivalent quantitative output on the interface (170) Measuring the intensity of the starter culture signature through indicator analysis; comparing milk with other milk. If diluted or mixed, the density value will be 30% outside the expected range. Quantitative molecular concentration that detects counterfeiting based on deviations from the norm. It includes the verification module (171). 73 27. It is a system that complies with Claim 1, and its feature is the interface of the milk molecular analyzer (40), final product spectroscopic analysis module (150), molecular analysis device interface (170), quantitative molecular concentration verification module (171), mass balance (140) and prescription compliance verification module (135) verifications If successful, machine-readable verification element (91) and touchless 5 electronic micro-verification element (92) allowing label production; any If verification fails, it autonomously stops the tagging pipeline and Automated tag generation that processes the "non-compliant party" record into the blockchain module (80). It contains the control module (175).

28. A system conforming to Claim 1, characterized by temperature, humidity and 10 in the ripening chamber. Continuously monitoring carbon dioxide levels; ID badge (RFID, NFC, BLE), biometric Identification (fingerprint, face, iris), mobile device QR code or equivalent access verification. element-based room entry and exit logs; recording each product within the room. Robotic sampling of long-term ripening cheeses that track their position. coordinating monthly random molecular analysis survey with station (165) 15 The maturation chamber includes an environmental monitoring and access control module (180).

29. It is a system that complies with Claim 1, and its feature is that it can be optionally included in the final product packaging. integrated, detects temperature fluctuations in the shipping process and the consumer It includes a cold chain tracking module (185) that gives a flag during verification.

30. A system that complies with Claim 1, and whose feature is the automatic extraction of 20 from whey. Milking with molecular analysis device interface (170) on the sample animal-specific starter culture combination injected into milk flow during this stage Identification of the identity; identification of the original milking session ID (SOK) (30) one-to-one matching; processing the matching result into the blockchain module (80) and In case of incompatibility, "break in the biological identity chain of milk-cheese-whey" 25 Whey bioidentification characterized by the creation of an anomaly record. It contains the verification module (99).

31. A system in accordance with Claim 30, characterized by being a biologically identified cheese. To protect the chain of identity in derivative products produced from the water source batch. (a) in derivative products where DNA integrity is preserved (whey 30 protein concentrate, whey protein isolate, fermented whey drinks, ricotta, hydrolyzed (including peptide powders and equivalent lines), molecular analysis of a sample taken from the final product. 74 Identification of starter culture combination identity with molecular analysis device interface (170) (b) DNA application and one-to-one matching with the original SOK (30); in derivative products where integrity is lost (distillation, ultrafiltration, high heat treatment) (including vodka, gin, whisky, brandy and equivalent distilled alcoholic beverages), Instead of biological detection; mass balance control module (140) with other whey 5 Mathematical verification of no adulteration with the batch, sample retention chain Cryptographic chain of custody protection and blockchain with NFC session module (128) uninterrupted continuation of the original SOK (30) connection with the part tracking of the module (80); In both cases, the final derivative product packaging has a double-layered physical security element. (90) by labeling, enabling consumers to access the individual animal's identity retrospectively. providing derivative product biological-operational hybrid chain authentication module (199) It includes.

32. A system in accordance with Claim 31, characterized by being a biologically identified cheese. The water batch that works exclusively with that batch in the derivative production process. processed in an individual / segregated production line; the other whey of the said line 15 isolated from their batches by physical valve systems and cryptographic line-batch matching; Full cleaning of the CIP cycle verification module (126) during line transitions. that records are entered into the blockchain; thanks to this architecture, an individual animal can be tracked individual where the obtaining of a single attributable batch of derivative products is guaranteed It includes the animal-derived product line integrity module (188). 20 33. It is a system compliant with Claim 1, characterized by its single-use token mechanism. (100); consumer validation life cycle of the product under at least three separate cases being structured in a governing manner: (i) "active" status — the product has been produced and (ii) labeled, not yet verified; (ii) "browsed" status — the product is or multiple contactless electronic microverification elements (92) and / or 25 The machine-readable validation element (91) was validated by reading it, but it was consumed. (iii) not marked as "consumed" — the product packaging has been opened or proven to be owned by the consumer, permanently registered on the blockchain Marked; containing at least one of the events that trigger the transition to the consumed state: (a) pair Subsequent verification 30 as a result of mechanical destruction of the layered physical security element (90). (b) previous verification signal detected by the system during the attempt their initiatives in a location different from the geographical location and at a predefined time Verification performed outside the window, (c) point of sale terminal 75 The record received via integration, (d) the "purchase" explicitly made by the consumer. The statement "I received / opened" indicates that all of these status changes have been recorded in the blockchain module. (80) Product life cycle characterized by cryptographic processing (297) It includes the status manager (95).

34. A system compliant with Claim 33, its feature is veterinary record database integration 5 module (19); multiple veterinary drugs to the same animal at the same time (antibiotics, antiparasitic, anti-inflammatory, hormone and similar) administered in these cases; independently calculating the defined breakthrough period for each drug; defining the longest of these breakthrough periods as the "effective breakthrough period"; The milk is automatically directed to the general tank until the effective breakthrough period ends. 10 Multidrug break-up time calculation submodule that enables directing to valve (17) It includes.

35. A system compliant with Claim 33, characterized by its integration with a veterinary records database. module (19); name of the drug, dose of each treatment applied to the animal, Date of administration, route of administration (oral, parenteral, intramuscular or equivalent), and treatment duration. 15 Authentication of the veterinarian's identity (electronic signature, digital certificate, Turkish Republic Identity Number) Veterinary Surgeons Association registration number or equivalent) that records; all treatment milking events, vaccination records and quarantine / isolation status changes Session ID (SOK) (30) as reference data to the blockchain module (80) It operates cryptographically; in case of quarantine or isolation, the column automatically increases to 20. redirection to the general tank diverting valve (17) and reporting of the situation to the blockchain treatment history and veterinary electronic signature sub-module that enables recording. It includes.

36. It is a system that complies with Claim 1, and its characteristic feature is that it is sent to a third-party laboratory. The sample taken is cryptographically marked with the milking session ID (SOK) (30) 25 assigning a unique external analysis identifier (DAT) to the linked; The identifier is placed on the sample packaging using a barcode, QR code, NFC tag, or equivalent machine. an external analytical identifier that physically marks a legible identification element. It contains the (DAT) module (84).

37. A system that complies with Claim 36, the feature of which is that a third-party laboratory performs the analysis. 30 can upload the result to the system along with the relevant external analysis identifier (DAT). standardized interface; match the returned result with the original SOK (30) via DAT 76 cryptographically verifying the match and sending the matched data to the blockchain module (80) External laboratory results reconciliation module (85) which functions as a traceability block It includes.

38. In the field of dairy farming, food traceability and distributed ledger technology; milking Session ID (SOK) (30) assignment engine, third-party milking system adapter layer 5 (190), external analysis identifier (DAT) module (84), external laboratory results reconciliation module (85), blockchain record module (80), two-layer data ownership boundary descriptor (192) and containing a double-layered physical security element (90); third-party robotics milking systems, third-party milk or cheese analysis equipment, and third-party matching data from laboratories on the basis of SOC (30) single traceability chain 10 composed of; the system operator having the aforementioned milking and analysis equipment. without which the core architecture in question can be implemented by a third party using a software as a service (SaaS) model. vendor-independent licenses that can be granted to farms, dairies, processing plants, or laboratories. A system characterized by its orchestration platform.

39. A system in accordance with Claim 38, characterized by being a byproduct of primary dairy production. The whey, which is a quality inherited from the source milking session. according to its parameters (fat, protein, somatic cell count, microbial load, conductivity) evaluating and creating a quality score; according to that score, the whey Based on predefined thresholds, at least two separate flows (standard flow: feed, bio- refinery, environmental discharge; premium flow: value-added derivative product lines) automatic valve 20 segregating each flow decision through the system with SOK (30) by connecting the blockchain module (80) to the cryptographically processed whey quality It includes segregation and premium flow routing module (195).

40. A system in accordance with claim 39, characterized by its derivatives obtained from whey. product lines (fermentation and distillation lines, protein concentration and 25 isolation lines, functional beverage lines, confectionery and food ingredient lines, baby and specialized nutritional product lines, pharmaceutical and nutraceutical ingredient lines, cosmetics component lines, agricultural and livestock input lines, bio-refinery lines and equivalent added value (including but not limited to valuable conversion lines) operational parameters — input volume, processing time, processing conditions (temperature, 30 pressure, pH, microorganisms or enzymes used), physicochemical properties of the final product. characteristics and packaging metadata — source whey batch SOK (30) real-time recording and blockchain module (80) in connection with 77 Cryptographically controlled derivative product pipeline process tracking and session ID continuity module. (196) is included.

41. A system in accordance with Claim 39, the characteristic of which is obtained from a specific milking session. A portion of the milk is used for the primary dairy product, and the remainder for one or more whey products. If all the final products obtained are converted into a water-based derivative product, then the same 5 Chaining under SOK (30); primary product or derivative product by final consumer Both products, upon scanning any verification element on their packaging... the source can trace back to the milking session, and therefore to the individual animal identity. It includes a multi-product cuvée registration and verification mechanism (198).

42. A system that complies with Claim 38, characterized by its continuous monitoring of the animal and 10 animal activity level, rumination time, body temperature, estrus status, resting position- wearable device that measures take-off number and equivalent physiological and behavioral parameters animal monitoring module (22); data obtained from the said device during milking sessions animal operating in blockchain module (80) connected with its identity (SOK) (30) It includes a welfare monitoring module (22). 15 43. A system in accordance with Claim 38, characterized by its demographic data for each individual animal. (date of birth, parental identity, family tree), physiological baseline (biochemical fingerprint, behavioral baseline, well-being score), medical history (vaccination, treatment records, breakthrough period) (history) and descriptive (visual records, name, history) data integrated The holder; upon RFID (11) query of the said profile, 20 to the relevant system modules shareable and summarized for consumer review during final product validation. It includes an individual animal identification profile module (24).

44. This is a system compliant with Claim 38, characterized by precise dosing during the milking phase. injected into the milk flow by the pump (162) and recorded on the blockchain regionally specific starter culture combination identity; molecular 25 from the final cheese. starter culture combination identity determined by molecular analyzer interface (170) matching one-to-one based on milking session ID (SOK) (30); matching success or by cryptographically verifying its incompatibility to the blockchain module (80) functioning; in case of incompatibility, it creates an anomaly record of "milk-cheese chain of identity break". It includes a milk-cheese biological chain authentication module (86). 30 45. A system in accordance with claim 38, whose feature is sensors in the milking line (12, 13), milk molecular analysis device interface (40), waiting tank monitoring module (125), smart production 78 boiler data node (130), maturation chamber monitoring module (180), environmental sensor all sensors including network (60) and final product spectroscopic analysis module (150) and data sources without the authority to write directly to the blockchain module (80) configured to operate solely as a data publisher. the system includes a single central scanning and logging server (193); the 5 in question central scanning and recording server (193) pre-records all data sources. The milking session ID collects data by querying in a defined order and frequency. (SOK) (30) consolidate under; cryptographic hash of consolidated data (SHA-256, SHA-3, BLAKE3 or equivalent) blockchain as a single record stream processing into the module (80); thanks to this architecture, any sensor or data 10 the direct destruction or manipulation of the source of the blockchain A central passive reading architecture characterized by not affecting its integrity.

46. ​​A system that complies with Claim 38, characterized by the fact that all system components (10, 20, 30, 40, timestamps used by (80, 125, 127, 130, 165, 170, 180, 105); GPS-disciplined oscillator at stratum 1 level (GPS-disciplined oscillator, 15 GPSDO), atomic reference clock (rubidium, cesium), Galileo HAS (High Accuracy (Time Service) or Network Time Protocol (NTPv4) according to RFC 5905 standard by a single central synchronized time source module (194) containing the server that all components are supplied from the source within ±10 milliseconds or more. It takes time for synchronization; when a synchronization deviation is detected, the system 20 suspending the verification flow by automatically creating an anomaly log; Thanks to time synchronization, all blockchain records are displayed chronologically. central synchronous time characterized by its verifiable sequencing The source module includes it.

47. A system that complies with Claim 38, and whose characteristic is the external analysis identifier (DAT) 25 module (84); taken from a batch under a single milking session ID (SOK) (30) multiple samples simultaneously to multiple independent third-party laboratories or if sent consecutively; a separate unique sample for each sample. The person assigning the DATs puts the said DATs into a "DAT pool" (DAT) under the same original SOK (30). consolidating the results from each laboratory within a pool structure; external 30 original SOK via the relevant DAT by the laboratory results reconciliation module (85) Matching with; consolidation of all results under the same SOC (Source-Based Analysis) multi-source analysis. The record is processed in the blockchain module (80) in a single traceability block structure. 79 a multi-laboratory DAT pool consolidation mechanism characterized by It includes.

48. The invention is realized by means of a system described in claims 1-47; ● robotic milking unit (10), RFID (11), data capture module (20) and SOK (30) 5 with, individual animal data via the interface of the robotic milking unit Automatic capture and assignment of unique SOK (30) (200), ● with the milk molecular analyzer interface (40); milk from the same milking session processing of the sample in a biochemical analysis device (220), containing It is a method, and its characteristic is 10 ● conductivity sensor (13), quality guidance mechanism (15), individual tank with valve (16), general tank valve (17) and blockchain module (80); column Automatic pipe routing to individual or general tank (210), ● with milking session ID (30), analytical matching module (50) and ETL (70); milking Matching the analysis results with the data on the basis of SOC (230), 15 ● With ETL (70) and blockchain registry module (80); distributed matching data packet recording in the ledger and creating an unchangeable record (240), ● double-layered physical security element (90), machine-readable verification element (91) and with a touchless electronic micro-verification element (92); double layer Implementation of physical security element (250), 20 ● Sequential Read Verification Session Manager (105), One-Time Use Token mechanism (100), verification and security module (110); consumer during verification of the touchless electronic microverification element (92) The session token is initiated by reading it, within a limited time frame on the machine. Reading the readable verification element (91) with the same device, both pieces of information are one 25 the message is sent to the blockchain record module (80) and the session duration cryptographic verification that it has not been breached (260), transaction steps It includes.

49. A method consistent with Claim 48, characterized by the fact that simultaneous occurrence is physically impossible. It includes the location detection (261) process step. 30 80 50. A method compliant with Claim 48, characterized by the generation and distribution of fraud warnings. Writing a warning entry in the ledger involves the process step (262).

51. A method compliant with Claim 48, characterized by its machine learning-based quality estimation. Probabilistic calculation of cheese production suitability score with module (18) (215) It includes the process step. 5 52. A method that complies with Claim 48, characterized by its machine learning-based biochemical capabilities. Probabilistic verification of milk source with fingerprint module (55) (225) process step It includes.

53. A method that complies with Claim 48, characterized by its machine learning-based behavioral approach. Analysis of the verification attempt pattern (265) with the anomaly detection module (115) process 10 It includes the step.

54. This is a method compliant with Claim 48, and its feature is veterinary record database integration. Checking whether the animal is in the expulsion period by querying module (19) (205) is that it includes the process step.

55. This is a method compliant with Claim 48, and its feature is the sustainability data calculation module 15. Calculation of carbon, water, energy and methane values ​​on a batch basis (235) (65) It includes the process step.

56. A method in accordance with Request 48, its feature is the forensic expert evidence storage module (120) (270) process of archiving all data in a redundant manner for the period required by legislation. It includes step 20.

57. This is a method that conforms to claim 48, and its feature is the edge computing / local caching module. (75) local caching of data and connection in case of internet connection interruption (245) process of automatically synchronizing to the blockchain network when it is re-established It includes the step.

58. A method consistent with claim 48, its feature being sequential read validation session 25 with manager (105) and one-time token mechanism (100); consumer verification during the reading of the touchless electronic microverification element (92) Session token initiation and machine-readable verification within a limited time period. (91) includes reading (255) with the same device.

59. A method conforming to claim 48, characterized by its microstructured machine-readable 30 The verification element (91) is batch-specific on the verification surface of the final product packaging. 81 one-time token mechanism (100) information is embedded and each reading the implementation will generate a randomly changing verification code in the attempt (251) is included.

60. This is a method compliant with Claim 48, characterized by its contactless electronic microverification. element (92), under the machine-readable verification element (91); label 5 structurally integrated in such a way that peeling it off permanently disables the element. (252) 61. This is a method consistent with Claim 48, and its characteristic feature is the assignment of animal-culture combinations. Querying the module (161) with RFID (11) data and the unique one assigned to the animal Calling the regional starter culture combination from the central module (202) operation 10 It includes the step.

62. A method that complies with Claim 43, characterized by instantaneous milk yield measured during milking. by the precision dosing pump (162) in proportion to its volume (flowmeter 12 data) Automatic injection of regional starter culture combination into the milk flow and The injection event is a cryptographic 15 to the blockchain record module (80) together with SOK (30). (208) includes the processing step.

63. This is a method in accordance with claim 48, the characteristic of which is that the milk is placed in individual holding tanks. After transfer, the waiting tank environmental monitoring module (125) temperature is +4°C fixing check, lid opening log and 24-hour waiting time counter It automatically starts up in case of temperature deviation or unauthorized lid opening. The process involves creating an anomaly record (212).

64. This is a method in accordance with Claim 48, and its characteristic feature is that after the daily milking process is completed. then the tank monitoring module (125) puts the tank in the "ready for production" state passing (218) and cheese master's (operator's) badge verification from module (127) RFID, NFC, biometric or mobile QR code based identification 25 with verification, it initiates the production process and the operator's signature is entered into the blockchain module. (80) recording includes (222) process steps.

65. This is a method compliant with Claim 48, and its characteristic feature is the intelligent manufacturing boiler data node. (130) pH probe, temperature sensor and stirring speed encoder data By reading at predefined intervals (e.g., every 60 seconds), the cryptographic hash 30 receiving and processing into the blockchain record module (80); simultaneously prescription compliance verification module (135) win curve raw material milk molecular analyzer 82 check the compatibility of the interface (40) profile and deviation outside the tolerance band suspending the verification flow involves the process step (232).

66. This is a method compliant with Claim 48, and its characteristic feature is the production line image monitoring module. (145) recording the non-boiler process steps with multiple cameras, artificial intelligence Process-based anomaly detection application and image hashes transferred to blockchain module 5 (80) processing involves (236) steps.

67. This is a method in accordance with claim 48, the characteristic of which is that the cheese production is completed. then the robotic sampling station (165) autonomously takes samples from the final product taking a sample, sample storage chain NFC session module (128) Time-stamped NFC tagging and automatic transfer to analysis devices (268) 10 It includes the process step.

68. This is a method in accordance with Claim 48, the characteristic of which is the spectroscopic analysis of the sample into the final product. The processing in the analysis module (150) and the resulting fat, protein, moisture and total solids the raw material values ​​of the milk molecular analysis instrument interface (40) profile Comparison; suspension of verification flow in case of spectral signature mismatch 15 (272) is the process step.

69. This is a method in accordance with Claim 48, characterized by its molecular analysis of the sample. Starter culture combination identity in a single reaction with device interface (170), GMO markers, feed source plant DNA signature and animal breed genetic markers are equivalent. 20 with timed scanning and quantitative molecular concentration verification module (171) Detecting dilution / mixing forgery by measuring signature density. (276) is the process step.

70. A method in accordance with claim 48, the feature of which is the mass balance control module (140) The total volume of milk recorded during milking versus the mass of the final cheese produced. Calculating the ratio between them and the theoretical upper limit of yield for the raw material milk type is 25. Checking whether it is included (280) is the process step.

71. A method that complies with claim 48, and its feature is the interface of the milk molecular analyzer (40), final product spectroscopic analysis module (150), molecular analysis device interface (170), quantitative molecular concentration verification module (171), mass balance control module (140) and prescription compliance verification module (135) 30 holistic evaluation of their validations in the analytical matching module (50); all If the verifications are successful, the automatic label production control module (175) 83 Machine-readable verification element (91) + contactless electronic microverification element (92) allows label production; otherwise the label line must operate autonomously. stopping and processing of the "non-compliant party" record into the blockchain module (80) (284) It includes the process step.

72. A method in accordance with claim 48, characterized by the ripening of the labeled product. transfer to the room and maturation room environmental monitoring module (180) product- It includes the process step of initiating tracking with location matching (288).

73. A method in accordance with claim 71, characterized by its temperature throughout the maturation period, humidity, carbon dioxide and room entry-exit log to the continuous blockchain module (80) Robotic sampling at specific intervals in synchronous and long-term ripening cheeses 10 molecular analysis device of station (165) by random sampling Performing identity chain verification with the interface (170) step (292) It includes.

74. This is a method compliant with Claim 66, and its feature is operator authentication and badge presentation. management module (127); biometric authentication (fingerprint, face recognition or iris 15 scanning), RFID / NFC badge verification and personal identification number (PIN) Multi-factor authentication requires that at least two of these verification criteria be provided simultaneously. configured to work with a multi-factor authentication protocol It is the fact that.

75. A method in accordance with claim 71, characterized by the fact that the molecular analysis instrument interface is 20 (170); provides basis for verifying the geographical origin of the feed source plant DNA signature. maize (Zea mays), soybeans (Glycine max), pasture grasses (Festuca, Trifolium, To identify regional genetic markers of Lolium and other animal feed components. It is structured in such a way that the said structure is based on the EU Deforestation Regulation (EUDR) and equivalent international deforestation restriction legislation 25 Within this scope, it provides verifiable feed source traceability.

76. A method that conforms to any of claims 51, 52 or 53, and whose characteristic is machine learning-based modules (18, 55, 115); explainable artificial intelligence (Explainable AI, It must be configured to work with XAI protocols; each acceptance / rejection For the decision, the model includes the attribute weights that caused the decision, the reasoning behind the decision, and 30 Creating a justifiable record of decision reasoning that includes threshold values; 84 the reason record with a reason code that can be reviewed by a human auditor It is processed into the blockchain module (80).

77. This is a method in accordance with Claim 48, characterized by the production of milk from individual holding tanks. Measuring the transfer volume during transfer to the boiler with a flow meter (14), smart Activation of the production boiler data node (130) and transfer event of milking session 5 (228) transaction processing to the blockchain record module (80) in connection with identity (30). It includes the step.

78. A method in accordance with claim 48, the feature of which is that it is monitored 24 / 7 by the environmental sensor network (60). Milking session of indoor and outdoor meteorological parameters collected continuously from the barn. By matching the measured values ​​with SOK (30) in time, blockchain 10 Processing the module (80) as a batch-specific environmental context fingerprint and the final In product consumer validation, this fingerprint is part of the product story. It can be presented by (237) processing steps.

79. It is a system in accordance with Claim 48, the characteristic of which is that each individual dairy animal is given; that animal a specific individual standby tank monitoring module (125) and 15 connected to this standby tank Assignment of an individual production boiler data node (130); individual waiting tank monitoring module (125), individual production boiler data node (130) and animal identifier (11) establishing one-to-one identity matching and milking session ID (SOK) (30) protection throughout the entire process; the system in multi-animal applications 20 which will include an independent and parallel individual waiting-production line for each animal It is scalable in this way.

80. A method in accordance with claim 48, characterized by being obtained from an individual dairy animal. the entire process of milk production, from milking to final product labeling and maturation. throughout the process, an individual waiting tank exclusively assigned to the animal in question via the monitoring module (125) and individual production boiler data node (130), animal-25 by connecting one-to-one with the specific SOK (30) and with the milk of other animals It involves processing the data without any interference at that point.

81. A method in accordance with claim 48 or 79, characterized by the involvement of one or more third parties. The analysis results obtained from the laboratory are compared with the external analysis results assigned to the relevant sample. Automatic 30 via the original milking session ID (SOK) (30) through the identifier (DAT). matching; cryptographic verification of the match and all matching data 85 Processing into the blockchain module (80) without requiring any other manual intervention (298) includes the steps of the process.

82. This is a method in accordance with claim 48, and its characteristic feature is that it is assigned to the animal during the milking stage and regionally specific starter recorded on the blockchain as injected into the milk stream culture combination identity; final 5 under the same milking session identity (SOK) (30) culture detected from cheese by molecular analysis device interface (170) A direct comparison of the combination identity; if a match is found, "milk-cheese biological "Identity chain verified" record and "Identity chain broken" in case of discrepancy. Processing of the anomaly record into the blockchain module (80); in addition, quantitative molecular The density value measured by the concentration verification module (171) is 10 Dilution / mixing by comparison with the theoretical concentration at the time of injection. Detecting counterfeiting (277) involves procedural steps.

83. A system in accordance with Claim 79, characterized by an individual waiting period assigned to each animal. tank monitoring module (125) and individual production boiler data node (130) connected to this tank the transfer of milk between them; physically by the operator or a third party 15 through a closed, sealed and leakproof pipeline that cannot be tampered with implementation; of the closed pipeline in question; to each individual tank-boiler pair being physically separated from the lines of other animals in an exclusive way; access points (valve, connection port, sampling port) to the closed pipeline electronic lock, seal sensor or equivalent unauthorized access detection device 20 equipped with; any unauthorized access attempt is detected immediately by the blockchain module. (80) is processed as an anomaly record.

84. A system conforming to Claim 61 or Claim 62, characterized by having a regionally specific starter. culture dosing unit (160), animal-culture combination assignment module (161) and volume-proportional precision dosing pump (162); physically by the operator 25 in an inaccessible, sealed, hygienic (sanitary) enclosure its location; the choice of culture combination, the dosage amount determination and injection timing exclusively by the system automatically. This should be done in a way that only grants the operator the authority to initiate the process, and the culture Manual intervention in the prescription, dosage parameter, or injection timing 30 denial of the possibility; electronic seal sensor for unauthorized access attempt to the containment It is detected by and processed as an anomaly record in the blockchain module (80).

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