WO2023031166A1 - System and method for classifying animal food products - Google Patents
System and method for classifying animal food products Download PDFInfo
- Publication number
- WO2023031166A1 WO2023031166A1 PCT/EP2022/074034 EP2022074034W WO2023031166A1 WO 2023031166 A1 WO2023031166 A1 WO 2023031166A1 EP 2022074034 W EP2022074034 W EP 2022074034W WO 2023031166 A1 WO2023031166 A1 WO 2023031166A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- feed
- animal
- animal food
- classification
- database
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
- G06Q10/0875—Itemisation or classification of parts, supplies or services, e.g. bill of materials
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/018—Certifying business or products
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0623—Electronic shopping [e-shopping] by investigating goods or services
- G06Q30/0625—Electronic shopping [e-shopping] by investigating goods or services by formulating product or service queries, e.g. using keywords or predefined options
- G06Q30/0627—Electronic shopping [e-shopping] by investigating goods or services by formulating product or service queries, e.g. using keywords or predefined options by specifying product or service characteristics, e.g. product dimensions
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
Definitions
- automatization of quality control has made tremendous progress.
- robots are taking samples, machines are testing the samples and test results are sent automatically to the client.
- the present invention is not about automatization of quality control. Unlike traditional quality control, no laboratory analysis at all is needed when practicing the herein disclosed invention.
- feed ingredient data comprises feed ingredients (e.g. linseed) and one or more properties for a respective feed ingredient.
- feed ingredients e.g. linseed
- properties may be nutritional properties (e.g. linseed comprises omega-3 fatty acids) but also environmentally relevant properties (e.g. a feed ingredient is a methane inhibitor) or any other suitable type of property which is of relevance for the certification of an animal product of an animal being fed feed containing the feed ingredient, or sufficient amounts thereof.
- the “log of procurements” comprises data which indicates what feed ingredients have been procured by a selected animal food producer.
- the log may comprise further data such as the amount of procured feed ingredient, the date of procurement, delivery date etc.
- a property of the selected feed ingredient might be mirrored in food (e.g. milk, meat etc.) that has been produced by said animal. This approach allows to certify animal food products without the need to analyze a sample of the animal food product in a food laboratory (see example 2 below).
- Each method, algorithm or pseudo-code described in this specification may be implemented on a computer as a computer implemented method, as dedicated hardware, or as a combination of both.
- instructions for the computer e.g., executable code
- the executable code may be stored in a transitory or non-transitory manner. Examples of computer-readable mediums include memory devices, optical storage devices, integrated circuits, servers, online software, etc.
- a classification e.g. CO2 friendly
- an animal food product e.g. milk
- a selected animal food producer e.g. dairy farmer
- the respective electronic log of procurements indicates that the selected animal food producer has indeed procured a certain feed ingredient having one or more properties which are relevant for the classification (e.g. the feed ingredient is a methane inhibitor).
- a classification e.g. CO2 friendly
- FIGURE 2 illustrates a preferred embodiment of the system of the invention.
- system (100) is in communication with network (50) via network interface (120).
- the system of Figure 2 comprises network interface (120), processor subsystem (140), data storage interface (160) and data storage (180) with feed ingredient database (182) and logging database (184).
- the client device (200) may for example be a computer or other electronic device operated by an animal food producer to ‘log onto’ an electronic marketplace hosted by the system (100).
- the animal food producer may use the client device (200) not only to purchase feed ingredients via the electronic marketplace, but also to request and download a digital certificate.
- a digital certificate may be generated by the system (100) if and only if the feed ingredients acquired by the animal food producer cause the feed fed to his/her animals to satisfy a predetermined characteristic.
- the client device (200) may also be a computer or other electronic device operated by an independent scientific council to upload feed ingredient data.
- client device e.g., PC, laptop, ...), e.g., of animal food producer
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- General Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Educational Administration (AREA)
- Game Theory and Decision Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention relates to a computer-implemented method of certifying animal products such as meat and milk. Instead of analyzing a sample of an animal product in a laboratory, characteristics of the animal product are deduced/estimated from what has been fed to the respective animal. The computer-implemented method of the invention is preferably run on the system of the invention, said system comprising network interface (120), data storage subsystem (180) and processor subsystem (140).
Description
System and method for classifying animal food products
Technical field
The present invention relates to certification labels, quality seals, and other identifiers of products from animals. It also relates to the misuse and counterfeiting of certification labels.
Background of the invention
A certification label provides a guarantee that products possess specific characteristics. The requirements to be met by a specific kind product are set out in a document. In some cases, it is relatively easy to determine if a product meets these predetermined requirements. In other cases, a technical analysis (e.g. in a specialized laboratory) is need.
Bleu-Blanc-Cceur is a French quality seal for animal products. It identifies meat, eggs, butter and milk that comprise an increased amount of omega-3 fatty acids. Thereby, this seal provides customers with verified information about potential health benefits of the animal product.
Many animal products have a carbon foot print. Due to methane emission, total greenhouse gas emission of products originating from dairy cows, cattle and other ruminants is unpleasantly high. The carbon footprint label is an identifier of products that have had their carbon footprints certified by the Carbon Trust (Dorset House, 27-45 Stamford Street, London SE1 9NT, UK). It provides customers with verified information about the carbon impacts of the products.
EP 2 158 484 B1 discloses a method for estimating the carbon footprint of milk. To do so, the quantity of fatty acids with 16 carbon atoms or less needs to be determined in milk. This is cumbersome, slow and expensive.
EP 2 588 855 B1 discloses a method for estimating the carbon footprint of cattle meat. To do so, the quantity of at least one fatty acid contained in a sample from the respective ruminant (muscle or adipose tissue) is determined after its death. This is cumbersome, slow and expensive. A specialized laboratory with skilled personal is needed.
This applies mutatis mutandis to the Bleu-Blanc-Cceur quality seal: a specialized laboratory with skilled personal is needed to determine if meat, eggs, butter, milk or other animal products comprise an increased amount of omega-3 fatty acids.
There is a need for a less cumbersome (e.g. faster, easier, less costly) manner to get access to objective, verifiable information about animal products. More generally, there is a need for a method to provide customers with objective, verifiable information about animal products.
Summary of the invention
When certifying animal products (such as meat and milk,) a semi-quantitative estimate is often sufficient. Therefore, the problems underlying the present invention can be solved by tracking an animal’s feed. Instead of analyzing a sample of an animal product in a laboratory, characteristics of the animal product are deduced/estimated from what has been fed to the respective animal.
The amount of omega-3 fatty acids in an animal product depends on the amount of omega-3 fatty acids in the animal’s feed. Unless the feed of a livestock animal comprises significant amounts of omega-3 fatty acids, the animal will not produce meat and/or milk with an increased amount of omega-3 fatty acids. Thus, information about e.g. a cow’s feed can be used to decide if a glass of milk or a steak is worth the respective quality seal.
In one embodiment of the invention, measuring fatty acids in a sample of milk is replaced by tracking the feed of the respective dairy cow. In another embodiment of the invention, measuring fatty acids in a sample of meat is replaced by tracking the feed of the respective cattle.
Feed is a mixture of multiple feed ingredients. Dairy farmers are home feed mixers; they buy feed ingredients wherever available and affordable. This makes it difficult to track the animal’s feed. This problem is solved by accessing a logging database comprising an electronic log of procurements of feed ingredients by the dairy farmer (or any other animal food producer). This solution is particularly promising if the system of the invention is configured to host a network- accessible electronic marketplace for farmers to acquire feed ingredients from various feed ingredient suppliers. A network-accessible electronic marketplace allows tracking an animal’s feed (via the electronic log) without restricting the farmer’s freedom to procure feed ingredients wherever they are available and most affordable.
One embodiment of the invention relates to a system for determining quality of or classifying animal food products, comprising:
- a network interface;
- a data storage subsystem comprising:
- a feed ingredient database comprising feed ingredient data, the feed ingredient data comprising feed ingredients and one or more properties for a respective feed ingredient;
- a logging database comprising an electronic log of procurements of feed ingredients that will preferably be fed in a feed to an animal by one or more animal food producers;
- a processor subsystem configured to:
- access at least one classification rule configured to conditionally assign a classification to an animal food product derived from an animal if feed fed to the animal satisfies a predetermined characteristic;
- from the logging database, identify one or more feed ingredients procured by a selected animal food producer;
- from the feed ingredient database, identify one or more properties of the one or more feed ingredients;
- determine the quality of the animal food product by evaluating the at least one classification rule by determining, on the basis of the one or more properties, whether the feed ingredients acquired by the selected animal food producer cause the feed to satisfy the predetermined characteristic, and if so, assigning the classification to the animal food product of the selected animal food producer, or evaluate the at least one classification rule by determining, on the basis of the one or more properties, whether the feed ingredients acquired by the selected animal food producer cause the feed to satisfy the predetermined characteristic, and if so, assign the classification to the animal food product of the selected animal food producer.
The present invention also relates to a computer-implemented method for determining quality of or classifying animal food products, comprising:
- accessing:
- a feed ingredient database storing respective data representations of feed ingredients in relation to one or more properties of the feed ingredients;
- a logging database comprising an electronic log of procurements of feed ingredients that will preferably be fed in a feed to an animal by one or more animal food producers;
- accessing at least one classification rule configured to conditionally assign a classification to an animal food product derived from an animal if feed fed to the animal satisfies a predetermined characteristic;
- from the logging database, identifying one or more feed ingredients procured by a selected animal food producer;
- from the feed ingredient database, identifying one or more properties of the one or more feed ingredients;
- determining the quality of the animal food product by evaluating the at least one classification rule by determining, on the basis of the one or more properties, whether the feed ingredients acquired by the selected animal food producer cause the feed to satisfy the predetermined characteristic, and if so, assigning the classification to the animal food product of the selected animal food producer, or evaluating the at least one classification rule by determining, on the basis of the one or more properties, whether the feed ingredients acquired by the selected animal food
producer cause the feed to satisfy the predetermined characteristic, and if so, assigning the classification to the animal food product of the selected animal food producer
The present invention also relates to the use of a digital certificate as generated by the system of the invention to determine whether an animal food product has obtained a classification.
Detailed description of the invention
Disruptive technology is an innovation that significantly alters the way that industries operate. A disruptive technology sweeps away the systems or habits it replaces.
Automatization of manual processes is not disruptive. Often, it is rather a matter of routine. The present invention is not about automatization. It is a new, surprising approach how a known technical problem (e.g. measuring the amount of fatty acids in a sample of milk) can be solved differently.
Definitions
The noun “feed” refers to food eaten by animals that are not kept as pets. Feed comprises one or more “feed ingredients”. Exemplary feed ingredients are corn, soybean meal, distillers dried grains, linseed and feed additives (such as vitamins, minerals, enzymes etc.).
“Food” as used in the context of the present invention is for human consumption. The present invention is mostly about food that has been produced by an animal. In the context of the present invention, such food is referred to as “animal food product”. Examples of animal food products are milk, meat and eggs. A typical “animal food producer” is a farmer. Dairy farmers produce milk and optionally other animal food products. A less preferred embodiment of the invention relates to a product that has been produced by an animal but is not meant for human consumption. In the context of the present invention, such product is referred to as “animal non-food product”. Examples of animal non-food products are skin and wool. An “animal nonfood producer” is sometimes referred to as breeder. Breeders produce skin, wool and/or other animal products. In the context of the present invention, an “animal product” is either an animal food product or an animal non-food product, and is preferably an animal food product. Accordingly, an “animal producer” is either an animal food producer or an animal non-food producer, and is preferably an animal food producer. It will be appreciated that all embodiments claimed or described in this specification which refer to “animal food products” and “animal food producers” equally apply to such “animal non-food products” and “animal non-food producers”, or equally to “animal products” and “animal producers” covering both food and non-food entities.
In the context of the present invention, “determining quality of animal food products” means to determine presence or quantity of a particular ingredient in an animal food product or carbon footprint of an animal food product.
In the context of the present invention, “classifying” means to divide products into groups on the basis of a classification rule. In a preferred embodiment of the invention, classifying means to divide products into two groups on the basis of a binary classification rule (i.e. binary classification). In the context of the present invention, the products to be classified are animal products that differ only in terms of quality, production method or alike. Thus, classifying does not mean to divide different kinds of products (e.g. milk versus meat) into groups. In a preferred embodiment of the invention, classifying is somewhat similarto quality control in industry, where it is decided whether a product meets a given specification.
In the past few years, automatization of quality control has made tremendous progress. In a fully automated food quality laboratory, robots are taking samples, machines are testing the samples and test results are sent automatically to the client. The present invention is not about automatization of quality control. Unlike traditional quality control, no laboratory analysis at all is needed when practicing the herein disclosed invention.
In the context of the present invention, “evaluating a classification rule” is a procedure by which animal products are assigned to one of the groups. The preferred classification rule is a binary classification rule. “Evaluating a binary classification rule” is a procedure by which animal products are assigned to one of two groups: animal products that fulfil the rule (“yes”) are assigned to one of the two groups, whereas animal products that do not fulfil the rule (“no”) are assigned to the other of the two groups. Animal products that fulfil the rule are good products and therefore merit a certification. Animal products that do not fulfil the rule are bad (or at least less good) products and are therefore not certified. By this mechanism, the certification gives guidance to consumers that are looking for a certain quality of an animal product or for an animal product that have been produced in a certain manner (e.g. low carbon foot print).
In traditional quality control, a product specification is used to classify products. Unlike this traditional approach, the herein disclosed method is based on the use of feed ingredient data, and a log of procurements of feed ingredients that will preferably be fed in a feed to an animal to classify animal products. “Feed ingredient data” comprises feed ingredients (e.g. linseed) and one or more properties for a respective feed ingredient. Such properties may be nutritional properties (e.g. linseed comprises omega-3 fatty acids) but also environmentally relevant properties (e.g. a feed ingredient is a methane inhibitor) or any other suitable type of property which is of relevance for the certification of an animal product of an animal being fed feed containing the feed ingredient, or sufficient amounts thereof. The “log of procurements” comprises data which indicates what feed ingredients have been procured by a selected animal food producer. The log may comprise further data such as the amount of procured feed ingredient, the date of procurement, delivery date etc. There is no direct connection between the properties of a feed ingredient and an animal food product. However, if an animal has been fed with a selected feed ingredient, a property of the selected feed ingredient might be mirrored in food (e.g. milk, meat etc.) that has been produced by said animal. This approach allows to
certify animal food products without the need to analyze a sample of the animal food product in a food laboratory (see example 2 below).
The method of the invention is a method for determining quality of or classifying animal food products. Said method is preferably a computer-implemented method.
Definition “computer-implemented method”: Each method, algorithm or pseudo-code described in this specification may be implemented on a computer as a computer implemented method, as dedicated hardware, or as a combination of both. For example, instructions for the computer, e.g., executable code, may be stored on a computer-readable medium, e.g., in the form of a series of machine-readable physical marks and/or as a series of elements having different electrical, e.g., magnetic, or optical properties or values. The executable code may be stored in a transitory or non-transitory manner. Examples of computer-readable mediums include memory devices, optical storage devices, integrated circuits, servers, online software, etc.
The herein disclosed computer-implemented method for determining quality of or classifying animal food products is preferably run on the system of the invention. The system of the invention is a system for determining quality of or classifying animal food products.
Definition “system”: may be embodied as, or in, a device or apparatus, such as a server or a workstation. The device or apparatus may comprise one or more (micro)processors which execute appropriate software. The processor subsystem of the system may be embodied by one or more of these (micro)processors. Any input and/or output interfaces may be implemented by respective interfaces of the device or apparatus.
The system may also be implemented in a “distributed manner”, e.g., involving different devices or apparatus. For example, the system may be implemented by distributed system of servers, or in general, a distributed system of network nodes in a network. The distribution may for example be geographically and/or in terms of network location.
A certain feature of a system may be referred to as “subsystem”.
Definition “data storage subsystem”: may comprise a data storage device such as a hard drive, a solid-state drive or an array of such hard and/or solid-state drives. In embodiments where the system is distributed over different entities, e.g., over different servers, the data storage subsystem may also be distributed, e.g., over different data storage devices of such different servers.
Definition “processor subsystem”: may be configured, e.g., by hardware design or software, to perform the operations attributed in this specification to the processor subsystem. For example, the processor subsystem may be embodied by a single Central Processing Unit (CPU), such as a x86 or ARM-based CPU, but also by a combination or system of such CPUs and/or other types of processing units. In embodiments where the system is distributed over different entities, e.g., over different servers, the processor subsystem may also be distributed, e.g., over the CPUs of such different servers.
Definition “database”: the databases described in this specification may be separate databases, e.g., constituted by separate data structures, or may be embodied by a single database providing the functionality of the described databases, or by any other number of databases together providing the functionality of the described databases.
Definition “client/server”: the system described in this specification may interface with a client device in accordance with a client-server model. For example, the client device may be configured to act as an input device and output device for the server, allowing a user to provide input data to the server, for example by uploading data such as feed ingredient data and livestock data, and to obtain output data from the server, for example a digital certificate. In a specific example, the system as server may be network-accessible via a network, such as the Internet, and the client device may comprise or may be connected to a display and configured to establish a graphical user interface on the display which allows a user, such as a feed ingredient supplier, animal food producer or third party (e.g., supermarket), to interact with the system via the graphical user interface, for example to upload feed ingredient data, to upload livestock data, to use an electronic marketplace hosted by the system, to check if an animal product has obtained a classification, to download a digital certificate, etc.
Definition “network interface”: the network interface may take any suitable form, including but not limited to a wired communication interface (e.g. Ethernet, fiber-optic based) or a wireless communication interface (e.g., Wi-Fi) or a virtual, software-based network interface.
System of the invention
The system of the invention is a system for determining quality of or classifying animal products, said system comprising at least one network interface (120), at least one data storage subsystem (180) and at least one processor subsystem (140). More preferably, it is a system for determining quality of or classifying animal food products, said system comprising at least one network interface (120), at least one data storage subsystem (180) and at least one processor subsystem (140). Less preferably, it is a system for determining quality of or classifying animal non-food products, said system comprising at least one network interface (120), at least one data storage subsystem (180) and at least one processor subsystem (140).
The data storage subsystem (180) of the invention comprises at least one feed ingredient database (182) and at least one logging database (184).
In a preferred embodiment, the system of the invention is configured to allow upload of feed ingredient data (e.g. feed ingredients and one or more properties for a respective feed ingredient) in feed ingredient database (182). Here, the term ‘feed ingredient’ is used as a label to indicate that the database (182) is capable of storing computer-readable representations of feed ingredients and one or more properties for each respective feed ingredient. For example,
in the feed ingredient database (182), each feed ingredient may have its own record, with the properties of the feed ingredients being attributes of the record. In general, the feed ingredient database (182) may be queried on the basis of a feed ingredient to retrieve its associated properties, and in some embodiments also vice versa. It will be appreciated that the feed ingredient database (182) is not limited to a particular type of database, but rather may be any type of database which allows a feed ingredient to be related to one or more properties for the respective feed ingredient. To upload the feed ingredient data, network interface (120) may be used. By way of example, feed ingredient suppliers may upload price and availability of feed ingredients that can be procured at the herein described electronic marketplace. One or more properties for a respective feed ingredient can be uploaded in the same manner, either by the feed ingredient supplier himself, or preferably, by an independent scientific council.
In a preferred embodiment, the system of the invention is also configured to host a network- accessible electronic marketplace for animal food producers (e.g. farmers) to acquire feed ingredients (e.g. omega-3 fatty acids) from feed ingredient suppliers (e.g. DSM® Nutritional Products, Switzerland). For accessing such electronic marketplace, the same or a different network interface can be used. With a suitable client device, an animal food producer can procure any feed ingredient that is available at the electronic marketplace. In this embodiment, processor subsystem (140) is also configured to maintain an electronic log of procurements based on transaction data from the electronic marketplace. Thus, whenever an animal food producer procures a certain feed ingredient at the electronic marketplace, it is recorded in his electronic log (preferably together with procurement date and amount of procured feed ingredient). The electronic log of procurements is stored in logging database (184). Here, the term ‘logging’ is used as a label to indicate that the database (184) is capable of storing electronic logs. It will be appreciated, however, that the database (184) may also store other information besides electronic logs. It will be further appreciated that the logging database (184) is not limited to a particular type of database, but rather may be any type of database which allows storing of an electronic log.
If desired or needed, the animal food producer can actively upload additional information via network interface (120). If storage of the additional information is desired or need, the uploaded additional information can be stored in the herein described data storage subsystem (e.g. in the feed ingredient or logging database.)
In a preferred embodiment, the system of the invention is configured to, via the network interface, allow upload of livestock data. Such livestock data may indicate the history of an animal being fed with a feed. Such livestock data may indicate the number of animals to which the feed is fed and preferably also a description of the animals (breed, age, sex etc.). For applying a more sophisticated classification rule, livestock data is often needed.
In case of a very basic classification rule, a classification (e.g. CO2 friendly) may be assigned to an animal food product (e.g. milk) of a selected animal food producer (e.g. dairy farmer) if
the respective electronic log of procurements indicates that the selected animal food producer has indeed procured a certain feed ingredient having one or more properties which are relevant for the classification (e.g. the feed ingredient is a methane inhibitor). In case of a more sophisticated classification rule, a classification (e.g. CO2 friendly) may only be assigned if the amount of feed ingredient (e.g. methane inhibitor) per animal (e.g. dairy cow) exceeds a predetermined threshold. In general, the system and method of the invention may evaluate the classification rule to determine whether the feed ingredients acquired by the selected animal food producer cause the feed to satisfy a predetermined characteristic. If this is the case, the classification may be assigned to the animal food product. Such a predetermined characteristic may for example require the feed to be sufficiently methane inhibiting or to contain significant amounts of omega-3 fatty acids. In an embodiment, the predetermined characteristic may be applied to one or more select feed ingredients of the feed. The predetermined characteristic may in some embodiments relate to a presence of a feed ingredient having a particular property, but in other embodiments also to a quantity of the feed ingredient in the feed and in yet other embodiments to a qualitative requirement for the property (e.g. fatty acids should be of the omega-3 type). In a more preferred embodiment, the predetermined characteristic may be applied to the feed ingredients of the feed as a whole, so as to determine whether the feed ingredients together have sufficient methane inhibiting properties, contain sufficient amounts of omega-3 fatty acids, etc. Examples of relevant classifications of the animal food product may include ‘CO2 friendly’ in case the feed is deemed to be sufficiently methane inhibiting, or ‘Healthy’ or the aforementioned Bleu-Blanc-Cceur certification if the feed is deemed to comprise sufficient quantities of omega-3 fatty acids so that the animal food product likewise is deemed to comprise sufficient quantities of omega-3 fatty acids.
Thus, a preferred embodiment relates to the system of the invention comprising a processor subsystem configured to evaluate the at least one classification rule by determining, on the basis of the one or more properties, whether the feed ingredients acquired by the selected animal food producer cause the feed to satisfy the predetermined characteristic, and if so, assign the classification to the animal food product of the selected animal food producer, wherein the classification rule requires a ratio between an amount of feed ingredients acquired by the animal food producer and the number of animals to which the feed is fed to exceed a predetermined threshold.
Even more preferably, the classification rule is configured to conditionally assign the classification if the feed fed to the animal contains an amount of methane inhibitors which exceeds a predetermined threshold. To determine the amount of methane inhibitor, it is thereby preferred that feed ingredient database (182) indicates whether, and optionally to what degree, a feed ingredient is a methane inhibitor. In the context of methane inhibition, the preferred feed ingredient is a feed additive comprising 3-Nitrooxypropanol (abbreviated: 3-NOP). Such feed ingredients are commercially available at DSM® Nutritional Products, Switzerland.
Also preferably, the classification rule is configured to conditionally assign the classification if the feed fed to the animal contains an amount of omega-3 fatty acids which exceeds a predetermined threshold. To determine the amount of omega-3 fatty acids, it is thereby preferred that feed ingredient database (182) indicates whether, and optionally to what amount, a feed ingredient contains omega-3 fatty acids.
In a preferred embodiment of the invention, processor subsystem (140) is configured to generate a digital certificate certifying that the animal food product has obtained the classification. Thereby, the digital certificate is preferably a computer-readable code, such as a QR-code, an alphanumeric code or a hash code. Alternatively or in addition, the digital certificate is a digital ledger, for example as, or as part of, a blockchain. Such a digital certificate may be made available for download, e.g., to a user such as the animal food producer which has acquired the feed ingredients.
In a preferred embodiment, the system of the invention is also configured to enable a client device (e.g. PC, laptop, smart phone...) to check, via network interface (120), whether an animal product has obtained the classification. Such checks allow to easily unveil counterfeited certifications. Counterfeiting may be unveiled by consumer organizations, government officials, individual consumers or anybody else who owns a suitable client device.
Whenever a user (e.g. an animal food producer, a feed ingredient supplier or a consumer) is given access to the system of the invention, it is preferred to configure processor subsystem (140) such that web-accessible graphical user interface is established.
Method of the invention
The method of the invention is a computer-implemented method for determining quality of or classifying animal products, preferably for classifying animal food products.
Thereby, at least one classification rule is accessed. Said at least one classification rule configured to conditionally assign a classification to an animal food product derived from an animal if feed fed to the animal satisfies a predetermined characteristic. Preferably, the classification rule requires a ratio between an amount of feed ingredients acquired by the animal food producer and the number of animals to which the feed is fed to exceed a predetermined threshold. More preferably, the classification rule is configured to conditionally assign the classification if the feed fed to the animal contains an amount of omega-3 fatty acids which exceeds a predetermined threshold. Alternatively but also preferably, the classification rule is configured to conditionally assign the classification if the feed fed to the animal contains an amount of omega-3 fatty acids which exceeds a predetermined threshold.
The method of the invention comprises evaluating the at least one classification rule.
For evaluating the at least one classification rule, one or more feed ingredients procured by a selected animal food produce must be identified. This information is obtained by accessing logging database (184) which comprises an electronic log of procurements of feed ingredients by one or more animal food producers. If needed or desired, additional data (such livestock data indicative of the history of an animal being fed with a feed or indicative of at least a number of animals to which the feed is fed) is obtained by accessing data storage (180).
For evaluating the at least one classification rule, one or more properties of the one or more feed ingredients must also be identified. This information is obtained by accessing feed ingredient database (182) which stores respective data representations of feed ingredients in relation to one or more properties of the feed ingredients. Feed ingredient database (182) may comprise further data which can be obtained by accessing feed ingredient database (182). In a preferred embodiment, feed ingredient database (182) indicates as property of a feed ingredient whether, and optionally to what amount, the feed ingredient contains omega-3 fatty acids. Alternatively but also preferred, feed ingredient database (182) indicates as property of a feed ingredient whether, and optionally to what degree, the feed ingredient is a methane inhibitor.
Typically, the method of the invention comprises evaluating the at least one classification rule by determining, on the basis of the one or more properties, whether the feed ingredients acquired by the selected animal food producer cause the feed to satisfy the predetermined characteristic, and if so, assign the classification to the animal food product of the selected animal food producer.
Preferably, assignment of the classification is conditional. In a preferred embodiment, a classification rule is evaluated, wherein the classification rule is configured to conditionally assign the classification if the feed fed to the animal contains an amount of omega-3 fatty acids which exceeds a predetermined threshold. Alternatively but also preferably, a classification rule is evaluated, wherein the classification rule is configured to conditionally assign the classification if the feed fed to the animal contains an amount of methane inhibitors which exceeds a predetermined threshold.
Use of the invention
In a preferred embodiment, the system of the invention generates as digital certificate. The animal food producer or owner of a retail shop selling the animal food products (or anyone else) can use such digital certificate to distinguish “good” animal food products from “less good” animals food products. Therefore, the present invention also relates to the use of a digital certificate as generated by the system of the invention to determine whether an animal food product has obtained a classification.
Figures
FIGURE 1 relates to a preferred embodiment of the system of the invention. In this embodiment, system (100) is in communication with client device (200) and client device (210) via network (50). For reference numerals, see below.
FIGURE 2 illustrates a preferred embodiment of the system of the invention. In this embodiment, system (100) is in communication with network (50) via network interface (120). The system of Figure 2 comprises network interface (120), processor subsystem (140), data storage interface (160) and data storage (180) with feed ingredient database (182) and logging database (184).
With continued reference to both Figs. 1 and 2, the client device (200) may for example be a computer or other electronic device operated by an animal food producer to ‘log onto’ an electronic marketplace hosted by the system (100). In such an example, the animal food producer may use the client device (200) not only to purchase feed ingredients via the electronic marketplace, but also to request and download a digital certificate. Such a digital certificate may be generated by the system (100) if and only if the feed ingredients acquired by the animal food producer cause the feed fed to his/her animals to satisfy a predetermined characteristic. The client device (200) may also be a computer or other electronic device operated by an independent scientific council to upload feed ingredient data. The client device (200) may also be a computer or other electronic device operated by an owner of a retail shop or by a consumer or end-user of the animal food product. In such an example, the client device (200) may be used to check if a digital certificate has been issued to a particular animal food product. For that purpose, the user may enter an identifier of the animal food product, e.g. a code, so as to identify the animal food product to the system (100). It will be appreciated that the system (100) may allow several client devices (200) to connect simultaneously, e.g., from several animal food producers.
Reference numerals
50 network, e.g., the Internet
100 system (e.g., server or distributed system of servers) 120 network interface
140 processor subsystem
160 data storage interface
180 data storage subsystem (e.g., hard disk, SSD, array thereof)
182 feed ingredient database
184 logging database
200 client device (e.g., PC, laptop, ...), e.g., of animal food producer
210 client device (e.g., PC, laptop, ...), e.g., of feed ingredient supplier
Examples
Comparative Example 1
In comparative example 1 , the carbon footprint of cattle meat is estimated by the method disclosed in EP 2 588 855 B1. To do so, sample from the respective ruminant (muscle or adipose tissue) is collected. In the collected sample, the quantity of at least one fatty acid is then determined specialized laboratory with skilled personal. This is cumbersome, slow and expensive.
Example 2
In example 2, the method of the invention is applied. Because no laboratory work is needed, more than one animal food product (milk and meat) can be assessed. For further details, see below Table.
Some of the assessed products obtained the respective classification, others not. Those products that obtain the classification are certified by imprinting a QR-code on the packaging.
In the supermarket, consumers can choose between certified milk and uncertified milk. They can also choose between different kind of certified milk: omega-3 fatty acid certified, CO2 friendly certified or both. The same applies mutatis mutandis to the meat. Interested consumers can scan the QR-code on the packaging for more detailed information about the respective certification.
Sceptical consumers may request an account for directly accessing the system of the invention via a network interface. This allows sceptical consumers to check whether a specific animal product has indeed obtained the respective classification. Counterfeited QR-codes are easily unveiled.
The approach of example 2 is fast, inexpensive and fraud resistant.
1 Feed data is stored in the feed ingredient database of the invention
2 Classification rule is evaluated by accessing the famer's log of procurements; said log is stored in the logging database of the invention
3 Digital certificates are preferred. In example 2, a computer-readable code (QR-code) is generated. The code is printed on the packaging material. Consumers can read the code with an app on their smart phone
4 The system of example 2 is configured to enable a client device to check whether the animal product has obtained the classification. This can be done via the network interface.
Claims
1 . A system for determining quality of animal food products, comprising:
- a network interface;
- a data storage subsystem comprising:
- a feed ingredient database comprising feed ingredient data, the feed ingredient data comprising feed ingredients and one or more properties for a respective feed ingredient;
- a logging database comprising an electronic log of procurements of feed ingredients that will be fed in a feed to an animal by one or more animal food producers;
- a processor subsystem configured to:
- access at least one classification rule configured to conditionally assign a classification to an animal food product derived from an animal if feed fed to the animal satisfies a predetermined characteristic;
- from the logging database, identify one or more feed ingredients procured by a selected animal food producer;
- from the feed ingredient database, identify one or more properties of the one or more feed ingredients;
- determine the quality of the animal food product, by evaluating the at least one classification rule by determining, on the basis of the one or more properties, whether the feed ingredients acquired by the selected animal food producer cause the feed to satisfy the predetermined characteristic, and if so, assigning the classification to the animal food product of the selected animal food producer.
2. The system according to claim 1 , wherein the system is configured to, via the network interface, allow upload of livestock data indicative of at least a number of animals to which the feed is fed.
3. The system according to claim 2, wherein the classification rule requires a ratio between an amount of feed ingredients acquired by the animal food producer and the number of animals to which the feed is fed to exceed a predetermined threshold.
4. The system according to any one of claims 1-3, wherein the system is configured to host a network-accessible electronic marketplace for animal food producers to acquire feed ingredients from feed ingredient suppliers, wherein the processor subsystem is configured to maintain the electronic log of procurements based on transaction data from the electronic marketplace.
5. The system according to claim 4, wherein the system is configured to, via the network interface, allow upload of feed ingredient data in the feed ingredient database.
6. The system according to any one of claims 1 to 5, wherein the system is configured to enable a client device to, via the network interface, check whether the animal product has obtained the classification.
7. The system according to claim 6, wherein the processor subsystem is configured to establish a web-accessible graphical user interface to enable the client device to check whether the animal product has obtained the classification.
8. The system according to any one of claims 1 to 7, wherein the processor subsystem is configured to generate a digital certificate certifying that the animal food product has obtained the classification.
9. The system according to claim 8, wherein the processor subsystem is configured to generate the digital certificate as a computer-readable code, such as a QR-code, an alphanumeric code or a hash code.
10. The system according to claim 8, wherein the processor subsystem is configured to generate the digital certificate as a digital ledger, for example as, or as part of, a blockchain.
11. The system according to any one of claims 1 to 10, wherein the feed ingredient database indicates whether, and optionally to what amount, a feed ingredient contains omega- 3 fatty acids, wherein the classification rule is configured to conditionally assign the classification if the feed fed to the animal contains an amount of omega-3 fatty acids which exceeds a predetermined threshold.
12. The system according to any one of claims 1 to 11 , wherein the feed ingredient database indicates whether, and optionally to what degree, a feed ingredient is a methane inhibitor, wherein the classification rule is configured to conditionally assign the classification if the feed fed to the animal contains an amount of methane inhibitors which exceeds a predetermined threshold.
13. A computer-implemented method for determining quality of animal food products, comprising:
- accessing:
- a feed ingredient database storing respective data representations of feed ingredients in relation to one or more properties of the feed ingredients;
- a logging database comprising an electronic log of procurements of feed ingredients that will be fed in a feed to an animal by one or more animal food producers;
17
- accessing at least one classification rule configured to conditionally assign a classification to an animal food product derived from an animal if feed fed to the animal satisfies a predetermined characteristic;
- from the logging database, identifying one or more feed ingredients procured by a selected animal food producer;
- from the feed ingredient database, identifying one or more properties of the one or more feed ingredients;
- determine the quality of the animal food product, by evaluating the at least one classification rule by determining, on the basis of the one or more properties, whether the feed ingredients acquired by the selected animal food producer cause the feed to satisfy the predetermined characteristic, and if so, assigning the classification to the animal food product of the selected animal food producer.
14. A computer-readable medium comprising transitory or non-transitory data representing a computer program, the computer program comprising instructions for causing a processor system to perform the method according to claim 13.
15. A use of a digital certificate as generated by the system of any one of claims 6 to 8 to determine whether an animal food product has obtained a classification.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP21194092.9 | 2021-08-31 | ||
| EP21194092 | 2021-08-31 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2023031166A1 true WO2023031166A1 (en) | 2023-03-09 |
Family
ID=77666135
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/EP2022/074034 Ceased WO2023031166A1 (en) | 2021-08-31 | 2022-08-30 | System and method for classifying animal food products |
Country Status (1)
| Country | Link |
|---|---|
| WO (1) | WO2023031166A1 (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1995010812A1 (en) * | 1993-10-14 | 1995-04-20 | Coleman Environmental Systems, Inc. | Method for tracking the production history of food products |
| US20050251449A1 (en) * | 2004-04-22 | 2005-11-10 | Pape William R | Method and system for private data networks for sharing food ingredient item attribute and event data across multiple enterprises and multiple stages of production transformation |
| US20090198541A1 (en) * | 2008-01-18 | 2009-08-06 | Aginfolink Holdings Inc., A Bvi Corporation | Enhanced Brand Label Validation |
| EP2158484B1 (en) | 2008-06-25 | 2011-11-02 | Valorex | Method for evaluating the amount of methane produced by a dairy ruminant and method for decreasing and controlling this amount |
| EP2588855B1 (en) | 2010-06-29 | 2014-03-19 | Valorex | Method for evaluating the quantity of methane produced by a ruminant used for meat production |
| US20200265446A1 (en) * | 2019-02-14 | 2020-08-20 | Avery Dennison Retail Information Services, Llc | Food chain product label and method of use, and food trust identifier system |
| US20200359550A1 (en) * | 2019-05-13 | 2020-11-19 | Bao Tran | Farm ecosystem |
-
2022
- 2022-08-30 WO PCT/EP2022/074034 patent/WO2023031166A1/en not_active Ceased
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1995010812A1 (en) * | 1993-10-14 | 1995-04-20 | Coleman Environmental Systems, Inc. | Method for tracking the production history of food products |
| US20050251449A1 (en) * | 2004-04-22 | 2005-11-10 | Pape William R | Method and system for private data networks for sharing food ingredient item attribute and event data across multiple enterprises and multiple stages of production transformation |
| US20090198541A1 (en) * | 2008-01-18 | 2009-08-06 | Aginfolink Holdings Inc., A Bvi Corporation | Enhanced Brand Label Validation |
| EP2158484B1 (en) | 2008-06-25 | 2011-11-02 | Valorex | Method for evaluating the amount of methane produced by a dairy ruminant and method for decreasing and controlling this amount |
| EP2588855B1 (en) | 2010-06-29 | 2014-03-19 | Valorex | Method for evaluating the quantity of methane produced by a ruminant used for meat production |
| US20200265446A1 (en) * | 2019-02-14 | 2020-08-20 | Avery Dennison Retail Information Services, Llc | Food chain product label and method of use, and food trust identifier system |
| US20200359550A1 (en) * | 2019-05-13 | 2020-11-19 | Bao Tran | Farm ecosystem |
Non-Patent Citations (1)
| Title |
|---|
| CHRISTINE LEONG ET AL: "TRACING THE SUPPLY CHAIN", 15 January 2019 (2019-01-15), XP055607062, Retrieved from the Internet <URL:https://www.accenture.com/_acnmedia/PDF-93/Accenture-Tracing-Supply-Chain-Blockchain-Study-PoV.pdf> [retrieved on 20190718] * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lean et al. | A meta-analysis of zilpaterol and ractopamine effects on feedlot performance, carcass traits and shear strength of meat in cattle | |
| US20140141134A1 (en) | Systems and methods for creating a customized blend of pet food | |
| Martinez et al. | Pork Quality And The Role Of Market Organizaton | |
| Igo et al. | Phase I of The National Beef Quality Audit-2011: Quantifying willingness-to-pay, best-worst scaling, and current status of quality characteristics in different beef industry marketing sectors | |
| Vestal et al. | The value of genetic information to livestock buyers: a combined revealed, stated preference approach | |
| WO2013180925A2 (en) | System and method for monitoring nutritional substances to indicate adulteration | |
| Niemi et al. | A value chain analysis of interventions to control production diseases in the intensive pig production sector | |
| Oliveira et al. | Combining different functions to describe milk, fat, and protein yield in goats using Bayesian multiple-trait random regression models | |
| de Andrade et al. | Perception of consultants, feedlot owners, and packers regarding the optimal economic slaughter endpoint in feedlots: a national survey in Brazil (Part I) | |
| Valeeva et al. | Improving food safety at the dairy farm level: farmers' and experts' perceptions | |
| Kumar et al. | Assessing the performance response of laying hens to intake levels of digestible balanced protein from 27 to 66 wk of age | |
| Hammami et al. | Use of front-face fluorescence spectroscopy to differentiate sheep milks from different genotypes and feeding systems | |
| Zheng et al. | Do alternative marketing arrangements increase pork packers' market power? | |
| Wang et al. | US grass‐fed beef premiums | |
| Uemoto et al. | Development of prediction equation for methane‐related traits in beef cattle under high concentrate diets | |
| Thompson et al. | Valuation of genomic-enhanced expected progeny differences in bull purchasing | |
| WO2023031166A1 (en) | System and method for classifying animal food products | |
| Cernicchiaro et al. | Hierarchical Bayesian modeling of heterogeneous variances in average daily weight gain of commercial feedlot cattle | |
| Ankamah-Yeboah et al. | Does organic supply growth lead to reduced price premiums? The case of salmonids in Denmark | |
| Ludemann et al. | A comparison of methods to assess the likely on‐farm value for meat production systems of pasture traits and genetic gain through plant breeding using phalaris (P halaris aquatica L.) as an example | |
| Patil et al. | Nutrient requirement equations for Indian goat by multiple regression analysis and least cost ration formulation using a linear and non‐linear stochastic model | |
| Tavares et al. | Evaluation of environmental enrichment on thermophysical responses, carcass traits, and meat quality of finishing pigs | |
| Tonsor et al. | Australia’s livestock identification systems: implications for United States programs | |
| Martinez | Pork quality and the role of marketing contracts: a case study of the US pork industry | |
| Eum et al. | Multiple regression analysis to estimate the unit price of Hanwoo (Bos taurus coreanae) beef |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 22769959 Country of ref document: EP Kind code of ref document: A1 |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| 122 | Ep: pct application non-entry in european phase |
Ref document number: 22769959 Country of ref document: EP Kind code of ref document: A1 |