Method for assisting in improving an environmental impact of a food product in a food protein value chain

Abstract

The invention refers to a method for assisting in improving an environmental impact of a food product in a food protein value chain. Product data is received at an Application Program Interface (API) from a participant node and / or a sensor, wherein the received product data is associated with a data model of the API. The received product data is aggregated to enable further processing and the aggregated product data is forwarded to the environmental impact assessment system. From a requesting node, a request for an environmental impact assessment is received. Assessment data associated with the received product data is provided to the requesting node. The assessment data comprises information on the environmental impact assessment and is determined by the environmental impact assessment system based on the aggregated product data, wherein the provided assessment data is associated with the data model of the API.

Description

[0001] Method for assisting in improving an environmental impact of a food product in a food protein value chain

[0002] FIELD OF THE INVENTION

[0003] The invention refers to a computer-implemented method, apparatus and computer program product for assisting in improving an environmental impact of a food product in a food protein value chain. BACKGROUND OF THE INVENTION

[0004] The production of food protein can have a strong impact on the environment. Thus, improving the production of food protein with respect to its environmental impact is thus of high importance.

[0005] SUMMARY OF THE INVENTION The food protein value chain is a complex value chain with a plurality of participants that interact in a complex manner to produce respective food protein. For example, the value chain of a food product can comprise fertilized producers, plant production producers, crop farmers, livestock farmers, food packaging providers, regulators, certifiers, and consumers. In such a complex value chain it is nearly impossible for a participant to really assess an environmental impact of the production of the food protein due to the complex interactions of the participants and missing information. In particular, the data necessary for determining an environmental impact is not only spread through all participants of the food protein value chain but also exists in a plurality of formats and comes from a plurality of sources, for instance, structured data can be provided from sensors like humidity sensors, temperature sensors, etc. or from unstructured sources, for instance, an electrical bill, a transportation protocol, etc. Thus, in order to assess an environmental impact which then allows to improve the production such that the environmental impact is decreased, it is not only necessary to collect the respective data but also to make the information provided by the data available for further analysis.

[0006] Since the invention refers to a method, as described in more detail in the following, that utilizes an application program interface and a data model for receiving product data and also for providing assessment data associated with the received product data, respective product data can be gathered from a large variety of different participants in the animal protein value chain. Moreover, the utilized API and data model allow to bring the gathered product data into a format that allows the application of an environmental impact assessment by an environmental impact assessment system. Thus, the environmental impact of each participant of a food protein value chain can be assessed in this way and based on the assessment the respective participants can identify actions that lead to an improvement of the environmental impact of the food production. The environmental impact of a food product can hence be improved throughout the complete food protein value chain.

[0007] In an aspect of the invention, a computer-implemented method is presented for assisting in improving an environmental impact of a food product in a food protein value chain, wherein the method comprises a) receiving product data associated with a food protein value chain of a food product at an Application Program Interface (API) from a participant node and / or a sensor providing measurements associated with the food protein value chain of the food product, wherein the received product data is associated with a data model of the API, b) aggregating the received product data to enable further processing by an environmental impact assessment system, c) forwarding the aggregated product data to the environmental impact assessment system, d) receiving, from a requesting node, a request for an environmental impact assessment associated with the received product data, and e) providing assessment data associated with the received product data to the requesting node, wherein the assessment data comprises information on the environmental impact assessment and is determined by the environmental impact assessment system based on the aggregated product data, wherein the provided assessment data is associated with the data model of the API.

[0008] The computer implemented method can be performed by any computer system comprising one or more data processors. For example, the computer implemented method can be performed by a standard general computer, dedicated hardware, or distributed computing in which a plurality of computing systems work together to perform the functions defined in the computer implemented method.

[0009] A food protein value chain can refer to a representation of the various processes and participants involved in producing a food product, starting, for instance, with respective raw materials and ending with the respective consumer product. However, also only parts of the food protein value chain can be utilized during the environmental impact assessment. The food protein can refer to any food product that provides protein for human or animal consumption. For example, the food protein can refer to plant based protein or to animal based protein or a combination thereof. In an embodiment, the food product is an animal protein product and the food protein value chain is an animal protein value chain. However, in another embodiment, the food product is a plant protein product and the food protein value chain is a plant protein value chain. Moreover, in an embodiment, the food product can also be a combination of an animal protein product and a food protein product and the value chain can be a respective combination of an animal protein value chain and a plant protein value chain.

[0010] The environmental impact that is assessed can be any environmental impact, for example, can be a carbon footprint, a general emission footprint, a land use, an energy consumption, water use, etc. In an embodiment, the environmental impact refers to a carbon footprint that can be defined as an amount of greenhouse gases emitted or removed in the production process of the food product through the complete food product value chain or only through parts of the food protein value chain, for instance, at one production facility participating in the food protein value chain.

[0011] Product data can refer to any data that is associated with the food product in the food protein value chain. In particular, the product data can comprise production data and / or environmental impact data. Production data refers to data that is collected from a food protein value chain process in order to monitor and / or optimize a production. For example, the production data can include data on fertilizers, plant protection, soil quality and type, crop yields, water usage, feed quality, feed quantity, additives, animal type, animal number, energy consumption, final product, and production rates. Production data is collected and used to track performance and identify areas for improvement to increase efficiency and reduce costs of a specific production step in the food protein value chain. Environmental impact data refers to data that is collected to assess the environmental impact of practices in the food protein value chain. The environmental impact data can include, for instance, data on greenhouse gas emissions, water usage, soil erosion, nutrient runoff, energy consumption, utilized energy mix and waste production. Environmental impact data is used to identify the environmental impact of at least a part of the food protein value chain and to develop strategies for reducing negative impacts and promoting sustainability. In the food protein value chain, both production data and environmental impact data can be utilized for optimizing production processes and promoting sustainability. By collecting and analyzing this type of data, the participants of the food protein value chain can make informed decisions about how to manage their resources and reduce the environmental impact while maintaining or improving the yields.

[0012] The product data can be provided by a sensor and thus can be derived from measurements associated with the food protein value chain of the food product. In particular, during the production of a food product, a plurality of sensors are utilized for measuring a plurality of aspects of the production of the food product and thus generating product data, for instance, as production data and / or environmental impact data. For example, the sensors providing the product data comprise at least one of a temperature sensor, a humidity sensor, an air quality sensor, a feed and / or water consumption sensor, a CO2 sensor, an electric reader, a plant growth sensor a light sensor and an animal behavior sensor. The product data can also be received from a participant node into which a participant inputs respective product data. For example, the participant node can be a smart phone running a respective application, a tablet, personal computer, etc. The product data received via the participant node can be data that comes from a plurality of data sources. For example, the product data can refer to an electrical bill, a transport protocol, a manual input of the participant, etc. In particular, a participant interface can be configured to request specific product data input from the participant.

[0013] An application programming interface refers to a software interface that regulates and defines the communication and data utilization between different computer programs. Thus, an API can provide a regulated and defined access to functions and data of a computer program by another computer program. A data model of the API refers to a definition on how information and data is stored and retrieved in communication with and by the API. For example, the data model can define a data format, communication protocol, data structure, etc. that can be utilized in communication with the API.

[0014] In particular, the API is configured to regulate and define the communication and data utilization between the participant node and / or sensors or sensor interfaces and the respective environmental impact assessment system. For example, the sensors can provide a plurality of different sensor software and controlling and management software which can provide the respective measured data of a sensor. Moreover, a participant node can provide an application or other communication interface that can provide the product data to the API. The API allows the participant node and / or sensors to communicate the respective product data to the environmental impact assessment system without the participant node and / or sensors having any knowledge of the environmental impact assessment system, its structure or function. Moreover, the API utilizing the data model is configured such that the product data received is associated with the respective data model. For example, the data model can define the received product data, in particular, its form, structure and type. However, the data model can also define respective parameters which the received product data can utilize. Preferably, the data model defines at least one of a structure, a format and a data type of the received product data and the provided assessment data, respectively. The data structure can define a relation between the data and also between the data and real-world entities. More preferably, the data model is based on an extendable mark-up language. However, the data model can also be based on a relational database that provides contextual relations between database entries and thus can define a data structure. The data model can comprise classifying the received product data into data format classes and further processing the data according to the classification. For example, product data received in a graphic format can be classified as graph data and the data model can define that respective graph data is processed by applying a text recognition function to the graph data in order to generate text data from the graph data. However also other data conversions can be performed. In an embodiment, the data model of the API comprises classifying the received product data into data format classes and processing the data according to the data format classes, wherein at least one of one or more processing functions used for processing the received product data according to its data format class comprises a text recognition function.

[0015] In a further step, the received product data is aggregated to enable further processing by the environmental impact assessment system. The aggregating refers generally to collecting the information provided by the product data that can come from a plurality of different participant nodes and / or sensors providing the respective product data. Moreover, the aggregating can also comprise manipulating the respective product data in order to extract the respective information from the product data and, if necessary, restructure the information to be suitable to being processed by the environmental impact assessment system. Preferably, the aggregating comprises converting the received product data into a predetermined data content format. In particular, the converting of the received product data into a predetermined data content format comprises extracting from the received product data included information, classifying the information with respect to different predetermined content types and processing the information based on the predetermined content types. The extracting can be based on the respective provided data type. For example, the ex- tracting can refer to applying a text recognition and optionally a natural language processing to the product data. Preferably, the extracting comprises to converting the product data into a plain text format. Predetermined content types can be defined based on a plurality of aspects of the product data. For example, the content types can be defined by the respective provided information, by the format in which the product data is provided, by the software providing the product data, by the provided data structure, etc. For each of the predetermined content types respective functions can be defined for the processing of the information. For example, for product data classified as unstructured data, a data normalization function can be defined that can extract and normalize the respective information provided by the unstructured data and the structured data. In another example, the extracted information can be compared with a keyword dictionary for classifying the product data based on its content and if predetermined keywords are found in the extracted information the respective product data can be classified accordingly, e.g. as energy data. Based on the classification predetermined rules and functions can be applied for further processing the classified product data. Preferably, information extracted from the received product data classified as a content type referring to quantities of predetermined parameters is aggregated by determining a total amount of the respective quantity, wherein the environmental impact assessment by the environmental impact assessment system is based on the determined total amount. Additionally or alternatively, for other predetermined content types referring to quantities of respective predetermined parameters, the aggregating can refer to determining an average, or a weighted average, maximal or minimal value, etc. of the respective quantity. Preferably, information extracted from the received product data classified as physical quantities is aggregated by converting the physical quantities into a predetermined system of units.

[0016] Moreover, instead of aggregating all received product data, in one embodiment it is preferred, the aggregating comprises extracting from the product data information indicative for the environmental impact of the product and continuing the method with the extracted information. Thus, only product data that is relevant for the environmental impact of the food product is further processed increasing the computational efficiency of the aggregation process.

[0017] The method then further comprises forwarding the aggregated product data to the environmental impact assessment system. For example, the API can be communicatively coupled with the environmental impact assessment system and provide aggregated product data such that it can be further processed by the environmental impact assessment system. For example, the structure, content and format of the aggregated product data can be such that the environmental impact assessment system can directly process the product data to determine an environmental impact assessment generating assessment data. Further, the method comprises receiving, from a requesting node that can be associated with the participant of the food protein value chain, a request for an environmental impact assessment associated with the received product data. For example, a participant of the food protein value chain can utilize a respective user interface on a requesting node that can refer to any computing system communicatively coupled with the API and / or environmental impact assessment system for providing the request.

[0018] A participant of the food protein value chain can be any participant that performs a process or produces a product that is part of the food protein value chain. The participant has access to the respective product data produced during the process or production that the participant of the food protein value chain performs. The requesting node can be any computational environment that allows a participant to access and upload request to the environmental impact assessment system. For example, the requesting node can be realized in form of a smartphone, tablet, laptop, personal computer or any other computational hardware or computational interface. The receiving can then refer, for instance, to receiving an upload of the respective request.

[0019] The environmental impact assessment system can be configured to apply an environmental impact assessment generation function to the aggregated product data to generate assessment data indicative of an environmental impact assessment of a product. The utilized impact assessment generation function can be configured to utilize known physical relationships, predetermined rules and other functional relationships to utilize the product data information provided in the aggregated product data to generate assessment data. In particular, a mass balance for predetermined substances can be utilized for determining the amount of a substance emission relevant for an environmental impact. Also functions determined by official regulations and laws can be utilized for specific aspects of an environmental impact assessment. Moreover, the environmental impact assessment generation function can also refer to a machine learning algorithms that is trained based on historical product data and respective environmental impacts. Utilizing a machine learning algorithm can for example decrease the number of parameters that have to be provided as input. The specific environmental impact assessment generation function utilized can depend on the respective information available and / or on the respective request of the participant. For example, if the participant is a farmer, requesting an assessment other information is relevant than if the participant is a food product producer or a vendor of food products. Moreover, also for participants belonging to the same category, for instance, farmers, different information can be available and / or relevant. Thus, the environmental impact assessment generation function can comprise different parts and aspects that are only utilized for the environmental impact assessment if the respective information to which they refer is available and / or depending on the respective request. The aggregated product data allows in this case for a fast assessment which information is available and thus which environmental impact assessment generation function can be utilized based on the available information. The environmental impact assessment generation function then generates assessment data that is indicative of an environmental impact assessment of the product. For example, the assessment data can refer to one or more values of respective environmental impact metrics. In one example, the environmental impact assessment can refer to the value of a carbon footprint of the product. Moreover, the assessment data can also comprise more information than the simple environmental impact metric. For example, the assessment data can also comprise an analysis on the main sources of the respective environmental impact. Thus, the assessment data can be utilized for controlling and / or monitoring at least a part of a production process of the requesting participant in the food protein value chain. The assessment data can then be provided by the environmental impact assessment system to the participant via the respective requesting node. For example, a carbon footprint value can be provided to the participant via a connection to a smartphone of the participant. In particular, the assessment data is provided to the requesting node via the API utilizing the data model. This again allows to utilize the API to communicate, for instance, with the requesting node and utilizing the data model for the API for providing the assessment data such that it can be processed by the requesting node.

[0020] In a further aspect, a computer-implemented method is presented for improving an environmental impact of a food product in a food protein value chain, wherein the method comprises a) collecting non-sensor data and / or sensor data from one or more sensors providing measurements associated with the food protein value chain of the food product, b) generating product data associated with a data model of an API of an environmental impact assessment system based on the collected sensor data and / or non-sensor data and providing the product data to the API, c) providing a request to the environmental impact assessment system via the API for receiving from the API, assessment data generated as described above, d) receiving assessment data associated with the provided product data from the API as described above, wherein the assessment data comprises information on the environmental impact assessment and is determined by the environmental impact assessment system based on the aggregated product data, wherein the provided assessment data is associated with the data model of the API, and e) implementing the information included in the assessment data into a production of the food product. In a further aspect, an apparatus is presented for assisting in improving an environmental impact of a food product in a food protein value chain, wherein the apparatus comprises an API, wherein the API is configured to a) receive product data comprising associated with a food protein value chain of a food product at the API from a participant node and / or a sensor providing measurements associated with the food protein value chain of the food product, wherein the received product data is associated with a data model of the API, b) aggregate the received product data to enable further processing by an environmental impact assessment system, c) forward the aggregated product data to the environmental impact assessment system, d) receive, from a requesting node, a request for an environmental impact assessment associated with the received product data, and e) provide assessment data associated with the received product data to the requesting node, wherein the assessment data comprises information on the environmental impact assessment and is determined by the environmental impact assessment system based on the aggregated product data, wherein the provided assessment data is associated with the data model of the API.

[0021] In a further aspect, an apparatus is presented for improving an environmental impact of a food product in a food protein value chain, wherein the apparatus comprises on or more processors configured to execute a production control of the production of the food product, wherein the one or more processors are configured to a) collect non-sensor data and / or sensor data from one or more sensors providing measurements associated with the food protein value chain of the food product, b) generate product data comprising associated with a data model of an API of an environmental impact assessment system based on the collected sensor data and / or non-sensor data and providing the product data to the API, c) providing a request to the environmental impact assessment system via the API for receiving from the API, assessment data generated as described above, d) receive assessment data associated with the provided product data from the API as described above, wherein the assessment data comprises information on the environmental impact assessment and is determined by the environmental impact assessment system based on the aggregated product data, wherein the provided assessment data is associated with the data model of the API, and e) implement the information included in the assessment data into a production of the food product.

[0022] In a further aspect, a computer program product for assisting in improving an environmental impact of a food product in a food protein value chain, wherein the computer program product causes an apparatus as described above to perform the method as described above when carried out on the apparatus. In a further aspect, a computer program product is presented for improving an environmental impact of a food product in a food protein value chain, wherein the computer program product causes an apparatus as described above to perform the method as described above when carried out on the apparatus.

[0023] It shall be understood that the method as described above, the apparatus as described above, and the computer program product as described above have similar and / or identical preferred embodiments, in particular, as defined in the dependent claims.

[0024] It shall be understood that a preferred embodiment of the present invention can also be any combination of the dependent claims or above embodiments with the respective independent claim.

[0025] These and other aspects of the invention will be apparent from and elucidated with reference to the embodiments described hereinafter.

[0026] BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Fig. 1 shows schematically and exemplarily an application of sensors in the production of a food product,

[0028] Fig. 2 shows schematically and exemplarily functions of an API utilized by an environmental impact assessment system,

[0029] Fig. 3 shows schematically and exemplarily a method for assisting in improving an environmental impact of a food product in a food protein value chain,

[0030] Fig. 4 shows schematically and exemplarily a data layer structure of an environmental impact assessment system,

[0031] Fig. 5 shows schematically and exemplarily a decentralized data structure for a food protein value chain, and

[0032] Figs. 6a, b show schematically and exemplarily product data utilized by the environmental impact assessment system. DETAILED DESCRIPTION OF EMBODIMENTS

[0033] Fig. 1 shows schematically and exemplarily the utilization of sensors in a food protein value chain. In the example shown in Fig. 1 , the food protein value chain refers to an animal protein value chain and exemplarily shows the sensors utilized in swine, beef and poultry production. In this context, typically sensors are utilized to monitor environmental factors in the environment of the animals, for instance, temperature, humidity, air quality, animal behavior, feed and water consumption, etc. The most commonly used sensors in these applications are temperature sensors, humidity sensors, air quality sensors, feed and water consumption sensors, animal behavior sensors, CO2 sensors and methane sensors. Temperature sensors, for example, are utilized to measure a temperature in a barn or a housing facility and the data measured by the temperature sensors can be utilized by farmers to maintain and optimize growing conditions for the animals. Humidity sensors measure the level of moisture in the air and the measured moisture can be utilized by farmers to prevent respiratory problems in the animals and to improve overall animal health. Air quality sensors, which can refer also to CO2 sensors or methane sensors, generally measure the concentration of one or more gases such as ammoniac, carbon dioxide or methane in the air. The measured concentration of these gases can help farmers to detect and address ventilation problems, other issues that can impact animal health but also can help to optimize a feeding protocol for the animals. Feed and water consumption sensors can monitor how much feed and water the animals are consuming, wherein the data from these sensors can help farmers to optimize feeding programs and ensure that animals are receiving the necessary nutrition they need. Animal behavior sensors monitor how the animals are moving and behaving which can help farmers to detect signs of stress or illness and take appropriate action. All the sensors are typically placed throughout a barn or housing facility in strategic locations to capture the respective data or the relevant metrics. For example, temperature sensors can be placed near a heating or cooling system, while humidity sensors can be placed near an animal drinking water resource. The data collected by these sensors is typically transmitted to a central data management system where it can be analyzed and processed using software applications specifically designed for this purpose, in particular, that help the farmer to optimize animal health and welfare, improve feed efficiency and reduce waste and environmental impact. However, generally, the data is not available to other participants of the food protein value chain, for instance, to a participant producing the food for the animals, a breeding stock farmer, a vendor of the food protein produced by animals, etc. Thus, it is not possible to optimize an environmental impact of a food product over a whole food product value chain utilizing this readily available data sources. In this context, the invention allows to receive, aggregate and utilize the data from all these sensors throughout the food protein value chain for assessing an environmental impact over a part or the whole food protein value chain.

[0034] Fig. 2 shows schematically and exemplarily an embodiment of the environmental impact assessment system and / or method in which an API is utilized and the data normalization function is part of the API. In particular, the API of the environmental impact assessment system can be configured to provide a data model that defines a structure, format and data type not only for communication with the API but also for the generated structured product data. The API utilizing the data model is configured to enable the collection of product data but also of any other sustainability information from a plurality of different sources and participants in the food protein value chain. The data model can be defined for each source or can be generally defined and provides predetermined rules for the processing of the product data received from a respective data source. The definition with respect to each source and the respective rules can be set by a respective operator or can be set automatically, for instance based on a predetermined default. For example, the API and the utilized data model can be generalized for the food protein value chain such that it allows to receive GET / POST calls from different participants and provide respective requested data and response. Moreover, the API utilizing the data model can be configured to store, collect, manipulate and forward all received data, for instance, product data, such that it can be utilized by the environmental impact assessment function. For example, the API can utilize the data normalization function to structure received structured and unstructured data. Further, the API can be configured to unify and / or process received data, for instance, product data, in a predetermined way. For example, data that comes from different sources can be structured, unified and processed such that the data can be utilized in an environmental impact assessment utilizing the environmental impact assessment function. Another example is the conversion and unification of units, for instance, the conversion from a value in miles to a value in kilometres. Further, the API can be configured to perform the extraction of relevant data, for instance, can extract data that is relevant for the environmental impact assessment. An example would be that the API is configured to extract from an energy consumption bill the exact amount of energy needed to produce the food product on the farm while ignoring all other energy consumers, for instance, the energy consumed by the private house of the farmer. Additional possible functions of the API shown, for instance, in Fig. 2, can also refer to retrieving of the environmental impact, for instance, a carbon footprint from the environmental impact assessment function or system performing the function to be provided to the respective participant node. Moreover, the API can be configured to provide a certification function that allows for a certification of data, either input data but also output data, for instance, the assessment data and the calculated environmental impact. Moreover, the API can provide a graphical representation function that allows to graphically represent the data in- and outputs. Further, the API can provide service functions for the participant like providing a modelling for a carbon market or managing and monitoring transaction data.

[0035] Fig. 3 shows schematically and exemplarily a method for assisting in improving an environmental impact of a food product in a food protein value chain. The method comprises receiving product data associated with the food protein value chain of a food product at an API from a participant node and / or a sensor providing measurements associated with the food protein value chain of the food product. The received product data is associated with the data model of the API. Further, the method comprises aggregating the received product data to enable further processing by an environmental impact assessment system. The aggregated product data is then forwarded to the environmental impact assessment system. If a request for an environmental impact assessment is received from a requesting node, the environmental impact is assessed by the environmental impact assessment system by generating assessment data that is associated with the received product data. The assessment data comprises information on the environmental impact assessment and is determined by the environmental impact assessment system based on the aggregated product data. The provided assessment data is associated with the data model of the API.

[0036] Fig. 4 shows schematically and exemplarily data levels of the environmental impact assessment system. In this figure, the environmental impact assessment system is schematically shown in the middle comprising, referred to as rule base, the environmental impact assessment function that can be utilized for the environmental impact assessment. However, additionally, the environmental impact assessment system can comprise data processing parts that can be configured for data receiving, aggregation and consolidation such that the data can then be utilized by the rule base, in particular, by the environmental impact assessment function. In particular, at least a part of data processing part refers to an API utilizing a data model, for example, as described above. On the left side, as first level, different possible data sources and formats are exemplarily shown that can be provided as input to the environmental impact assessment system. For example, the data represented on the left side can refer to manual input data, excel upload data, third party application data, literature data, etc. This data can referto product data which can comprise production data and also environmental impact data. The data utilized by the environmental impact assessment system can come from databases shown, for instance, forthe upperthree data sources but can also come from individual sources, for instance, a participant node, as shown for the lower four examples. The environmental impact assessment system then utilizes, for instance, an API, and a data model that allows to represent the received data that is exchanged between the API and the respective data sources. For example, the data model can define the structure, format and data type of the information that is exchanged utilizing the API. The API itself can be utilized as an interface that allows participants to access the environmental impact assessment system, for instance, its provided databases and functionalities that are provided on one or more respective servers. The API then defines the operations that the respective participants can perform and the data that they can access or modify. The relationship between the data model utilized by the API and the API can be regarded such that the data model defines the structure and format of the data that is exchanged through the API, while the API provides the interface for the participants to access that data and perform operations on it. Thus, the data model can be regarded as a component of the API that ensures that the data exchange between the participant, for instance, the participant node, and a server, is consistent and interoperable. In an example embodiment, the data model can be based on an XML file or a similar specification that defines for different data types the structure and format with which the data types can be exchanged with the environmental impact assessment system.

[0037] Preferably, Extensible Markup Language (XML) files are utilized as part of the data model. An XML file refers to a text encoding system consisting of a set of symbols inserted in a text document to control its structure, formatting, or the relationship between its parts and a file format for storing, transmitting, and reconstructing the respective product data. In particular, it defines a set of rules for encoding documents in a format that is both human readable and machine readable. As a markup language, XML labels, categorizes and structurally organizes information, wherein XML text represents data structure and contains meta data. The data is provided within the text and encoded in a way that the XML standard specifies. Further, additional XML schemas can define the necessary meta data for interpreting and validating the XML file. Alternatively, other data models can be utilized. Preferably, relational databases are used that provide a contextual relation between the content of the product data.

[0038] Fig. 5 shows schematically and exemplarily a decentralized data structure of the food protein value chain, wherein each of the respective databases 2200, 2202 and 2208 can be a source for product data or other information that can be usable forthe environmental impact assessment of a food product. Moreover, the environmental impact assessment system can be configured to store at least some of the environmental impact assessment data one or more of the respective databases 2200, 2202 and 2208 based on an ID of a food protein product or a chain of associated food protein product IDs. A food product or an intermediate ingredient 2720, e.g., a feed mix, arriving at a respective facility of a participant can be identified. For example, a physical identifier, like a QR code can be scanned utilizing scanner 2206 and associated with a digital identifier. Based on the received intermediate ingredient or final food product 2720 utilizing the determined identifier 2222 a request to access product or environmental impact data associated with the intermediate ingredient or final food product can be triggered by a data consuming service 2210 of a participant. For example, the identifier may be provided 2212 to a data providing service 2205 associated with or of the producer of the intermediate ingredient or final food product. In addition, authentication and / or authorization information may be provided. The environmental impact data or assessment data associated with the intermediate ingredient or final food product can then be assessed via the identifier 2218 in the database 2202 of the producer. The database 2202 is a database associated with the producer and data owner of the intermediate ingredient or final food product. The one or more environmental impact data can refer to a product carbon footprint, N2, water consumption, recycled content or bio-based content and can be stored in database 2202 associated with the producer of the intermediate ingredient or final food product, e.g., feed mix, feed supplement, final food product e.g., a package of milk, eggs, meat, sausage, pizza, and the identifier. The associated data can then be provided via the data providing service 2208 to the data consuming service 2210 as signified by arrows 2220, 2216. The environmental impact data associated with the intermediate ingredient or final food product can then be stored in the data base 2208 associated with the user of the intermediate ingredient or final food product, e.g., a farm using the feed mix, as signified by arrow 2222.

[0039] Figs. 6a and 6b show schematically and exemplarily product data that can be utilized for an environmental impact assessment. In the first row of the tables the parameter name is provided. The following rows indicate a status of the parameter and typical or alternative sources. For example, a mandatory parameter is a parameter that in this example is necessary for the environmental assessment in this example case and thus has to be provided by the participant, if possible. Default values can be either set based as default, for instance, as an average from other data sources or from literature, or can be set to a specific value is available for the participant. Background values can be utilized, if available, but are only relevant for specific assessments or improvement goals. The data type and possible sources can, for instance, be defined in the data model. Generally, it is preferred that as many parameters as possible are provided by the participant to tune the assessment specifically to the production process of the participant. However, except of the mandatory parameters all other parameters utilized for the environmental impact assessment can be set to a default value. Generally, for other cases and environmental impact assessments also different parameter sets can be defined. Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims.

[0040] For the processes and methods disclosed herein, the operations performed in the processes and methods may be implemented in differing order. Furthermore, the outlined operations are only provided as examples, and some of the operations may be optional, combined into fewer steps and operations, supplemented with further operations, or expanded into additional operations without detracting from the essence of the disclosed embodiments.

[0041] In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality.

[0042] A single unit or device may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

[0043] Procedures like the receiving of product data, aggregating the received product data to enable further processing by an environmental impact assessment system, forwarding the aggregated product, receiving a request, providing of assessment data, etc. performed by one or several units or devices can be performed by any other number of units or devices. These procedures can be implemented as program code means of a computer program and / or as dedicated hardware.

[0044] A computer program product may be stored / distributed on a suitable medium, such as an optical storage medium or a solid-state medium, supplied together with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems.

[0045] Any units described herein may be processing units that are part of a classical computing system. Processing units may include a general-purpose processor and may also include a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or any other specialized circuit. Any memory may be a physical system memory, which may be volatile, non-volatile, or some combination of the two. The term “memory” may include any computer-readable storage media such as a non-volatile mass storage. If the computing system is distributed, the processing and / or memory capability may be distributed as well. The computing system may include multiple structures as “executable components”. The term “executable component” is a structure well understood in the field of computing as being a structure that can be software, hardware, or a combination thereof. For instance, when implemented in software, one of ordinary skill in the art would understand that the structure of an executable component may include software objects, routines, methods, and so forth, that may be executed on the computing system. This may include both an executable component in the heap of a computing system, or on computer- readable storage media. The structure of the executable component may exist on a computer-readable medium such that, when interpreted by one or more processors of a computing system, e.g., by a processor thread, the computing system is caused to perform a function. Such structure may be computer readable directly by the processors, for instance, as is the case if the executable component were binary, or it may be structured to be interpretable and / or compiled, for instance, whether in a single stage or in multiple stages, so as to generate such binary that is directly interpretable by the processors. In other instances, structures may be hard coded or hard wired logic gates, that are implemented exclusively or near-exclusively in hardware, such as within a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or any other specialized circuit. Accordingly, the term “executable component” is a term for a structure that is well understood by those of ordinary skill in the art of computing, whether implemented in software, hardware, or a combination. Any embodiments herein are described with reference to acts that are performed by one or more processing units of the computing system. If such acts are implemented in software, one or more processors direct the operation of the computing system in response to having executed computer-executable instructions that constitute an executable component. Computing system may also contain communication channels that allow the computing system to communicate with other computing systems over, for example, network. A “network” is defined as one or more data links that enable the transport of electronic data between computing systems and / or modules and / or other electronic devices. When information is transferred or provided over a network or another communications connection, for example, either hardwired, wireless, or a combination of hardwired or wireless, to a computing system, the computing system properly views the connection as a transmission medium. Transmission media can include a network and / or data links which can be used to carry desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general-purpose or specialpurpose computing system or combinations. While not all computing systems require a user interface, in some embodiments, the computing system includes a user interface system for use in interfacing with a user. User interfaces act as input or output mechanism to users for instance via displays. Those skilled in the art will appreciate that at least parts of the invention may be practiced in network computing environments with many types of computing system configurations, including, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, pagers, routers, switches, datacenters, wearables, such as glasses, and the like. The invention may also be practiced in distributed system environments where local and remote computing system, which are linked, for example, either by hardwired data links, wireless data links, or by a combination of hardwired and wireless data links, through a network, both perform tasks. In a distributed system environment, program modules may be located in both local and remote memory storage devices.

[0046] Those skilled in the art will also appreciate that at least parts of the invention may be practiced in a cloud computing environment. Cloud computing environments may be distributed, although this is not required. When distributed, cloud computing environments may be distributed internationally within an organization and / or have components possessed across multiple organizations. In this description and the following claims, “cloud computing” is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources, e.g., networks, servers, storage, applications, and services. The definition of “cloud computing” is not limited to any of the other numerous advantages that can be obtained from such a model when deployed. The computing systems of the figures include various components or functional blocks that may implement the various embodiments disclosed herein as explained. The various components or functional blocks may be implemented on a local computing system or may be implemented on a distributed computing system that includes elements resident in the cloud or that implement aspects of cloud computing. The various components or functional blocks may be implemented as software, hardware, or a combination of software and hardware. The computing systems shown in the figures may include more or less than the components illustrated in the figures and some of the components may be combined as circumstances warrant.

[0047] Any reference signs in the claims should not be construed as limiting the scope.

[0048] The invention refers to a method for assisting in improving an environmental impact of a food product in a food protein value chain. Product data is received at an Application Program Interface (API) from a participant node and / or a sensor, wherein the received product data is associated with a data model of the API. The received product data is aggregated to enable further processing and the aggregated product data is forwarded to the environ- mental impact assessment system. From a requesting node, a request for an environmental impact assessment is received. Assessment data associated with the received product data is provided to the requesting node. The assessment data comprises information on the environmental impact assessment and is determined by the environmental impact as- sessment system based on the aggregated product data, wherein the provided assessment data is associated with the data model of the API.

Claims

Claims1 . A computer-implemented method for assisting in improving an environmental impact of a food product in a food protein value chain, wherein the method comprises: receiving product data associated with a food protein value chain of a food product at an Application Program Interface (API) from a participant node and / or a sensor providing measurements associated with the food protein value chain of the food product, wherein the received product data is associated with a data model of the API, aggregating the received product data to enable further processing by an environmental impact assessment system, forwarding the aggregated product data to the environmental impact assessment system, receiving, from a requesting node, a request for an environmental impact assessment associated with the received product data, and providing assessment data associated with the received product data to the requesting node, wherein the assessment data comprises information on the environmental impact assessment and is determined by the environmental impact assessment system based on the aggregated product data, wherein the provided assessment data is associated with the data model of the API.

2. The method according to claim 1 , wherein the data model defines at least one of a structure, a format and a data type of the received product data and the provided assessment data, respectively.

3. The method according to any of claims 1 and 2, wherein the aggregating comprises converting the received product data into a predetermined data content format.

4. The method according to claim 3, wherein the converting of the received product data into a predetermined data content format comprises extracting from the received prod-uct data included information, classifying the information with respect to different predetermined content types and processing the information based on the predetermined content types.

5. The method according to claim 4, wherein information extracted from the received product data classified as content type referring to quantities of predetermined parameters is aggregated by determining a total amount of the respective quantity, wherein the environmental impact assessment by the environmental impact assessment system is based on the determined total amount.

6. The method according to any of claims 4 and 5, wherein information extracted from the received product data classified as physical quantities is aggregated by converting the physical quantities into a predetermined system of units.

7. The method according to any of the preceding claims, wherein the aggregating comprises extracting from the product data information indicative for the environmental impact of the product and continuing the method with the extracted information.

8. The method according to any of the preceding claims, wherein the data model is based on an extendable mark-up language.

9. The method according to any of the preceding claims, wherein the sensors providing product data comprise at least one of a temperature sensor, a humidity sensor, an air quality sensor, a feed and / or water consumption sensor, a CO2 sensor, an electric reader, a plant growth sensor a light sensor and an animal behavior sensor.

10. The method according to any of the preceding claims, wherein the food product is an animal protein product and the food protein value chain is an animal protein value chain.

11. A computer-implemented method for improving an environmental impact of a food product in a food protein value chain, wherein the method comprises: collecting non-sensor data and / or sensor data from one or more sensors providing measurements associated with the food protein value chain of the food product,generating product data associated with a data model of an API of an environmental impact assessment system based on the collected non-sensor data and / or sensor data and providing the product data to the API, providing a request to the environmental impact assessment system via the API for receiving from the API, assessment data generated according to any of claims 1 to 10, receiving assessment data associated with the provided product data from the API according to any of claims 1 to 10, wherein the assessment data comprises information on the environmental impact assessment and is determined by the environmental impact assessment system based on the aggregated product data, wherein the provided assessment data is associated with the data model of the API, and implementing the information included in the assessment data into a production of the food product.

12. An apparatus for assisting in improving an environmental impact of a food product in a food protein value chain, wherein the apparatus comprises an API, wherein the API is configured to: receive product data associated with a food protein value chain of a food product at the API from a participant node and / or a sensor providing measurements associated with the food protein value chain of the food product, wherein the received product data is associated with a data model of the API, aggregate the received product data to enable further processing by an environmental impact assessment system, forward the aggregated product data to the environmental impact assessment system, receive, from a requesting node, a request for an environmental impact assessment associated with the received product data, and provide assessment data associated with the received product data to the requesting node, wherein the assessment data comprises information on the environmental impact assessment and is determined by the environmental impact assessmentsystem based on the aggregated product data, wherein the provided assessment data is associated with the data model of the API.

13. An apparatus for improving an environmental impact of a food product in a food protein value chain, wherein the apparatus comprises on or more processors configured to execute a production control of the production of the food product, wherein the one or more processors are configured to: collect non-sensor data and / or sensor data from one or more sensors providing measurements associated with the food protein value chain of the food product, generate product data associated with a data model of an API of an environmental impact assessment system based on the collected non-sensor data and / or sensor data and providing the product data to the API, providing a request to the environmental impact assessment system via the API for receiving from the API, assessment data generated according to any of claims 1 to 10, receive assessment data associated with the provided product data from the API according to any of claims 1 to 10, wherein the assessment data comprises information on the environmental impact assessment and is determined by the environmental impact assessment system based on the aggregated product data, wherein the provided assessment data is associated with the data model of the API, and implement the information included in the assessment data into a production of the food product.

14. A computer program product for assisting in improving an environmental impact of a food product in a food protein value chain, wherein the computer program product causes an apparatus according to claim 12 to perform the method according to any of claims 1 to 10 when carried out on the apparatus.

15. A computer program product for improving an environmental impact of a food product in a food protein value chain, wherein the computer program product causes an apparatus according to claim 13 to perform the method according to claim 11 when carried out on the apparatus.

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