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Blockchain and more - Algorithm driven food traceability
Food Control 105 (2019) 45–51
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Review
Blockchain and more - Algorithm driven food traceability M. Creydt, M. Fischer
T
∗
Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146, Hamburg, Germany
ARTICLE INFO
ABSTRACT
Keywords: Blockchain Traceability Food fraud Authenticity Food chain
Food safety and quality assurance has become increasingly difficult in times of growing global flows of goods. In particular, the traceability of food turns out to be very challenging for retailers, resellers and state surveillance authorities. The reasons for this range from the proof of simple, but harmless modifications to the detection of health-endangering substances, bacteria or viruses. In addition, it concerns the verification of food authenticity, for example the correct declaration of the geographical origin, variety or cultivation. Such quality parameters justify higher prices and therefore, they are often in the focus of food fraudsters. Some of those qualities can be monitored by objective analytical methods, but not all of them. For ensuring the traceability of food trade networks blockchain algorithms incorporate a high potential, as data can be stored in an unmodifiable way and enabling quick tracking across all process steps, so that stakeholders as well as commodities or semi-finished items can be identified much faster. Areas of applications on one hand and limitations on the other hand are discussed in this review article and reflected with alternative strategies.
1. General measures to ensure food authenticity The protection of food safety and quality continuously poses new challenges for politics, industry and science. This is particularly in line to the statement by the WHO that more than 23 million people suffer from contaminated food in Europe every year. Of those affected, about 5,000 people die (WHO, 2015a; 2015b). On the one hand, the issues raised include conscious food fraud, because counterfeiters generally have a high level of ingenuity and scientific knowledge, which makes it rather difficult to find the perpetrators guilty. On the other hand, despite the high standards of hygiene and measures for quality assurance, inadvertent contamination and residues in the end products occur again and again. These include, for example, pathogenic germs such as EHEC strains (enterohemorrhagic Escherichia coli), Noro viruses or salmonella, but also chemical compounds such as MOSH (mineral oil saturated hydrocarbons) and MOAH (mineral oil aromatic hydrocarbons), which migrate from packaging materials into the raw material or the food and are a serious problem, primarily in recycled cardboard. In addition, defined and consistently observed transport or storage conditions play an important role in the assessment of food quality. For the review and compliance of standards and food safety levels,
different strategies are pursued by the legislators, politics and consumer associations plus by the institutions which are involved in the value chain, e.g. the first and the second-processing food companies. One possibility represents the use of objective analytical methods to detect food safety parameters, such as microbiological infestation or specific contaminants (mold toxins, heavy metals, pesticides, allergens etc.) as well as the evidence of molecular and sub molecular authenticity properties, which are the basis to derive indications concerning the geographic origin, biological and chemical identity and methods of production (e.g. organic vs. conventional growing). In particular, hypothesis-free fingerprinting technologies (non-targeted methods), which can also be summarized under the term omics-methods, have proven to be suitable in this regard. With the help of these methods socalled maxi or mini fingerprints can be created, by which foods could be characterized on different molecular levels. DNA analyzes (Genomics) are suitable for the detection of species or varieties as well as genetically modified foods (Herrmann et al., 2015; Schelm, Haase, Fischer, & Fischer, 2017). Based on protein profiles (Proteomics) animal species, technological processes or storage-dependent changes can be better understood. Metabolomics analyzes, which are usually done by mass spectrometry (MS) or nuclear magnetic resonance (NMR) spectroscopy,
Abbreviations: DAG, directed acyclic graph; DLT, distributed ledger technologies; EHEC, enterohemorrhagic Escherichia coli; GPS, global positioning system; HACCP, hazard analysis and critical control points; IoT, Internet of things; LFA, lateral flow assay; MOAH, mineral oil aromatic hydrocarbons; MOSH, mineral oil saturated hydrocarbons; MS, mass spectrometry; NIR, near infrared-spectroscopy; NMR, nuclear magnetic resonance; QR code, quick response; REE, rare earth elements; RFID, radio-frequency identification ∗ Corresponding author. E-mail address: [email protected] (M. Fischer). https://doi.org/10.1016/j.foodcont.2019.05.019 Received 28 March 2019; Accepted 15 May 2019 Available online 16 May 2019 0956-7135/ © 2019 Elsevier Ltd. All rights reserved.
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are relevant for evidence of origin or mode of cultivation (Bachmann, Klockmann, Haerdter, Fischer, & Hackl, 2018; Creydt, Hudzik, Rurik, Kohlbacher, & Fischer, 2018). Analyzes of stable isotopes ratios (Isotopolomics) and certain elements (especially the rare earths elements, REE) are also frequently used for such questions (Creydt & Fischer, 2018; Richter, Gurk, Wagner, Bockmayr, & Fischer, 2019). However, these methods unfortunately require a comparatively extensive instrumentation and laboratory infrastructure. Generally, those analyses have to be carried out in these laboratories, are very time consuming and thus usually very expensive. Although, some parameters can also be checked directly on-site with suitable rapid testing systems, such as c), microarrays or spectroscopic methods e. g. near-infrared-spectroscopy (NIR) or raman spectroscopy as well as comparable technologies. Such described analytical methods are carried out or commissioned by the food industry as well as applied by the official food control authorities (Esteki, Regueiro, & Simal-Gándara, 2019). In addition, the European legislator demands the complete traceability of food from “the field or the stable to the table” (European Parliament and Council. Regulation (EC) No 178/2002, 2002). So far, this claim has been met by the verification of documents such as shipping documents and invoices, which however can be easily manipulated. In addition, the reconstruction of the supply chain and the associated recall campaigns prove to be very difficult and time-consuming as well as almost impossible in the case of very complex and global trade structures, as was particularly evident in the outbreak of the EHEC epidemic in 2011. At that time, more than 3.800 people in Germany became infected with the dangerous intestinal bacterium, and in some cases the disease was even fatal. After first identifying Spanish cucumbers as triggers, Egyptian vegetable sprouts emerged weeks later as the actual culprits. During this time, more and more people fell ill because the primary source could not be identified. This example is just one of many comparable cases. Consequently, in order to be able to better guarantee the safety and authenticity of food, alternative solutions must be developed. In this regard, blockchain technology offers a great potential (Federal Institute for Risk Assessment, 2012).
subscribers, so that a “peer-to-peer network” is obtained (Fig. 1). In such networks each partner has the same rights and obligations. When creating a new data entry, it is first checked by all participants and only transferred to the block chain after verification (consensus principle). At the same time, the blockchain is stored invariably on the computers (nodes) of all participants, so that all those partners have the same information and in retrospect, no manipulations are possible (Burkhardt, Werling, & Lasi, 2018, pp. 1–9; European Union Agency for Network and Information Security, 2019). Public blockchains such as often used in crypto currencies are publicly available and do not require a higher instance. This makes them very transparent, but also comparatively slow. Private blockchains are only accessible to certain participants, so data privacy can be guaranteed. Furthermore, read-, write or administration-rights can be limited. The verification of the data sets is usually the responsibility of a participant or company. As a result of this development, the distributed structure is lost, but data backup is still cryptographically performed. In comparison to a public blockchain, this system is faster. A consortium blockchain is a mix of public and private execution, as a group of participants secure a consensus. In this way, a quick execution of the transactions can be ensured, and at the same time a decentralized administration can be guaranteed (Xu et al., 2016; Zibin; Zheng, Xie, Chen, & Wang, 2018). Several people were involved in the development of the blockchain approach, who performed various preparatory work. These include in particular the work of Haber and Stornetta with their considerations on time-stamp of digital documents, to cryptographically secure data (Haber & Stornetta, 1991) as well as the publication of Anderson regarding a decentralized data storage (Eternity Service) (Anderson, 1996). Furthermore, Schneier and Kelsey have made a contribution based on their considerations to secure data blocks (Schneier & Kelsey, 1998). A significant part is attributed to Nick Szabo for his statements regarding “smart contracts” and the “bit gold” currency (Szabo, 1997). Stefan Konst published further work in 2000 for cryptographically secured data chaining (Konst, 2000). In addition, the white paper “Bitcoin: A Peer to Peer Electronic Cash System”, published at the end of 2008, was the decisive factor, which appeared shortly after the global bank crash. This essay on a concept for a decentralized monetary system is considered authoritative for the development of blockchain technology and was published under the pseudonym “Satoshi Nakamoto”, whose exact identity is still rumored to this day (Nakamoto, 2008). One year after the appearance of the publication, the first block (genesis block) of the Bitcoin blockchain was generated using open a source software. Bitcoin is not just a blockchain, but also a digital means of payment that does not require banks (Nofer, Gomber, Hinz, & Schiereck, 2017). Bitcoin uses a “Proof of Work” algorithm to compute a new hash, where a certain number (nonce) from the total hash, the timestamp and a check number of the previous block must be determined. The nonce cannot be calculated, but determined only by trial and error. This process is performed by many computers (miners) in parallel, whereby the computer that is able to determine the hash, receive a distinct amount of bitcoins. This process is repeated every 10 min (Böhme,
2. Blockchain - what is it and what was it developed for? Distributed Ledger Technologies (DLTs) are receiving increased attention within many different industrial sectors (Bhardwaj & Kaushik, 2018, pp. 263–271). Currently, the blockchain technology represents the most important part of DLTs. The idea of the blockchain technology originally stems from the financial sector, whose basis for conducting transactions is a trusted instance such as a bank. However, this may be problematic if the intermediary pursues its own interests and/or misappropriates funds. Blockchain allows transactions to be performed independently of a mediating entity (Z. Zheng, Xie, Dai, Chen, & Wang, 2017). The basis is a digital logbook, which is also called “distributed ledger” and is composed of so-called “blocks”. These are a lists of data records. The individual blocks also contain a timestamp and an indication of the previous block, the “hash”. Through this, the individual blocks are linked together and secured against manipulations. The blockchain will be distributed decentral on the computers of all
Fig. 1. Different network structures. The blockchain is based on a distributed network and all partners have the same dataset. 46
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3. Blockchain in the food industry
Christin, Edelmann, & Tyler, 2015). Meanwhile, professional computer farms have emerged to ensure the required computing power and to generate bitcoins. Theoretically, although a commercial computer would be sufficient, but this is not worthwhile in the meantime, because the more computers are used, the greater the probability to generate the nonce and get bitcoins. In addition, the Bitcoin algorithm requires in order making profit, relatively powerful computers with a high power consumption. Meanwhile, a true arms race has sprung up between individual computer farms. According to estimates, the current amount of energy required by the four large cryptocurrencies Bitcoin, Ethereum, Litecoin and Monero is as much electricity as needed by Cuba or Slovenia. Thus, the generation of cryptocurrencies is relatively more expensive than, for example, the mining of copper, gold or platinum (Krause & Tolaymat, 2018). As an alternative to Bitcoin, the Ethereum system was introduced in 2015, which is based on a different algorithm that does not require special hardware equipment. This allows more capacity to be used so that a new block can be generated every 15 s. Therefore, this method is significantly faster and many more transactions can be performed. In addition, operators are proposing a switch from the „Proof of Work“ process to the more power-efficient „Proof of Stake“ approach, which uses a weighted randomization to select a participant to create the hash. In this manner, it is no longer the number of computer capacity, but the share of the currency (Stake) which is deposited as a kind of pledge and retained in potential fraud attempts. In this way, the system should be resource-saving and secure (Tikhomirov, 2018, pp. 206–221). Originally developed for the trading of cryptocurrencies (Blockchain 1.0), the blockchain technology is increasingly used in other areas. These include the introduction of the already mentioned smart contracts, which are mainly known under the term Blockchain 2.0. Smart Contracts are digital contracts that automatically come into effect in the so-called if-then conditions without human supervision. In this context, a common example is the function of a vending machine, which dispenses the corresponding drink after the money has been withdrawn. Smart contracts are digital contracts that automatically come into effect in if-then decisions without human supervision. In this context, a frequently used example is the function of a drinks vending machine, which dispenses the corresponding drink after the money has been paid. Applications of blockchain technologies that are not directly related to financial transactions are assigned to the third-generation blockchain (Blockchain 3.0) (Schütte et al., 2017). For the sake of completeness, as a further development of the blockchain, the tangle technology should not be left unmentioned, in which some scientists see a greater potential. In this approach, the data will no longer be stored as blocks, but as a Directed Acyclic Graph (DAG), creating a kind of mesh in which the data can be processed much faster compared to the blockchain (Fig. 2). This technique could better address the scalability issue of throughput, latency, and capacity (Popov, 2016).
The Blockchain Technology can be used in the food industry for very different issues (Galvez, Mejuto, & Simal-Gandara, 2018; Kim & Laskoski, 2018) (Fig. 3). A large field of application concerns the traceability of food. In this regard, first attempts have already been made in cooperation with the American retailer Walmart and the IT company IBM. Using the example of mangos and pork, the two partners demonstrated the strength of the system in 2017. While the hitherto customary traceability of shipping documents and invoices for these products took several days, the use of blockchain technology made it possible to trace the entire supply chain within a few seconds (Yiannas, 2018). In the future, recall actions should be able to take place much faster and more purposefully. In addition, the blockchain technology allows a more determined detection and elimination of contamination sources, so that food crises such as the above-mentioned EHEC outbreak can be correspondingly reduced much faster. Further, to the automation and digitization of documents, smart sensors can be also used to secure additional accompanying data. These include, for example, temperature loggers whose data records are transferred directly to the blockchain. In this way, cold chains should also be counterfeit-proofed and food safety should be better monitored (Fuertes et al., 2016; Kuswandi, Wicaksono, Jayus, Heng, & Ahmad, 2011). Ensuring traceability even within very complex and global supply chains implies that food fraud can be more efficiently contained. It is estimated that a total of 10% of food products traded on the world are counterfeit (Johnson, 2014). Sometimes such manipulations do not strike at all, since there is often no direct danger to health, for example when different qualities of raw materials are used, which relate to the place of cultivation, varieties or production methods. The promotion of food with such parameters is often applied to justify higher selling prices. Such products are also widely preferred by many consumers. This reason makes the counterfeit with food very lucrative. In addition, deliberate manipulation of food may also be associated with a direct health risk, for example if a surrogate with allergenic potential is used to stretch the products. In such cases, a life-threatening danger can arise for predisposed allergy sufferers. The use of digital recording and tracing approaches can also have a positive effect on the idea of sustainability. These include quality parameters based on consumer confidence like animal welfare, working conditions or special environmental requirements that cannot be analyzed by instrumental laboratory methods. For some of these parameters often also special seals are used (fair trade, marine stewardship council etc.), which can also be retraced only poorly. Also in this area, the blockchain technology could be helpful (Kim & Laskoski, 2018). Furthermore, the waste of food can be reduced, because on the one hand more contaminated batches can be narrowed down and on the other hand the shelf life of food during the transport and storage process can be monitored in more detail (Yiannas, 2018). Fig. 2. Data storage in a blockchain and as a tangle. While in a blockchain, the individual blocks involve multiple transactions, at a tangle every single transaction represents a node, which in turn must be confirmed by two other transactions. This makes the system more efficient and faster, especially with numerous transactions.
47
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Fig. 3. Various applications of Blockchain technology within the food industry.
of consumers, for example with the help of smart refrigerators, which reorder directly on their own when the supply quantity of a specific food falls below a certain level (Floarea & Sgârciu, 2016, pp. 1–6).
In addition, a blockchain is suitable for establishing greater transparency directly at the consumer, by printing the relevant data directly on the packaging (Yiannas, 2018). One-dimensional barcodes or twodimensional QR codes (quick response) are particularly suitable, because they are compact and spacesaving. These metadata can be read out by the consumers using their own smartphones (Esteki et al., 2019; Pigini & Conti, 2017). Consumer information is of overriding importance, as there has been increasing interest in the past few years (Creydt & Fischer, 2018). At the same time, the growing uncertainty caused by various food crises and scandals can be mitigated and consumer confidence be improved. This criterion is also a priority for the honest food producers and distributors, as such scandals adversely affect the entire industry, even though objectively only a fraction of a food branch is really concerned (Feng, 2016). The technology also has great potential to simplify and accelerate the logistical processes, since inventories can be reproduced in real time due to the full digitization. This includes the automation of certain processes, such as customs clearance, so that additional time is gained (Feng, 2016). With the aid of the mentioned smart contracts the financial transfer can also be time-optimized and be made simpler, since payment processes can be automated. This ensures direct networking between incoming and outgoing goods as well as payment transactions, which can be carried out autonomous and more efficient. On invoices, which are currently created on paper and often sent by post, could become unnecessary in the future (Mao, Hao, Wang, & Li, 2019; Raskin, 2017). In particular with regard to the implementation of Blockchain and the Internet of Things (IoT, see also Industry 4.0), there are still many other possibilities, whose full potential cannot yet be correctly estimated at the present time (Fernández-Caramés & Fraga-Lamas, 2018; Khan & Salah, 2018). The interaction between the digital and the real world is becoming increasingly relevant across all economic sectors. The synchronous networking and simultaneous monitoring of all production and process flows enables a just-in-time coordination in the food industry, where production capacities can be directly adapted to the demand-related behavior of the consumer. The purchase of food could be done fully automated. By this, both unnecessary costs and overproductions could be avoided and flows of goods significantly accelerated. The aim is a self-controlling process chain. The basis is the automatic identification of objects by labeling them using RFID (radiofrequency identification) systems or even simple barcodes, thus making them automatically controllable (Creydt & Fischer, 2018; Feng, 2016). Further advantages could be achieved through the direct involvement
4. How to setup a blockchain to secure the food chain? Any operator within the value chain must be part of the blockchain: The long-term establishment of blockchain approaches requires a nationwide deployment, in which every single supplier as well as every participating company must be obliged to participate. To ensure this claim, however, reliable networks must be in place to guarantee the necessary internet connections. Particularly in developing countries, as well as in very rural and sparsely populated regions, this requirement cannot always be fulfilled, which means that some technical challenges still need to be overcome in this regard (Montecchi, Plangger, & Etter, 2019; Tripoli & Schmidhuber, 2018). Further challenges result in the allocation of access rights to the sometimes very sensitive data of a blockchain. The involved stakeholders do not always support to announce their suppliers or complete recipes, because competitors also have a great interest in this knowledge. The specification of read and write rights must be done with caution, in order to protect market shares and profits, while at the same time ensuring the necessary transparency. Equally relevant are the different legal requirements within the various supplier countries. Therefore, standards must be defined for very global and far-reaching consortia in order to achieve a uniform level for all partners (Casey & Wong, 2017). The crossover from the real world into the blockchain system is of crucial importance: One of the biggest challenges is certainly the quality of the input data from the real world into the digitized blockchain, especially at the beginning of the process chain. In this regard, however, it must not be forgotten, that falsifications cannot be ruled out. In particular, during the initial steps in the raw material production, manipulations are still possible, for example, if a “certified organic” declared food is produced using pesticides and the application has not been incorporated into the blockchain. Therefore, there are basically two options: (i) One possibility would be to verify these data using objective analytical methods. (ii) A regular auditing of the production sites. Ideally, both methods are used to achieve the greatest possible data input security. For this, in addition to the digital data profiles analytical fingerprints are recorded. Currently and in the future, such measures must continue to be carried out in the digital age, too. The symbiosis of these two control instruments together with the 48
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Fig. 4. Transparency from farm to fork: Areas of application and potential data for a blockchain exemplified shown in a food process chain for chocolate production and similar products including distribution. By using QR codes on food packaging, consumers can apply their smartphones to obtain reliable additional information about the product. Specific data is limited exclusively to the blockchain network. Routine quality controls on semi-finished or finished products are still to be provided.
blockchain technology could ensure the food process chain many times more in the future and, above all, significantly facilitate the traceability of food. It is conceivable that these two approaches could be integrated into the already proven structures of a HACCP system (hazard analysis and critical control points), which already has to be applied in the EU and which, in turn, can be managed via the blockchain (European Parliament and Council. Regulation (EC) No 852/2004, 2004; Feng, 2017). In addition, these checks could be carried out according to a randomized principle, so that the effort is kept within manageable limits, but nevertheless a secure process chain is guaranteed. This system can be controlled by a forecast software, which performs a digital market observation and automatically calculates which process branch needs to be specially monitored. This may be the case, for example, when regional crop failures occur, increasing the potential for adulteration of a particular industry. Based on these calculations, the monitoring could be increased for a particular production area (Verhaelen et al., 2018). As an example Fig. 4 shows the application of the blockchain technology for cholate production process chain monitoring (Beckett, 2009). The first authenticity and quality parameters are already recorded in the blockchain during the cultivation of the raw materials. These include, for example, the cultivation method as well as the use of pesticides and fertilizers or which seed were used in the field. In the
case of animal products, feed is also of relevance. In addition, also factors relating to sustainability, working conditions or animal welfare could be relevant. Subsequently data of the harvesting or slaughtering process as well as the corresponding parameters for transport (GPS (global positioning system), moisture, temperature) and storage could be followed, which are generally carried out by crop companies, commodity traders or markets, cooperatives and logistic companies. For the recording of these data smart sensors, which are able to transfer data automatically and directly into the block chain, are suitable (Abad et al., 2009; Kuswandi et al., 2011). If necessary, importers, logistics companies and first or second processors can also record the transport or storage conditions. The manufacturers add the recipes of the final products. Furthermore, they are also responsible for the final packaging process, whose materials and production process can also be monitored in a block chain. On the packaging appropriate labels can be as well as a QR code, with which it is possible to save a variety of data in a smallest space. Wholesalers and retailers can add additional transportation and delivery conditions. In particular, retailers can better calculate freshness and shelf life using blockchain technology and plan deliveries more predictable. Consumers can use their smartphones to read out the appropriate metadata, resulting in a far-reaching, transparent process (Esteki et al., 2019; Pigini & Conti, 2017). We are just at the beginning: The linking of the digital data with 49
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the goods is only partially resolved in these days. Therefore, some researchers are currently working on a clear labeling of foods. The approaches range from consumable additives (Liang, 2013; Puddu, Paunescu, Stark, & Grass, 2014), which are added directly into the food, to the use of RFID chips, with which it is possible to reproduce at what time and at which place a product is located. At the same time, the RFID chips can serve as sensors (Shanahan et al., 2009). In addition, the establishment of standards and norms (for example, the generation of an appropriate consensus mechanism) is necessary. These include, among other things, the granting of reading and writing rights, so that a central supervisory authority is still required. In addition, it must be ensured that third parties cannot tap the confidential data. This implies the introduction of a general security system (Ge et al., 2017).
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5. Conclusion The implementation of blockchain technology combined with IoT approaches, can revolutionize the food industry. Participating companies are aware of the potential of those new technologies. Therefore, some retailers are already beginning to make demands on their suppliers to use blockchain technologies to enable a more transparent supply chain as well as a greater food security. This concerns traceability, in order to prevent contamination of the food as far as possible or to be able to record sources of input more quickly and to reduce the high proportion of food adulterants. However, it should not be forgotten that changes could still be carried out directly on the food. Especially during the first initial steps of the raw material production, clever manipulations are conceivable. In addition, it must be ensured that the food and the blockchain data are linked together and that no exchange can take place. The direct labeling of foodstuffs using synthetic, but nontoxic ingredients are considered by many consumers to be problematic. Therefore, there is still a need for additional methods and analytical technologies to meet the high demands of food. In addition, there are some challenges that need to be addressed in dealing with sensitive data and the digital storage capacity that this technology requires. This also includes a complex transformation of the working world and the current process flow primarily for small and mediumsized companies as well as the implementation of required standards and interfaces for data transmission. Due to the complexity, the full establishment of blockchain technologies is likely to take some time. Conflicts of interest The authors declare no conflicts of interest related to this article. Funding The idea of this article is based on the scientific joint project “Food Profiling” (funding code: 2816500914) funded since 2016. The project is supported by funds of the Federal Ministry of Food and Agriculture (BMEL) based on a decision of the Parliament of the Federal Republic of Germany via the Federal Office for Agriculture and Food (BLE) under the innovation support programme. The consortium is headed by the HAMBURG SCHOOL OF FOOD SCIENCE. The focus lays on developments in the area of instrumental analysis for the authentication of foodstuffs. References Abad, E., Palacio, F., Nuin, M., Zárate, A. G. d., Juarros, A., Gómez, J. M., et al. (2009). RFID smart tag for traceability and cold chain monitoring of foods: Demonstration in an intercontinental fresh fish logistic chain. Journal of Food Engineering, 93(4), 394–399. https://doi.org/10.1016/j.jfoodeng.2009.02.004. Anderson, R. (1996). The eternity service. Proceedings of Pragocrypt, 96, 242–252. Bachmann, R., Klockmann, S., Haerdter, J., Fischer, M., & Hackl, T. (2018). 1H NMR spectroscopy for determination of the geographical origin of hazelnuts. Journal of
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M. Creydt and M. Fischer Mao, D., Hao, Z., Wang, F., & Li, H. (2019). Novel automatic food trading system using consortium blockchain. Arabian Journal for Science and Engineering, 44(4), 3439–3455. https://doi.org/10.1007/s13369-018-3537-z. Montecchi, M., Plangger, K., & Etter, M. (2019). It's real, trust me! Establishing supply chain provenance using blockchain. Business Horizons. (in press) https://doi.org/10. 1016/j.bushor.2019.01.008. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic Cash system. https://bitcoin.org/ bitcoin.pdf, Accessed date: 1 March 2019. Nofer, M., Gomber, P., Hinz, O., & Schiereck, D. (2017). Blockchain. BISE, 59(3), 183–187. https://doi.org/10.1007/s12599-017-0467-3. Pigini, D., & Conti, M. (2017). NFC-based traceability in the food chain. Sustainability, 9(10), 1910–1930. https://doi.org/10.3390/su9101910. Popov, S. (2016). The tangle. http://www.tangleblog.com/wp-content/uploads/2016/11/ IOTA_Whitepaper.pdf, Accessed date: 4 March 2019. Puddu, M., Paunescu, D., Stark, W. J., & Grass, R. N. (2014). Magnetically recoverable, thermostable, hydrophobic DNA/silica encapsulates and their application as invisible oil tags. ACS Nano, 8(3), 2677–2685. https://doi.org/10.1021/nn4063853. Raskin, M. (2017). The law and legality of smart contracts. Georgetown Law Technology Review, 305–341. https://doi.org/10.2139/ssrn.2842258. Richter, B., Gurk, S., Wagner, D., Bockmayr, M., & Fischer, M. (2019). Food authentication: Multi-elemental analysis of white asparagus for provenance discrimination. Food Chemistry, 286, 475–482. https://doi.org/10.1016/j.foodchem.2019.01.105. Schelm, S., Haase, I., Fischer, C., & Fischer, M. (2017). Development of a multiplex realtime PCR for determination of apricot in marzipan using the plexor system. Journal of Agricultural and Food Chemistry, 65(2), 516–522. https://doi.org/10.1021/acs.jafc. 6b04457. Schneier, B., & Kelsey, J. (1998). Cryptographic support for secure logs on untrusted machines. The Seventh USENIX Security Symposium Proceedings, 53–62. Schütte, et al. (2017). Blockchain - technologien, Forschungsfragen und Anwendungen. https://www.aisec.fraunhofer.de/content/dam/aisec/Dokumente/Publikationen/ Studien_TechReports/deutsch/FhG-Positionspapier-Blockchain.pdf, Accessed date: 4 March 2019. Shanahan, C., Kernan, B., Ayalew, G., McDonnell, K., Butler, F., & Ward, S. (2009). A framework for beef traceability from farm to slaughter using global standards: An Irish perspective. Computers and Electronics in Agriculture, 66(1), 62–69. https://doi.
org/10.1016/j.compag.2008.12.002. Szabo, N. (1997). Formalizing and securing relationships on public networks. First Monday, 2(9)https://doi.org/10.5210/fm.v2i9.548. Tikhomirov, S. (2018). Ethereum: State of knowledge and research perspectives. Cham: Foundations and Practice of Security. FPS 2017. Lecture Notes in Computer Science https://doi.org/10.1007/978-3-319-75650-9_14. Tripoli, M., & Schmidhuber, J. (2018). Food and agriculture organization of the united nations. Emerging opportunities for the application of blockchain in the agri-food industry. http://www.fao.org/3/CA1335EN/ca1335en.pdf, Accessed date: 4 March 2019. Verhaelen, K., Bauer, A., Günther, F., Müller, B., Nist, M., Ülker Celik, B., et al. (2018). Anticipation of food safety and fraud issues: ISAR - a new screening tool to monitor food prices and commodity flows. Food Control, 94, 93–101. https://doi.org/10. 1016/j.foodcont.2018.06.029. WHO (2015a). More than 23 million people in the WHO European Region fall ill from unsafe food every year. http://www.euro.who.int/en/health-topics/disease-prevention/ food-safety/news/news/2015/12/more-than-23-million-people-in-the-whoeuropean-region-fall-ill-from-unsafe-food-every-year, Accessed date: 1 March 2019. WHO (2015b). WHO estimates of the global burden of foodborne diseases: Foodborne disease burden epidemiology reference group 2007-2015. https://apps.who.int/iris/bitstream/ handle/10665/199350/9789241565165_eng.pdf?sequence=1, Accessed date: 1 March 2019. Xu, X., Pautasso, C., Zhu, L., Gramoli, V., Ponomarev, A., Tran, A. B., et al. (2016). The blockchain as a software connector. Venice: 2016 13th working IEEE/IFIP conference on software architecture (WICSA). 182-191. https://doi.org/10.1109/WICSA.2016.21. Yiannas, F. (2018). A new era of food transparency powered by blockchain. Innovations: Technology, Governance, Globalization, 12(1–2), 46–56. https://doi.org/10.1162/ inov_a_00266. Zheng, Z., Xie, S., Chen, X., & Wang, H. (2018). Blockchain challenges and opportunities: A survey. International Journal of Web and Grid Services, 14(4), 352–375. https://doi. org/10.1504/IJWGS.2018.095647. Zheng, Z., Xie, S., Dai, H., Chen, X., & Wang, H. (2017). An overview of blockchain technology: Architecture, consensus, and future trends. Honolulu: 2017 IEEE international congress on big data (BigData congress) (pp. 557–564). . https://doi.org/10. 1109/BigDataCongress.2017.85.
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Food Control journal homepage: www.elsevier.com/locate/foodcont
Review
Blockchain and more - Algorithm driven food traceability M. Creydt, M. Fischer
T
∗
Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146, Hamburg, Germany
ARTICLE INFO
ABSTRACT
Keywords: Blockchain Traceability Food fraud Authenticity Food chain
Food safety and quality assurance has become increasingly difficult in times of growing global flows of goods. In particular, the traceability of food turns out to be very challenging for retailers, resellers and state surveillance authorities. The reasons for this range from the proof of simple, but harmless modifications to the detection of health-endangering substances, bacteria or viruses. In addition, it concerns the verification of food authenticity, for example the correct declaration of the geographical origin, variety or cultivation. Such quality parameters justify higher prices and therefore, they are often in the focus of food fraudsters. Some of those qualities can be monitored by objective analytical methods, but not all of them. For ensuring the traceability of food trade networks blockchain algorithms incorporate a high potential, as data can be stored in an unmodifiable way and enabling quick tracking across all process steps, so that stakeholders as well as commodities or semi-finished items can be identified much faster. Areas of applications on one hand and limitations on the other hand are discussed in this review article and reflected with alternative strategies.
1. General measures to ensure food authenticity The protection of food safety and quality continuously poses new challenges for politics, industry and science. This is particularly in line to the statement by the WHO that more than 23 million people suffer from contaminated food in Europe every year. Of those affected, about 5,000 people die (WHO, 2015a; 2015b). On the one hand, the issues raised include conscious food fraud, because counterfeiters generally have a high level of ingenuity and scientific knowledge, which makes it rather difficult to find the perpetrators guilty. On the other hand, despite the high standards of hygiene and measures for quality assurance, inadvertent contamination and residues in the end products occur again and again. These include, for example, pathogenic germs such as EHEC strains (enterohemorrhagic Escherichia coli), Noro viruses or salmonella, but also chemical compounds such as MOSH (mineral oil saturated hydrocarbons) and MOAH (mineral oil aromatic hydrocarbons), which migrate from packaging materials into the raw material or the food and are a serious problem, primarily in recycled cardboard. In addition, defined and consistently observed transport or storage conditions play an important role in the assessment of food quality. For the review and compliance of standards and food safety levels,
different strategies are pursued by the legislators, politics and consumer associations plus by the institutions which are involved in the value chain, e.g. the first and the second-processing food companies. One possibility represents the use of objective analytical methods to detect food safety parameters, such as microbiological infestation or specific contaminants (mold toxins, heavy metals, pesticides, allergens etc.) as well as the evidence of molecular and sub molecular authenticity properties, which are the basis to derive indications concerning the geographic origin, biological and chemical identity and methods of production (e.g. organic vs. conventional growing). In particular, hypothesis-free fingerprinting technologies (non-targeted methods), which can also be summarized under the term omics-methods, have proven to be suitable in this regard. With the help of these methods socalled maxi or mini fingerprints can be created, by which foods could be characterized on different molecular levels. DNA analyzes (Genomics) are suitable for the detection of species or varieties as well as genetically modified foods (Herrmann et al., 2015; Schelm, Haase, Fischer, & Fischer, 2017). Based on protein profiles (Proteomics) animal species, technological processes or storage-dependent changes can be better understood. Metabolomics analyzes, which are usually done by mass spectrometry (MS) or nuclear magnetic resonance (NMR) spectroscopy,
Abbreviations: DAG, directed acyclic graph; DLT, distributed ledger technologies; EHEC, enterohemorrhagic Escherichia coli; GPS, global positioning system; HACCP, hazard analysis and critical control points; IoT, Internet of things; LFA, lateral flow assay; MOAH, mineral oil aromatic hydrocarbons; MOSH, mineral oil saturated hydrocarbons; MS, mass spectrometry; NIR, near infrared-spectroscopy; NMR, nuclear magnetic resonance; QR code, quick response; REE, rare earth elements; RFID, radio-frequency identification ∗ Corresponding author. E-mail address: [email protected] (M. Fischer). https://doi.org/10.1016/j.foodcont.2019.05.019 Received 28 March 2019; Accepted 15 May 2019 Available online 16 May 2019 0956-7135/ © 2019 Elsevier Ltd. All rights reserved.
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are relevant for evidence of origin or mode of cultivation (Bachmann, Klockmann, Haerdter, Fischer, & Hackl, 2018; Creydt, Hudzik, Rurik, Kohlbacher, & Fischer, 2018). Analyzes of stable isotopes ratios (Isotopolomics) and certain elements (especially the rare earths elements, REE) are also frequently used for such questions (Creydt & Fischer, 2018; Richter, Gurk, Wagner, Bockmayr, & Fischer, 2019). However, these methods unfortunately require a comparatively extensive instrumentation and laboratory infrastructure. Generally, those analyses have to be carried out in these laboratories, are very time consuming and thus usually very expensive. Although, some parameters can also be checked directly on-site with suitable rapid testing systems, such as c), microarrays or spectroscopic methods e. g. near-infrared-spectroscopy (NIR) or raman spectroscopy as well as comparable technologies. Such described analytical methods are carried out or commissioned by the food industry as well as applied by the official food control authorities (Esteki, Regueiro, & Simal-Gándara, 2019). In addition, the European legislator demands the complete traceability of food from “the field or the stable to the table” (European Parliament and Council. Regulation (EC) No 178/2002, 2002). So far, this claim has been met by the verification of documents such as shipping documents and invoices, which however can be easily manipulated. In addition, the reconstruction of the supply chain and the associated recall campaigns prove to be very difficult and time-consuming as well as almost impossible in the case of very complex and global trade structures, as was particularly evident in the outbreak of the EHEC epidemic in 2011. At that time, more than 3.800 people in Germany became infected with the dangerous intestinal bacterium, and in some cases the disease was even fatal. After first identifying Spanish cucumbers as triggers, Egyptian vegetable sprouts emerged weeks later as the actual culprits. During this time, more and more people fell ill because the primary source could not be identified. This example is just one of many comparable cases. Consequently, in order to be able to better guarantee the safety and authenticity of food, alternative solutions must be developed. In this regard, blockchain technology offers a great potential (Federal Institute for Risk Assessment, 2012).
subscribers, so that a “peer-to-peer network” is obtained (Fig. 1). In such networks each partner has the same rights and obligations. When creating a new data entry, it is first checked by all participants and only transferred to the block chain after verification (consensus principle). At the same time, the blockchain is stored invariably on the computers (nodes) of all participants, so that all those partners have the same information and in retrospect, no manipulations are possible (Burkhardt, Werling, & Lasi, 2018, pp. 1–9; European Union Agency for Network and Information Security, 2019). Public blockchains such as often used in crypto currencies are publicly available and do not require a higher instance. This makes them very transparent, but also comparatively slow. Private blockchains are only accessible to certain participants, so data privacy can be guaranteed. Furthermore, read-, write or administration-rights can be limited. The verification of the data sets is usually the responsibility of a participant or company. As a result of this development, the distributed structure is lost, but data backup is still cryptographically performed. In comparison to a public blockchain, this system is faster. A consortium blockchain is a mix of public and private execution, as a group of participants secure a consensus. In this way, a quick execution of the transactions can be ensured, and at the same time a decentralized administration can be guaranteed (Xu et al., 2016; Zibin; Zheng, Xie, Chen, & Wang, 2018). Several people were involved in the development of the blockchain approach, who performed various preparatory work. These include in particular the work of Haber and Stornetta with their considerations on time-stamp of digital documents, to cryptographically secure data (Haber & Stornetta, 1991) as well as the publication of Anderson regarding a decentralized data storage (Eternity Service) (Anderson, 1996). Furthermore, Schneier and Kelsey have made a contribution based on their considerations to secure data blocks (Schneier & Kelsey, 1998). A significant part is attributed to Nick Szabo for his statements regarding “smart contracts” and the “bit gold” currency (Szabo, 1997). Stefan Konst published further work in 2000 for cryptographically secured data chaining (Konst, 2000). In addition, the white paper “Bitcoin: A Peer to Peer Electronic Cash System”, published at the end of 2008, was the decisive factor, which appeared shortly after the global bank crash. This essay on a concept for a decentralized monetary system is considered authoritative for the development of blockchain technology and was published under the pseudonym “Satoshi Nakamoto”, whose exact identity is still rumored to this day (Nakamoto, 2008). One year after the appearance of the publication, the first block (genesis block) of the Bitcoin blockchain was generated using open a source software. Bitcoin is not just a blockchain, but also a digital means of payment that does not require banks (Nofer, Gomber, Hinz, & Schiereck, 2017). Bitcoin uses a “Proof of Work” algorithm to compute a new hash, where a certain number (nonce) from the total hash, the timestamp and a check number of the previous block must be determined. The nonce cannot be calculated, but determined only by trial and error. This process is performed by many computers (miners) in parallel, whereby the computer that is able to determine the hash, receive a distinct amount of bitcoins. This process is repeated every 10 min (Böhme,
2. Blockchain - what is it and what was it developed for? Distributed Ledger Technologies (DLTs) are receiving increased attention within many different industrial sectors (Bhardwaj & Kaushik, 2018, pp. 263–271). Currently, the blockchain technology represents the most important part of DLTs. The idea of the blockchain technology originally stems from the financial sector, whose basis for conducting transactions is a trusted instance such as a bank. However, this may be problematic if the intermediary pursues its own interests and/or misappropriates funds. Blockchain allows transactions to be performed independently of a mediating entity (Z. Zheng, Xie, Dai, Chen, & Wang, 2017). The basis is a digital logbook, which is also called “distributed ledger” and is composed of so-called “blocks”. These are a lists of data records. The individual blocks also contain a timestamp and an indication of the previous block, the “hash”. Through this, the individual blocks are linked together and secured against manipulations. The blockchain will be distributed decentral on the computers of all
Fig. 1. Different network structures. The blockchain is based on a distributed network and all partners have the same dataset. 46
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3. Blockchain in the food industry
Christin, Edelmann, & Tyler, 2015). Meanwhile, professional computer farms have emerged to ensure the required computing power and to generate bitcoins. Theoretically, although a commercial computer would be sufficient, but this is not worthwhile in the meantime, because the more computers are used, the greater the probability to generate the nonce and get bitcoins. In addition, the Bitcoin algorithm requires in order making profit, relatively powerful computers with a high power consumption. Meanwhile, a true arms race has sprung up between individual computer farms. According to estimates, the current amount of energy required by the four large cryptocurrencies Bitcoin, Ethereum, Litecoin and Monero is as much electricity as needed by Cuba or Slovenia. Thus, the generation of cryptocurrencies is relatively more expensive than, for example, the mining of copper, gold or platinum (Krause & Tolaymat, 2018). As an alternative to Bitcoin, the Ethereum system was introduced in 2015, which is based on a different algorithm that does not require special hardware equipment. This allows more capacity to be used so that a new block can be generated every 15 s. Therefore, this method is significantly faster and many more transactions can be performed. In addition, operators are proposing a switch from the „Proof of Work“ process to the more power-efficient „Proof of Stake“ approach, which uses a weighted randomization to select a participant to create the hash. In this manner, it is no longer the number of computer capacity, but the share of the currency (Stake) which is deposited as a kind of pledge and retained in potential fraud attempts. In this way, the system should be resource-saving and secure (Tikhomirov, 2018, pp. 206–221). Originally developed for the trading of cryptocurrencies (Blockchain 1.0), the blockchain technology is increasingly used in other areas. These include the introduction of the already mentioned smart contracts, which are mainly known under the term Blockchain 2.0. Smart Contracts are digital contracts that automatically come into effect in the so-called if-then conditions without human supervision. In this context, a common example is the function of a vending machine, which dispenses the corresponding drink after the money has been withdrawn. Smart contracts are digital contracts that automatically come into effect in if-then decisions without human supervision. In this context, a frequently used example is the function of a drinks vending machine, which dispenses the corresponding drink after the money has been paid. Applications of blockchain technologies that are not directly related to financial transactions are assigned to the third-generation blockchain (Blockchain 3.0) (Schütte et al., 2017). For the sake of completeness, as a further development of the blockchain, the tangle technology should not be left unmentioned, in which some scientists see a greater potential. In this approach, the data will no longer be stored as blocks, but as a Directed Acyclic Graph (DAG), creating a kind of mesh in which the data can be processed much faster compared to the blockchain (Fig. 2). This technique could better address the scalability issue of throughput, latency, and capacity (Popov, 2016).
The Blockchain Technology can be used in the food industry for very different issues (Galvez, Mejuto, & Simal-Gandara, 2018; Kim & Laskoski, 2018) (Fig. 3). A large field of application concerns the traceability of food. In this regard, first attempts have already been made in cooperation with the American retailer Walmart and the IT company IBM. Using the example of mangos and pork, the two partners demonstrated the strength of the system in 2017. While the hitherto customary traceability of shipping documents and invoices for these products took several days, the use of blockchain technology made it possible to trace the entire supply chain within a few seconds (Yiannas, 2018). In the future, recall actions should be able to take place much faster and more purposefully. In addition, the blockchain technology allows a more determined detection and elimination of contamination sources, so that food crises such as the above-mentioned EHEC outbreak can be correspondingly reduced much faster. Further, to the automation and digitization of documents, smart sensors can be also used to secure additional accompanying data. These include, for example, temperature loggers whose data records are transferred directly to the blockchain. In this way, cold chains should also be counterfeit-proofed and food safety should be better monitored (Fuertes et al., 2016; Kuswandi, Wicaksono, Jayus, Heng, & Ahmad, 2011). Ensuring traceability even within very complex and global supply chains implies that food fraud can be more efficiently contained. It is estimated that a total of 10% of food products traded on the world are counterfeit (Johnson, 2014). Sometimes such manipulations do not strike at all, since there is often no direct danger to health, for example when different qualities of raw materials are used, which relate to the place of cultivation, varieties or production methods. The promotion of food with such parameters is often applied to justify higher selling prices. Such products are also widely preferred by many consumers. This reason makes the counterfeit with food very lucrative. In addition, deliberate manipulation of food may also be associated with a direct health risk, for example if a surrogate with allergenic potential is used to stretch the products. In such cases, a life-threatening danger can arise for predisposed allergy sufferers. The use of digital recording and tracing approaches can also have a positive effect on the idea of sustainability. These include quality parameters based on consumer confidence like animal welfare, working conditions or special environmental requirements that cannot be analyzed by instrumental laboratory methods. For some of these parameters often also special seals are used (fair trade, marine stewardship council etc.), which can also be retraced only poorly. Also in this area, the blockchain technology could be helpful (Kim & Laskoski, 2018). Furthermore, the waste of food can be reduced, because on the one hand more contaminated batches can be narrowed down and on the other hand the shelf life of food during the transport and storage process can be monitored in more detail (Yiannas, 2018). Fig. 2. Data storage in a blockchain and as a tangle. While in a blockchain, the individual blocks involve multiple transactions, at a tangle every single transaction represents a node, which in turn must be confirmed by two other transactions. This makes the system more efficient and faster, especially with numerous transactions.
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Fig. 3. Various applications of Blockchain technology within the food industry.
of consumers, for example with the help of smart refrigerators, which reorder directly on their own when the supply quantity of a specific food falls below a certain level (Floarea & Sgârciu, 2016, pp. 1–6).
In addition, a blockchain is suitable for establishing greater transparency directly at the consumer, by printing the relevant data directly on the packaging (Yiannas, 2018). One-dimensional barcodes or twodimensional QR codes (quick response) are particularly suitable, because they are compact and spacesaving. These metadata can be read out by the consumers using their own smartphones (Esteki et al., 2019; Pigini & Conti, 2017). Consumer information is of overriding importance, as there has been increasing interest in the past few years (Creydt & Fischer, 2018). At the same time, the growing uncertainty caused by various food crises and scandals can be mitigated and consumer confidence be improved. This criterion is also a priority for the honest food producers and distributors, as such scandals adversely affect the entire industry, even though objectively only a fraction of a food branch is really concerned (Feng, 2016). The technology also has great potential to simplify and accelerate the logistical processes, since inventories can be reproduced in real time due to the full digitization. This includes the automation of certain processes, such as customs clearance, so that additional time is gained (Feng, 2016). With the aid of the mentioned smart contracts the financial transfer can also be time-optimized and be made simpler, since payment processes can be automated. This ensures direct networking between incoming and outgoing goods as well as payment transactions, which can be carried out autonomous and more efficient. On invoices, which are currently created on paper and often sent by post, could become unnecessary in the future (Mao, Hao, Wang, & Li, 2019; Raskin, 2017). In particular with regard to the implementation of Blockchain and the Internet of Things (IoT, see also Industry 4.0), there are still many other possibilities, whose full potential cannot yet be correctly estimated at the present time (Fernández-Caramés & Fraga-Lamas, 2018; Khan & Salah, 2018). The interaction between the digital and the real world is becoming increasingly relevant across all economic sectors. The synchronous networking and simultaneous monitoring of all production and process flows enables a just-in-time coordination in the food industry, where production capacities can be directly adapted to the demand-related behavior of the consumer. The purchase of food could be done fully automated. By this, both unnecessary costs and overproductions could be avoided and flows of goods significantly accelerated. The aim is a self-controlling process chain. The basis is the automatic identification of objects by labeling them using RFID (radiofrequency identification) systems or even simple barcodes, thus making them automatically controllable (Creydt & Fischer, 2018; Feng, 2016). Further advantages could be achieved through the direct involvement
4. How to setup a blockchain to secure the food chain? Any operator within the value chain must be part of the blockchain: The long-term establishment of blockchain approaches requires a nationwide deployment, in which every single supplier as well as every participating company must be obliged to participate. To ensure this claim, however, reliable networks must be in place to guarantee the necessary internet connections. Particularly in developing countries, as well as in very rural and sparsely populated regions, this requirement cannot always be fulfilled, which means that some technical challenges still need to be overcome in this regard (Montecchi, Plangger, & Etter, 2019; Tripoli & Schmidhuber, 2018). Further challenges result in the allocation of access rights to the sometimes very sensitive data of a blockchain. The involved stakeholders do not always support to announce their suppliers or complete recipes, because competitors also have a great interest in this knowledge. The specification of read and write rights must be done with caution, in order to protect market shares and profits, while at the same time ensuring the necessary transparency. Equally relevant are the different legal requirements within the various supplier countries. Therefore, standards must be defined for very global and far-reaching consortia in order to achieve a uniform level for all partners (Casey & Wong, 2017). The crossover from the real world into the blockchain system is of crucial importance: One of the biggest challenges is certainly the quality of the input data from the real world into the digitized blockchain, especially at the beginning of the process chain. In this regard, however, it must not be forgotten, that falsifications cannot be ruled out. In particular, during the initial steps in the raw material production, manipulations are still possible, for example, if a “certified organic” declared food is produced using pesticides and the application has not been incorporated into the blockchain. Therefore, there are basically two options: (i) One possibility would be to verify these data using objective analytical methods. (ii) A regular auditing of the production sites. Ideally, both methods are used to achieve the greatest possible data input security. For this, in addition to the digital data profiles analytical fingerprints are recorded. Currently and in the future, such measures must continue to be carried out in the digital age, too. The symbiosis of these two control instruments together with the 48
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Fig. 4. Transparency from farm to fork: Areas of application and potential data for a blockchain exemplified shown in a food process chain for chocolate production and similar products including distribution. By using QR codes on food packaging, consumers can apply their smartphones to obtain reliable additional information about the product. Specific data is limited exclusively to the blockchain network. Routine quality controls on semi-finished or finished products are still to be provided.
blockchain technology could ensure the food process chain many times more in the future and, above all, significantly facilitate the traceability of food. It is conceivable that these two approaches could be integrated into the already proven structures of a HACCP system (hazard analysis and critical control points), which already has to be applied in the EU and which, in turn, can be managed via the blockchain (European Parliament and Council. Regulation (EC) No 852/2004, 2004; Feng, 2017). In addition, these checks could be carried out according to a randomized principle, so that the effort is kept within manageable limits, but nevertheless a secure process chain is guaranteed. This system can be controlled by a forecast software, which performs a digital market observation and automatically calculates which process branch needs to be specially monitored. This may be the case, for example, when regional crop failures occur, increasing the potential for adulteration of a particular industry. Based on these calculations, the monitoring could be increased for a particular production area (Verhaelen et al., 2018). As an example Fig. 4 shows the application of the blockchain technology for cholate production process chain monitoring (Beckett, 2009). The first authenticity and quality parameters are already recorded in the blockchain during the cultivation of the raw materials. These include, for example, the cultivation method as well as the use of pesticides and fertilizers or which seed were used in the field. In the
case of animal products, feed is also of relevance. In addition, also factors relating to sustainability, working conditions or animal welfare could be relevant. Subsequently data of the harvesting or slaughtering process as well as the corresponding parameters for transport (GPS (global positioning system), moisture, temperature) and storage could be followed, which are generally carried out by crop companies, commodity traders or markets, cooperatives and logistic companies. For the recording of these data smart sensors, which are able to transfer data automatically and directly into the block chain, are suitable (Abad et al., 2009; Kuswandi et al., 2011). If necessary, importers, logistics companies and first or second processors can also record the transport or storage conditions. The manufacturers add the recipes of the final products. Furthermore, they are also responsible for the final packaging process, whose materials and production process can also be monitored in a block chain. On the packaging appropriate labels can be as well as a QR code, with which it is possible to save a variety of data in a smallest space. Wholesalers and retailers can add additional transportation and delivery conditions. In particular, retailers can better calculate freshness and shelf life using blockchain technology and plan deliveries more predictable. Consumers can use their smartphones to read out the appropriate metadata, resulting in a far-reaching, transparent process (Esteki et al., 2019; Pigini & Conti, 2017). We are just at the beginning: The linking of the digital data with 49
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the goods is only partially resolved in these days. Therefore, some researchers are currently working on a clear labeling of foods. The approaches range from consumable additives (Liang, 2013; Puddu, Paunescu, Stark, & Grass, 2014), which are added directly into the food, to the use of RFID chips, with which it is possible to reproduce at what time and at which place a product is located. At the same time, the RFID chips can serve as sensors (Shanahan et al., 2009). In addition, the establishment of standards and norms (for example, the generation of an appropriate consensus mechanism) is necessary. These include, among other things, the granting of reading and writing rights, so that a central supervisory authority is still required. In addition, it must be ensured that third parties cannot tap the confidential data. This implies the introduction of a general security system (Ge et al., 2017).
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5. Conclusion The implementation of blockchain technology combined with IoT approaches, can revolutionize the food industry. Participating companies are aware of the potential of those new technologies. Therefore, some retailers are already beginning to make demands on their suppliers to use blockchain technologies to enable a more transparent supply chain as well as a greater food security. This concerns traceability, in order to prevent contamination of the food as far as possible or to be able to record sources of input more quickly and to reduce the high proportion of food adulterants. However, it should not be forgotten that changes could still be carried out directly on the food. Especially during the first initial steps of the raw material production, clever manipulations are conceivable. In addition, it must be ensured that the food and the blockchain data are linked together and that no exchange can take place. The direct labeling of foodstuffs using synthetic, but nontoxic ingredients are considered by many consumers to be problematic. Therefore, there is still a need for additional methods and analytical technologies to meet the high demands of food. In addition, there are some challenges that need to be addressed in dealing with sensitive data and the digital storage capacity that this technology requires. This also includes a complex transformation of the working world and the current process flow primarily for small and mediumsized companies as well as the implementation of required standards and interfaces for data transmission. Due to the complexity, the full establishment of blockchain technologies is likely to take some time. Conflicts of interest The authors declare no conflicts of interest related to this article. Funding The idea of this article is based on the scientific joint project “Food Profiling” (funding code: 2816500914) funded since 2016. The project is supported by funds of the Federal Ministry of Food and Agriculture (BMEL) based on a decision of the Parliament of the Federal Republic of Germany via the Federal Office for Agriculture and Food (BLE) under the innovation support programme. The consortium is headed by the HAMBURG SCHOOL OF FOOD SCIENCE. The focus lays on developments in the area of instrumental analysis for the authentication of foodstuffs. References Abad, E., Palacio, F., Nuin, M., Zárate, A. G. d., Juarros, A., Gómez, J. M., et al. (2009). RFID smart tag for traceability and cold chain monitoring of foods: Demonstration in an intercontinental fresh fish logistic chain. Journal of Food Engineering, 93(4), 394–399. https://doi.org/10.1016/j.jfoodeng.2009.02.004. Anderson, R. (1996). The eternity service. Proceedings of Pragocrypt, 96, 242–252. Bachmann, R., Klockmann, S., Haerdter, J., Fischer, M., & Hackl, T. (2018). 1H NMR spectroscopy for determination of the geographical origin of hazelnuts. Journal of
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