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Digital Object Identifier 10.1109/ACCESS.2017.DOI
Smart Contract-Based Agricultural Food
Supply Chain Traceability
LU. WANG1,2,3, LONGQIN. XU1,2,3,4,5 , ZHIYING. ZHENG1,2,4, SHUANGYIN.
LIU1,2,3,4,5,6,XIANGTONG. LI1,2,5,LIANG. CAO1,2,3,4,5,JINGBIN. LI6,AND CHUANHENG SUN7
1College of Information Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, China
2Smart Agriculture Engineering Technology Research Center of Guangdong Higher Education Institutes, Zhongkai University of Agriculture and Engineering,
Guangzhou, 510225, China
3Guangzhou Key Laboratory of Agricultural Products Quality & Safety Traceability Information Technology, Zhongkai University of Agriculture and
Engineering, Guangzhou 510225, China
4Academy of Smart Agricultural Engineering Innovations, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China
5Guangdong Province Key Laboratory of Waterfowl Healthy Breeding, Guangzhou 510225, China
6College of Mechanical and Electric Engineerings Shihezi University, Shihezi, 832000, China
7National Engineering Research Center for Information Technology in Agriculture, Beijing, 100097, China
Corresponding author: SHUANGYIN. LIU (e-mail: hdlsyxlq@126.com)
This work was supported in part by the National Natural Science Foundation of China under Grants 61871475; in part by the Special
Project of Laboratory Construction of Guangzhou Innovation Platform Construction Plan under Grant 201905010006; the Guangdong
Science and Technology Plan of Project under Grant 2017B0101260016; the Foundation for High-level Talents in Higher Education of
Guangdong Province under Grants 2017GCZX0014, 2016KZDXM0013, 2017KTSCX094, and 2018LM2168; Guangzhou Science and
Technology Project 201903010043; and the Beijing Natural Science Foundation under Grant 4182023.
ABSTRACT The complexity of a supply chain makes product safety or quality issues extremely difficult
to track, especially for the basic agricultural food supply chains of people’s daily diets. The existing
agricultural food supply chains present several major problems, such as numerous participants, inconvenient
communication caused by long supply chain cycles, data distrust between participants and the centralized
system. The emergence of blockchain technology effectively solves the pain-point problem existing in
the traceability system of agricultural food supply chains. This paper proposes a framework based on
the consortium and smart contracts to track and trace the workflow of agricultural food supply chains,
implement traceability and shareability of supply chains, and break down the information islands between
enterprises as much as possible to eliminate the need for the central institutions and agencies and improve
the integrity of the transaction records, reliability and security. At the same time, farmers record details of
the environment and crop growth data in the InterPlanetary File System (IPFS) and store file IPFS hashes in
smart contracts, which not only increases data security but also alleviates the blockchain storage explosion
problem. This framework has been applied in Shanwei Lvfengyuan Modern Agricultural Development
Co., Ltd. Although there are still many defects, the framework has successfully realized functions such as
disintermediation and tracing of agricultural product information through QR codes. Thus, the framework
proposed in this paper is of great significance and reference value for enterprises to ensure product quality
and safety traceability.
INDEX TERMS Blockchain, smart contract, agricultural food supply chain, traceability, food safety.
I. INTRODUCTION
The supply chain connects many entities, such as supplier-
s, logistics providers, processors, distributors, retailers, and
consumers, forming a complex network chain structure. This
complex supply chain may go through dozens or even hun-
dreds of stages, leading to considerable time consumption
and involving a wide range of regions. Therefore, in this case,
if the product has safety or quality problems, the traceability
process is extremely difficult. Especially in agricultural food
supply chains, the process ensures the traceability of the final
products, which not only guarantees consumer life and health
but also improves user trust in the product and enterprise.
In recent years, prevalent food safety accidents have caused
people to devote more attention to food safety and quality.
However, the current agricultural food supply chains are
characterized by a long life cycle, numerous and complex
links, and dynamic information, etc., so it is difficult to track
and trace problems in a certain link. Agricultural foods are
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foods produced by agriculture, such as sorghum, rice, peanut-
s, corn, and wheat, which form the basis of people’s daily
food, and their importance is self-evident. Subsequently, it is
very important to establish and improve the agricultural food
supply chain traceability system "from farm to fork" [1]–[3].
There are three major problems with the existing agricul-
tural food supply chains. First, there are many participants in
the supply chain, and the communication between them is not
convenient, leading to a long cycle of the whole supply chain.
Then, due to the large number of participants and distribution
in different links, the information sharing is poor, and data
is not trusted among participants. Finally, the agricultural
food supply chain is a centralized system with power con-
centrated on the central manager and data easily tampered
with. Although the central manager is under the supervision
of government departments, there are always loopholes in
human supervision [1], [4]–[6]. By reason of this situation, in
order to effectively track product information, ensure product
safety and quality, and thus ensure the safety of consumers,
the research on advanced traceability technology and its sys-
tems wields important research value to guarantee the quality
and safety of agricultural food. To date, many researchers
have studied and developed supply chain traceability systems
based on barcodes, QR codes and radio frequency identifi-
cation devices (RFID), but most of these systems still have
some problems. First, most of the traceability systems are
develop based on a single enterprise, which is an internal
traceability system by which information is not easily shared.
Second, the majority of traceability systems are based on
centralized development, and the information is opaque and
asymmetric, with the risk of tampering by the administrator
and low credibility. Finally, existing traceability systems have
a single point of failure, and once a node fails, the whole
system will crash. The emergence of blockchain technology
effectively solves the pain point of the existing agricultural
food supply chain traceability systems.
Blockchain is a distributed ledger system which consists of
one-by-one blocks with timestamps in the form of a decen-
tralized database in the point-to-point (P2P) network. There-
fore, it has the characteristics of decentralization, immutabil-
ity, anti-tampering and traceability. Blockchain technology is
introduced into the agricultural food traceability system to
track the information of the supply chain process, offering
the advantages of reducing the management cost, improving
the information credibility, realizing the visualization of the
supply chain process data and the traceability of the infor-
mation, etc. [2], [7]–[10]. In view of the many advantages
of blockchain, the research on traceability systems based
on blockchain is growing rapidly [11]. In the medical field,
Yong et al. [12] developed a "vaccine blockchain" system
based on the blockchain and machine learning technology,
and can be used to address the problems of vaccine expiration
and vaccine record fraud by using the traceability and smart
contract of the blockchain. Tripathi et al. [13] proposed an
smart healthcare system framework based on blockchain to
provide a secure and privacy-protecting healthcare system.
In the field of protecting privacy, Chen et al. [14] proposed
a novel on-chain and off-chain data storage model and de-
veloped a prototype system to verify the feasibility of the
model, thus solving the problems of information redundancy
and insufficient storage space in blockchain. However, this
framework is only applicable to personnel information man-
agement system and has not been extended to more fields.
Yang et al. [15] proposed a blockchain privacy-preservation
crowdsensing system, which solves the risk that the existing
crowd-testing system is vulnerable to attack, invasion and
manipulation. In the field of traceability, Liu et al. [16],
with respect to the background of cross-border e-commerce,
proposed a framework based on blockchain and developed
a set of corresponding technologies and methods to realize
product traceability and transaction traceability in supply
chain management. The key methods and algorithms, such as
the information anchoring method, key distribution method,
information encryption algorithm and anti-counterfeiting al-
gorithm, are developed to solve the key recovery problem
and effectively resist clone attack, counterfeit label attack
and counterfeit product attack. However, this system is not
implemented for actual business. Baralla et al. [17] pro-
posed a traceability system for agricultural product supply
chains based on the blockchain hyperledger Sawtooth tech-
nology, which implements the EU’s "farm-to-fork" model.
Consumers can learn detailed product information through
QR code scanning and verify product quality and safety.
However, the Sawtooth technology is not mature enough and
lacks materials and applications. Yu et al. [18] designed a foot
ring based on blockchain and RFID technology to solve the
problem of poultry food safety, which is conducive to timely
detection of health problems in the poultry breeding process,
and helps consumers to track information and quickly locate
specific links in the poultry breeding life cycle when prob-
lems occur. Nevertheless, RFID technology is not mature
enough and exhibits insufficient security and excessive cost:
it is thus not practical for the full application to large poultry
farms. Based on the research of RFID and blockchain tech-
nology, Tian [19] established a traceability system for agri-
cultural food supply chains which covers the whole process
of data collection and information management of all links
of the entire supply chain, and also realizes the quality and
safety monitoring, traceability and traceability management
of agricultural supply chains. Similarly, because of the same
shortcomings as those of the previous paper, the system
cannot be widely used in all fields.
This paper proposes a framework based on consortium
chain and smart contracts to track and trace workflows in
agricultural food supply chains, implement traceability and
shareability of supply chains, and disrupt information islands
between enterprises as much as possible to eliminate the
need for the central agencies and intermediaries and improve
the transaction record integrity, reliability, and security. At
the same time, farmers record the environmental information
and details of crop growth data into the InterPlanetary File
System (IPFS). The file IPFS hash is stored in the smart
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contracts, which not only increases the data security but also
alleviates the blockchain storage explosion problem. Besides,
this framework has been applied in Shanwei Lvfengyuan
Modern Agricultural Development Co., Ltd. Although there
are still many defects, it has successfully achieved decentral-
ization and traced the information of agricultural products
through QR codes, which will be briefly introduced in the
following article.
The remainder of this paper is organized as follows.
Section 2 reviews the related work. Section 3 introduces
some basic knowledge. In Section 4, we discuss the design,
system overview and entity sequence diagram. Then, Section
5 describes implementation details including algorithms for
agricultural food sales between various participants using
smart contracts. Finally, Section 6 presents the conclusions.
II. RELATED WORK
Food is the basis of people’s survival, and food safety is
closely related to people’s health: thus, people are devoting
increasing attention to food safety. In recent years, experts
have become more interested in food traceability. The first
technology applied to food safety traceability is Internet of
Things (IoT) technology [20], [21], such as barcodes, QR
codes, and RFID technology. Li et al. [22] proposed a food
traceability system for the dairy supply chain based on QR
codes, which improves the transparency from production to
sales and builds a food traceability platform. However, QR
codes are not suitable for living bodies, such as poultry
and waterfowl, and are easily damaged by pollution. RFID
is the most widely used technology in the IoT to realize
food traceability due to its low cost and small size. Zhao
et al. [23] developed an RFID-based pork supply chain
traceability system. A set of pork quality monitoring and
tracking systems was constructed by using Structured Query
Language (SQL) Server 2000 and intelligent identification
technology to realize the information traceability of the
entire pork production process. Zhang et al. [24] designed
a complete life cycle food traceability system, which uses
RFID technology to realize whole process monitoring from
source to consumption. At the same time, the RFID fault-
tolerant mechanism is designed to ensure the practicability
of the system. Saikat Mondal et al. [25] used object-based
validation protocols, real-time quality monitoring with RFID
sensors at the physical level, and blockchain technology
at the network level to create a transparent food supply
chain. However, RFID technology also presents some de-
fects such as immature technology, high cost, inconsistent
technical standards and low security. In addition, most of
the traceability system data based on the IoT are stored
in SQL Server and other central databases, which leads to
problems like information asymmetry, data tampering and
escalating data volume, thus increasing the cost of centralized
storage. Blockchain technology has the characteristics of
decentralization, immutability, anti-tampering and traceabil-
ity. The application of blockchain technology in agricultural
food safety traceability systems can store traceable data in
chronological order, which is conducive to solving the prob-
lems remaining in the existing agricultural food traceability
systems.
As a result, the combination of blockchain technology and
food traceability has become a new trend in recent years. Tian
[26] proposed the traceability of food supply chains based
on hazard analysis and critical control points (HACCP) by
combining blockchain and IoT. IoT technology automatically
collects and stores information, improves the reliability of
information and enhances food safety. Blockchain can ensure
that data will not be tampered with after the chain, which
improves the authenticity of the traceability information.
However, since data quantities are constantly increasing, the
blockchain cannot hold all of it. Hao [27] studied a traceabili-
ty storage scheme using IPFS and secondary databases. IPFS
is a technique for storing and sharing data in a distributed
file system. To retrieve data from the IPFS, the transaction
hash must be accesssed from the secondary database and then
the IPFS hash must be retrieved from the blockchain. This
approach solves the blockchain data explosion problem, but
if the secondary database fails, the entire system will fail.
With the advent of the blockchain 2.0 era, the self-
execution and self-verification features of smart contracts
have made them widely used in food safety traceability sys-
tems. Wang et al. [3] proposed a product quality management
system that uses smart contracts technology to permanently
record all product transactions. In [28], the author present-
ed a collaborative food safety traceability system based on
blockchain and EPCIS, and adopted enterprise-level smart
contracts to solve problems such as disclosure of sensitive
information, data tampering and trust transfer. At the same
time, the system also adopts the dynamic management of
data on and off the chain to alleviate the problem of data
explosion on the blockchain. Salah et al. [2] researched a
method of using blockchain and smart contracts to execute
business transactions, so as to realize traceability and vis-
ibility in the soybean supply chain. The solution aims to
eliminate a trusted centralized authority, provide transaction
records, and use smart contracts to manage and control
transaction interactions between participants in the soybean
supply system. These transactions are recorded and stored
on the blockchain and connected to the IPFS, providing
transparency and traceability to the soybean supply chain
system in a safe and reliable manner. The huge advantage
of smart contracts is not only widely used in food safety
traceability. Omar et al. [29] presented a method based on
blockchain, using Ethereum smart contracts and decentral-
ized storage system to automate processes and information
exchange, and capture the detailed algorithm of interaction
between supply chain stakeholders, provides them with a
compact, safe, reliable and transparent communication mode,
has solved the Vendor Managed Inventory operation of data
integrity, transparency, traceability and single point of failure.
Zhang et al. [30] proposed a novel secure billing protocol for
online ride-hailing vehicles, which solved the difficult prob-
lem of fare estimation and automatic payment through smart
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contracts. Xuan et al. [31] proposed a data sharing incentive
model based on evolutionary game theory using blockchain
with smart contracts, which could dynamically control the
excitation parameters and continuously encourages users to
participate in data sharing. Tso et al. [32] introduced the first
decentralized electronic voting and bidding systems based
on a blockchain and smart contract, which improved the
anonymity of participants, privacy of data transmission, and
reliability and verifability of data.
The consortium chain is a kind of blockchain which is
managed by multiple organizations or institutions, and the
data can only be read, written and maintain by these organi-
zations or institutions. This disrupts the information island-
s between enterprises and is very suitable for agricultural
food safety traceability systems. Ethereum and hyperledger
are two popular consortium chain platforms [2] based on
Ethereum, while Wal-Mart [33], the world’s largest retail-
er, is experimenting with food traceability through IBM’s
hyperledger. Taking advantage of the key features of the
blockchain and smart contracts, Shahid [34] deployed the
Ethereum blockchain network to propose a blockchain-based
reputation system in the agricultural and food supply chain.
In [35], the authors proposed a decentralized storage mech-
anism based on Ethereum. The use of IPFS overcomes the
problems of centralized storage of sensitive data leaks and
single points of failure. Before the data is stored in IPFS, the
file is encrypted using the file encryption algorithm, and the
ciphertext is uploaded to IPFS, which provides the hash value
of the stored file recorded in Ethereum. However, due to the
increased computing overhead, the proposed solution will not
work effectively in an IoT scenario.
III. PRELIMINARIES
A. BLOCKCHAIN
As we mentioned above, blockchain is a distributed ledger
system that consists of one-by-one blocks with timestamps
in the form of a decentralized database in the P2P net-
work [23], [24]. As the underlying technology of Bitcoin,
blockchain technology has gradually emerged into the public
consciousness. Although this new concept has become a hot
topic in recent years, in fact, some technologies it relies on,
such as asymmetric encryption technology and P2P network
protocol, have existed for a long time. However, blockchain is
a good combination of encryption technology, consensus al-
gorithm, timestamp technology and smart contracts, forming
a distributed system where users can be anonymous and data
can be trusted. It offers the advantages of decentralization,
immutability, anti-tampering and traceability, etc. It is widely
applied in the fields of medical treatment, education, credit
and supply chain traceability. Fig. 1 shows the blockchain
structure.
As can be observed from the diagram, the connection
between blocks is produced by the hash value of the previous
block, which is the unique identifier of each block. In this
way, the connection from the latest block to the first block
is created by the sequence of each block to its parent hash
Header
Body
Block m-1
Header
Body
Block m
Version
Number Nonce Timestamp
Previous Block
Hash
Block
Difficulty
Merkle Tree
TX1 TX2 TX3 TX4
Hash1 Hash2 Hash3 Hash4
Hash12 Hash34
Block m+1
ȭȭ ȭȭ
Header
Body
FIGURE 1: The Structure of Blockchain.
value, creating a form similar to a data structure. The block
consists of a header and a body. The header contains a ver-
sion number, nonce, timestamp, previous block hash, block
difficulty and Merkle tree. The block difficulty determines
the difficulty of mining. The nonce is the answer to the math
problem the miners are looking for, and the previous block
hash is used to connect the previous block. The timestamp
is the generation time of each block, which corresponds
to the authentication of each transaction record, ensuring
the authenticity of the transaction record. The body mainly
contains transaction data.
The Merkle tree appears to be very similar to a binary tree,
and it can summarize and quickly verify all transaction data
in a block. Each leaf node uses the hash of the data block as
its tag, and each non-leaf node uses the encrypted hash of its
child node’s tag as its tag. As shown in the body area of the
diagram, the respective hash values of each transaction are
taken as leaf nodes, and the hash values of the two leaf nodes
are combined for another hash calculation to generate the
parent node, namely the Merkle root. When the transaction
records are tampered with, the value will be inconsistent.
Such a storage method not only enables the blockchain to
quickly discover that the information has been tampered with
but also enables it to quickly locate the specific transaction
information.
B. CONSORTIUM CHAIN
The blockchain is divided into public chain, private chain and
consortium chain. In the public chain, anyone can send trans-
actions and participate in the consensus process. The whole
network is open, without authorization, and characterized by
"complete decentralization". The private chain is generally
the blockchain within the enterprise, whose authority is com-
pletely in the hands of an organization or a person, with
the lowest degree of decentralization. The consortium chain
exists between the public chain and the private chain and is
a special blockchain requiring registration and permission:
it is only open to specific organizations or institutions, so
it can maintain the distributed structure, limit the number
of participants, and can only be verified in the blockchain
through pre-set nodes, thus enhancing security. The consen-
sus algorithm is implemented by validating data and blocks
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through pre-selected nodes rather than by all nodes in the
entire network, which accelerates the generation of blocks
and shortens the time to reach consensus and validate data.
Therefore, the consortuim chain exhibits characteristics such
as few consensus nodes, high system operation efficiency and
rapid transaction speed. Agricultural food traceability sys-
tems have high requirements with respect to privacy protec-
tion, transaction speed and internal supervision: if every par-
ticipant joins the consortium chain, these systems combined
with the smart contracts technique can effectively solve the
issue that existing agricultural food traceability systems are
established on the basis of a single enterprise development,
thus disrupting the information islands between enterprises to
make the adoption of consortium chains in agricultural food
traceability systems more suitable [36]–[40].
C. HYPERLEDGER
Hyperledger is an open source collaborative project initiated
by the Linux Foundation in 2015 to promote blockchain
digital technology and transaction verification. It is the first
distributed ledger platform for enterprise application sce-
narios, involving technology and financial giants such as
IBM, Intel, Cisco, and R3. Hyperledger can be divided into
distributed ledger technology, libraries and tools. Fabric is the
most important application project of Hyperledger technolo-
gy, which is a general license blockchain with modular and
extensible characteristics, follows the execution-sequence-
validation paradigm and fundamentally deviates from the
order-execution model. Fabric consists of four parts: (1)
Describing the roles between nodes in the infrastructure; (2)
Execution of the smart contracts; (3) Configurable consensus;
(4) Membership services, whose modular structure provides
a high degree of confidentiality, flexibility and extensibility
applicable to any industry [41], [42]. HyperLedger establish-
es consortium chain through channel and uses membership
service provider(MSP) to control the permissions of nodes.
As an important communication mechanism, channel is an
independent communication channel between members that
transactions sent in it can only be seen by members belong-
ing to the channel. There can be multiple channels in the
network, and each channel maintains an account of its own
channel.
IV. AGRICULTURAL FOOD TRACEABILITY BASED ON
BLOCKCHAIN
In this section, we use the hyperledger fabric to build consor-
tium chain and smart contracts named chaincode to track and
execute transactions in the agricultural food supply chain.
This method eliminates the need for a central authority,
realizes decentralization, and provides complete, reliable and
secure transaction records for the management and security
of the agricultural food supply chain, ensuring the authen-
ticity and reliability of the agricultural food information that
ultimately reaches the consumer.
A. SYSTEM OVERVIEW
Smart contracts have the ability to integrate agricultural and
agricultural food safety into an integrated intelligent system,
thus ensuring the quality and safety of agricultural food and
the health of consumers. This paper presents a framework
for the use of automated smart contracts on the hyperledger
platform. According to the information in the agreed contrac-
t, when the trigger condition is met, the smart contracts au-
tomatically send out the preset data resources, including the
events of the trigger condition. This is a system of transaction
processing modules and state mechanisms that do not gener-
ate or modify smart contracts but only enable a complex set
of digital commitments with trigger conditions to be executed
correctly according to the will of the participants. Smart con-
tracts are executed by tens of thousands of nodes distributed
around the world and are the result of consensus. Nodes are
one of the components of the blockchain network, namely,
participating entities in the agricultural food supply chain.
These nodes can collect, validate, and execute transactions,
and store the data and results of these transactions in a ledger,
which will eventually be replicated and synchronized by all
nodes. As a result, all nodes have the same ledger information
without contingency. As mentioned earlier, smart contracts
receive transactions and trigger events in the form of function
calls, enabling participating entities to continuously monitor,
track, and receive appropriate alerts when violations occur.
Fig. 2 depicts a general overview of the system architecture
presented in this paper, with the main participating entities
including the agricultural bureau, farmer, processor, qual-
ity supervision bureau, distributor, retailer, consumer, and
blockchain implementing smart contracts.
As shown in Fig. 2, in order to achieve traceability of
agricultural food, information is recorded using hyperledger
smart contracts, and all participants in the agricultural food
supply chain are added to the process. The agricultural bureau
records farmer information, seed information, plot informa-
tion and yield information, etc., and carries out unified man-
agement of farmers’ production to ensure the authenticity of
source information. Farmers cultivate crops and record the
environment and growth detail data of the crops in IPFS,
where the growth images of the crops are marked with
timestamps. Timestamps represent complete and verifiable
data that already exists at a given point in time, providing
the user with electronic proof of when some of the user’s data
was generated. The file IPFS hash is stored in smart contracts.
When the crops mature, the farmer harvests them and then
sells them to a processor for a series of processing steps.
The quality supervision bureau supervises the processing to
ensure the safety and quality of agricultural food. The fin-
ished agricultural foods are purchased in bulk by a distributor,
stored and sold to a retailer, who buys agricultural food from
a distributor and sells it directly to the customer in small
quantities.
Data stored in the blockchain or IPFS is encrypted by
the entity storing the data using a digital signature, which
offers the following advantages: (1) Anti-tampering: After
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Hyperledger smart contract
IFPS
Farmer Processor Distributor Retailer Customer
crop detail
informations
Agricultural bureau Quality supervision bureau
supervise
informations
transaction
informations
transaction
informations
transaction
informations
transaction
informations
transaction
informations
manage
informations
FIGURE 2: A system overview for agricultural food trace-
ability using hyperledger smart contracts.
signing, the authenticity of the data is determined through
the calculation and verification of the signature to ensure the
integrity of the data; (2) Non-repudiation: A digital signature
can be used as the identity authentication of the stored
data entity, or as the evidence of the signer’s operation; (3)
Confidentiality: Data loss is likely to lead to data leakage, but
the digitally signed data needs to be decrypted to obtain the
original data. Entities are responsible for their own data, the
blockchain automatically executes programs through smart
contracts, and entities will execute punishment measures if
they commit illegal activities. In the planting stage, farmers
use a variety of sensors to upload the growing environment
information and details of crops directly to the server in real
time. The data is not processed by human beings, which
enhances the authenticity and anti-tampering characteristic
of the data and enables the data to be audited and trusted.
B. SYSTEM DESIGN
The agricultural food supply chain completes the entire
production and transportation process "from farm to fork",
involving many participating entities, and forming long and
complex characteristics that make tracking the entire process
very cumbersome. Therefore, for traceability purposes, we
record the information and add the unique identity and lot
number of the food to each subsequent transaction when the
transaction is initiated, and record the hash value to ensure
the authenticity of the transaction. A batch is a group of
foods in a warehouse whose batch number is the unique
identifier. To address the blockchain data explosion and IPFS
limitations, the hash of the data is stored in the hyperledger,
and the transaction data is stored in the IPFS. Access control
policy is adopted to restrict blockchain reads and writes,
ensuring that transactions are executed by authorized users
and enhancing data security. Similarly, smart contracts allow
only specific entities to execute. Entities are registered in
the system and interact through the smart contracts. The
processing of the entity in the agricultural food supply chain
is shown in Fig. 3, and the description of each entity is as
follows:
Agricultural bureau: The agriculture bureau is an orga-
nization that manages farmers, keeping records of farmers’
information, seed information, plot information and yield
Farmer Processor Distributor Retailer Consumer
Agricultural bureau Quality supervision
bureau
FIGURE 3: The simple agricultural food process in the
agricultural food supply chain.
information to ensure the authenticity of source information.
The information is stored in the IPFS, and its hash value is
stored on the chain.
Farmer: The farmer is responsible for planting crops,
using sensors to monitor and record details of crop growth,
such as water, air, sunlight and soil quality in the growing
environment, and storing the information regarding the pro-
cess of crop growth in IPFS in the form of images or MPEG
files. In addition, the farmer is responsible for creating smart
contracts and storing IPFS data hashes in smart contracts.
Processor: The farmer harvests crops and sells them to
the processor, who processes the raw crops into produce
purchased by the final consumer, and stores the batch infor-
mation, quantity, and inspection information of the finished
products in IPFS. The data hash is stored in the blockchain,
and the data label is finally generated and pasted on the
product packaging.
Quality supervision bureau: The quality supervision bu-
reau mainly manages the processing and guides the quality
supervision and inspection, and is responsible for the im-
plementation of product quality supervision and compulso-
ry inspection of the production enterprises. To investigate
and punish violations of laws and regulations concerning
standardization, measurement and quality, and crackdown on
illegal activities related to counterfeiting and shoddy goods,
its information is recorded on the IPFS, and the hash value is
stored on the blockchain.
Distributor: The finished product may go through mul-
tiple levels of distribution before reaching the retailer. The
distributor is responsible for storing processed agricultural
products and selling them to retailers in batches. Company
information, product selling time, price and other informa-
tion is stored in IPFS, and like the situation for the quality
supervision bureau, the hash value is stored in blockchain to
ensure that the subsequent data is not tampered with.
Retailer: The retailer buys processed produce from the
distributor and sells it in small quantities to consumers. Basic
information of the retailer, time of selling, quantity sold and
other information is recorded in IPFS, and the hash value is
also recorded in the blockchain.
Customer: Consumers are the users who purchase and
consume the final agricultural food, and can obtain the
complete supply chain information of the agricultural food
according to the barcode, RFID or QR code on the product
package to realize the traceability function of agricultural
food information.
6VOLUME 4, 2016
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
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10.1109/ACCESS.2021.3050112, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
+Farmer Add:string
+Date Sold:date
+Processor Add
+createContract()
+updateGrowthInfo()
+sellToProcessor
Smart Contract Attributes
1
1
+Processor Add:string
+Farmer Add:string
+Purchase Date:date
+Quantity:int
+buyCropFromFarmer()
+sellAgriFoodToDistributor()
1
+Distributor Add:string
+Processor Add:string
+buyAgriFoodFromProcessor()
+sellAgriFoodToRetailer()
n
n
+Retailer Add:string
+Purchase Date:date
+buyAgriFoodFromDistributor()
+sellAgriFoodToCustomer()
1
+Customer Add:string
+Purchase Date:date
+Retailer Add:string
+buyAgriFoodFromRetailer()
1
n
1
n
n
1
n
n
1
Smart Contract Fuctions
1
FIGURE 4: Entity relationship diagram.
C. ENTITY SEQUENCE DIAGRAM
The relationships between entities, as shown in Fig. 4, show
some of the key properties and capabilities of the smart
contracts, as well as the relationships between entities and
smart contracts. Each participating entity in the agricultur-
al food supply chain participates by calling a function in
the smart contracts. The smart contracts are created by the
farmer, who grows the crop and uploads the growing envi-
ronment, details and images to the IPFS by calling update-
GrowthInfo(), which is stored in the IPFS hash, and updates
the updateGrowthInfo() until the crop is ready for harvest.
When the crops are harvested, the trade begins between the
farmer and the processor. Once the farmer and the processor
have negotiated the details of the agreement, the farmer
agrees and sells the crop to the processor. Fig. 5 shows
the sequence diagram of the farmer and processor executing
the sellToProcessor() and buyCropFromFarmer() functions,
respectively. First, the processor executing the buyCropFrom-
Farmer() function, passing processor address, quantity and
sales date parameters to activate the smart contract trigger the
CropRequested() event to notify the participants, and passing
and recording these parameters. Then, the farmer executing
the sellToProcessor() function, passing the farmer address,
processor address, quantity and sales date parameters, the
smart contract trigger the CropSold() event to notify closing
the transaction, and passing and recording these parameters.
Fig. 6 shows a sequence diagram of the processor and dis-
tributor collaboration using smart contracts. The distributor
is a warehouse that buys processed produce in bulk from
various processors and sells it to retailers. Firstly, the distribu-
tor trigger AgriFoodRequestedByDistributor() event, passing
distributor address, processor address, quantity and sales date
parameters to notifies the processor selling agricultural food
to it, then the farmer performs the sellAgriFoodToDistrib-
utor() function, passing processor address, distributor ad-
dress, sales quantity and sales date parameters to activate
Smart Contract ProcessorFarmer
createContract()
ContractCreated()
updateGrowthInfo()
CropGrowthInfoUpdated()
buyCropFromFarmer()
CropRequested()
sellToProcessor()
CropSold()
Functions
Events
FIGURE 5: Sequence diagram showing interactions among
farmers, smart contracts, and processors.
Smart Contract DistributorProcessor
buyAgriFoodFromProcessor()
AgriFoodRequestedByDistributor()
sellAgriFoodToDistributor()
AgriFoodSoldToDistributor()
Functions
Events
FIGURE 6: Sequence diagram showing interactions among
processors, smart contracts, and distributors.
the AgriFoodSoldToDistributor() event to notify interaction
entities. Retailers buy agricultural food from distributors,
executing the buyAgriFoodFromDistributor() function, and
passing retailer address, distributor address, quantity param-
eters. The activation AgriFoodRequestedByRetailer() event
notifies the distributor, the distributor then performs the
sellAgriFoodToRetailer() function to sell agricultural food
to the retailer, and activated event AgriFoodSoldToRetail-
er() notifies the relevant participant of this process. At the
same time, passing the addresses of both parties, quantity,
batch number and sales date parameters. Finally, the retailer
sells the agricultural food to the customer by executing the
sellAgriFoodToCustomer() function, passing retailer address,
customer address, agri-food name and sales date parameters,
and broadcasts the process for the agricultural food via the
AgriFoodSold() event. Fig. 7 shows a sequence diagram of
distributor, retailer and customer.
V. IMPLEMENTATION
As mentioned above, the smart contracts are created by the
farmer. In the initial state of establishing the smart con-
tracts, the smart contracts will check whether the farmer is
registered. The processor then issues a purchase request, at
which time the contract status is buyCropFromFarmer, and
two conditions need to be checked: (1) Whether the requested
VOLUME 4, 2016 7
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10.1109/ACCESS.2021.3050112, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
Smart Contract RetailerDistributor
buyAgriFoodFromDistributor ()
AgriFoodRequestedByRetailer()
sellAgriFoodToRetailer()
AgriFoodSoldToRetailer()
Functions
Events
Customer
buyAgriFoodFromRetailer ()
AgriFoodRequestedByCustomer()
sellAgriFoodToCustomer()
AgriFoodSold()
FIGURE 7: Sequence diagram showing interactions among
distributors, smart contracts, retailers and customers.
Input:
þ
rp
ÿ
is the list of registered Processors
Address of Processor,
Address of Farmer,
Quantity,DatePurchased,CropPrice
1 Contractstate is buyCropFromFarmer
2 State of the processor is CropRequested
3 Farmer state is WaitForSellCropToProcessor
4 Restrict access to only rp ę Processor
5 if CropSale is agreed and CropPrice = paid then
6 Contract state changes to CropRequestAgreed
7 Change State of the processor to
WaitForCropFromFarmer
8 Farmer state is SellCropToProcessor
9 Send a notification of crop sale to processor
10 end
11 else
12 Contract state changes to CropRequestFailed
13 State of processor is RequestFailed
14 Farmer state is CancelRequestOfProcessor
15 Send a notification stating request failure
16 end
17 else
18 Reset contract and displays an error message.
19 end
Algorithm 1 Farmer Sell Crops To Processor
processor is a registered entity; (2) Whether the processor has
paid the fee. If these two conditions are satisfied, the contract
status changes to CropRequestAgreed, the processor status
is now WaitForCropFromFarmer, the farmer status changes
to SellCropToProcessor and all active entities receive infor-
mation from the farmer about selling crops to the processor.
If the above two conditions are not met, the contract state
becomes CropRequestFailed, the processor state is Request-
Failed, and the farmer state is CancelRequestOfProcessor.
Algorithm 1 describes the process by which farmers sell their
crops to processors.
The processor then sells the processed crop to a distributor,
who in turn sells it to retailer, as shown in algorithm 2. At
this point, the production date, sales quantity and purchase
date of the agricultural food are important parameters of the
current stage. First, with respect to recognition address and
the states of the distributor and retailer, due to the distrib-
Input:
þ
rr
ÿ
is the list of registered Retailer
Address of Distributor,
Address of Retailer,
DateManufactured, Quantity,
DatePurchase
1 Contractstate is AgriFoodSoldToDistributor
2 State of the distributor is AgriFoodReceivedFromProcessor
3 Retailer state is ReadyToPurchase
4 Restrict access to only rr ę Retailer
5 if Sale is agreed and Price = paid then
6 Contract state changes to SaleRequestedSuccess
7 Change State of the distributor to
AgriFoodSoldToRetailer
8 Reatailer state is AgriFoodDeliveredSuccess
9 Send a þsuccessÿnotification to retailer .
10 end
11 else
12 Contract state changes to SaleRequestDenied
13 State of distributor is RequestFailed
14 Retailer state is AgriFoodDeliveryFailure
15 Send a þfailureÿnotification to all participants.
16 end
17 else
18 Reset contract and displays an error message.
19 end
Algorithm 2 Distributor Sell Agri-Food To Retailer
utor having just finished the trade with the processor, the
smart contract status is AgriFoodSoldToDistributor, and the
state of the distributor is AgriFoodReceivedFromProcessor.
The status of the retailer is ReadyToPurchase, which must
satisfy two conditions: (1) Whether the requested retailer
is a registered entity; (2) Whether to agree to the sales
agreement and whether the agricultural food payment has
been completed. If these two conditions are satisfied, the
contract will automatically execute the transaction with the
contract status changed to SaleRequestedSuccess, distributor
status changed to AgriFoodSoldToRetailer, and retailer status
changed to AgriFoodDeliveredSuccess. Upon completion of
the transaction, the deed will send a notification of successful
delivery to the retailer. If the above two conditions are not
satisfied, the contract status is changed to SaleRequestDe-
nied, the distributor status is changed to RequestFailed, the
retailer status is changed to AgriFoodDeliveryFailure, and the
contract sends a notification of failure to all participants.
Algorithm 3 describes the algorithm for consumers to pur-
chase agricultural food from retailers. First, the consumer’s
initial state is ReadyToBuy. Thanks to the successful dealings
between retailers and distributors, the smart contract state is
SaleRequestAgreedSuccess, while retailer status is AgriFood-
DeliveredSuccess. Similarly, smart contracts restrict cus-
tomers who register with retailer to make purchase requests.
The important parameters at this stage are customer address,
retailer address, purchase date, sales ID, and AgriFood ID.
When consumers successfully pay agricultural food prices,
contract status changes to AgriFoodSoldToCustomer, retailer
status to SuccessfulPurchaseAgriFoodSaleSuccess, and cus-
8VOLUME 4, 2016
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10.1109/ACCESS.2021.3050112, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
Input: Address of Retailer,
Address of Customer,
SalesID, AgriFoodID,
DatePurchased
1 Contractstate is SaleRequestAgreedSuccess
2 State of the retailer is AgriFoodDeliveredSuccess
3 Customer state is ReadyToBuy
4 Restrict access to only Customers
5 if Price = paid then
6 Contract state changes to AgriFoodSoldToCustomer
7 Change State of the retailer to
SuccessfulPurchaseAgriFoodSaleSuccess
8 Customer state is SuccessfulPruchase
9 Send a þpurchase successÿnotification.
10 end
11 else
12 Contract state changes to SaleOfAgriFoodDenied
13 State of retailer is AgriFoodSaleFailure
14 Customer state is FailedPurchase
15 Send a þpurchase failureÿnotification.
16 end
17 else
18 Reset contract and displays an error message.
19 end
Algorithm 3 Customer Buys From Retailer
tomer status to SuccessfulPurchase. If the payment is not
successful or the paid price is incorrect, the contract status
will be changed to SaleOfAgriFoodDenied, the retailer status
will be AgriFoodSaleFailure, and then the customer status
will be changed to FailedPurchase.
VI. RESULTS AND ANALYSIS
A. APPLICATION EXAMPLE INTRODUCTION
Shanwei Lvfengyuan Modern Agriculture Development Co.,
Ltd., is committed to crop planting, processing, and agricul-
tural technology promotion services, etc. Based on this, on
the basis of the field survey of the enterprise, a smart farm
cloud platform was built to manage and track the buckwheat
supply chain information. The system adopts browser/server
(B/S) structure, uses the VMware virtual machine to deploy
the blockchain network, and uses IPFS to store data with the
Hyperledger Fabric platform to realize distributed deploy-
ment. System development languages include Go, JavaScript,
HTML and CSS, with data processing and sending in JSON
format based on Nodejs and Bootstrap framework develop-
ment.
Fig. 8 shows the monitoring interface. Video monitoring
equipment and high-definition cameras are installed on the
farm. The administrator can remotely view and monitor
the crop situation and agricultural production situation in
real time. For the sake of reducing the use of agricultural
pesticides and ensuring the safety of agricultural food, the
early warning function for diseases and pests was designed.
An image recognition algorithm was adopted to match a
large number of image libraries of diseases and pests to
FIGURE 8: Monitoring interface.
FIGURE 9: Traceability interface.
quickly and accurately identify pests for early warning and
prevention.
Fig. 9 shows the crop traceability process, including up-
loading crop information and creating a QR code and attach-
ing it to the crop package. When the crops are transported
to the next link, the logistics manager can also check them
in the background, so as to clearly understand the flow
direction of the crops. In case of any problems, crops can be
locate quickly and rapidly recalled, thus effectively avoiding
the spread of crops with problems and greater losses being
suffered by the enterprise.
The information on the final product packaging purchased
by the consumer includes not only the product name, produc-
tion time and manufacturer’s name but also a pasted trace-
able QR code, such as the buckwheat traceability QR code
generated by the above platform as shown in Fig. 10. Upon
scanning the QR code, the information shown in Fig. 11 will
appear, including planting information, farm information,
enterprise qualification and on-link information, etc. This
platform can trace the entire life cycle of buckwheat from
planting to consumer, and guarantee the consumers’ right
to know almost all information. The cultivation, production
and processing of transparent buckwheat increase the trust
between consumers and enterprises. Meanwhile, the applica-
tion of blockchain technology also prevents data tampering.
In general, the platform built based on blockchain technology
realizes buckwheat information traceability, which increases
the trust between consumers and maximizes the interests of
both sides while also providing reference significance for
various researchers and enterprises.
VOLUME 4, 2016 9
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10.1109/ACCESS.2021.3050112, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
B. COST ANALYSIS AND PROBLEM DISCUSSION
Smart contracts in Ethereum exist in the form of accounts.
The successful deployment of a smart contract will create
a smart contract account. After that, the smart contract is
called, that is, a transaction is initiated to the smart contract
account, which consumes a number of gas. Gas is the unit
of calculation for all calculations in Ethereum. In [3] and
[29], the authours used Ethereum smart contracts to solve
the researched problems, and conducted detailed testing and
analysis. The results showed that the use of Ethereum smart
contracts can cost-savings and increase stakeholder profits.
However, unlike the Ethereum smart contract, the Hyper-
ledger smart contract is directly deployed on each node
without built-in tokens, so it does not need to consume tokens
to terminate the execution of the smart contract. The payment
model of Ethereum can avoid the abuse of resources. Once
you have to pay for each operation, you will write the code
as concise and efficient as possible; the existence of Gas can
also prevent attackers from flooding the Ethereum network
through invalid operations (unless the attacker is willing to
pay a large sum of money to perform invalid operations),
but if the gas is consumed, the contract will fail to execute
and the consumed fee will not be refunded. The Hyperledger
smart contract uses a timer scheme, which uses time as a
standard to measure whether a contract has entered an infinite
loop: if the contract has not terminated normally before the
timeout period is reached, then it is considered to have en-
tered an infinite loop and forced to terminate . Therefore, the
Hyperledger smart contract can save resource consumption.
Although the timer can partially solve the downtime problem,
in a distributed system, the execution time of each node may
not be guaranteed to be consistent, and the performance and
load of each node are different, resulting in the judgment of
whether the contract runs overtime. Inconsistencies occur,
which greatly increases the failure rate of the consensus
algorithm, which is an important disadvantage of the timer
solution.
In addition, smart contracts also have some common
security issues, which reduce the security guarantees for
constructing agricultural food traceability systems. Firstly,
smart contracts cannot be modified once deployed, so they
are vulnerable to security vulnerabilities. Secondly, the open
source code of smart contracts reduces the attack cost of
hackers and becomes vulnerable to attacks. Finally, due to
the late start and short development time of smart contracts,
there are still some shortcomings, such as the lack of rigorous
code will cause loopholes. Therefore, in the future, research
can be conducted on these security issues of smart contracts.
VII. CONCLUSION
We propose a framework for tracking and executing transac-
tions by using hyperledger smart contracts, which changes
the centralized model, eliminates intermediaries and inter-
mediate nodes, and realizes the decentralized model of the
agricultural food supply chain, thus meeting the demand for
traceability of agricultural food. With respect to agricultural
FIGURE 10: Traceability QR code.
food safety problems, this paper expounds the importance
of food safety traceability, summarizes related research, in-
troduces blockchain and consortium chain, and presents a
framework using hyperledger smart contracts to track and
implement the agricultural food trade; it presents system
architecture design and describes the relationship between
the agricultural food supply chain entities and the interaction
between entities. In the end, the smart contracts algorithms
are implemented in order to realize tracking and tracing of the
agricultural food supply chain, and the practical application
in Shanwei Lvfengyuan Modern Agricultural Development
Co., Ltd., is introduced, cost analysis and problem discus-
sion. However, regarding the existing problems of blockchain
scalability, privacy and regulation, we have presented a so-
lution which does not take into account the reliability and
auditability of data transactions and payments, and with the
development of the agricultural food supply chain, the decen-
tralized automatic payment mechanism is needed to ensure
that all system entities abide by the promise of deficiencies
in the deal. As a goal of our future work, we plan to study
related problems and to be able to ameliorate and solve them.
ACKNOWLEDGMENT
This work was supported in part by the National Natural
Science Foundation of China under Grants 61871475; in
part by the Special Project of Laboratory Construction of
Guangzhou Innovation Platform Construction Plan under
Grant 201905010006; the Guangdong Science and Tech-
nology Plan of Project under Grant 2017B0101260016;
the Foundation for High-level Talents in Higher Educa-
tion of Guangdong Province under Grants 2017GCZX0014,
2016KZDXM0013, 2017KTSCX094, and 2018LM2168;
Guangzhou Science and Technology Project 201903010043;
and the Beijing Natural Science Foundation under Grant
4182023.
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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2021.3050112, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
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LU. WANG is studying for a master’s degree at
Zhongkai University of Agriculture and Engineer-
ing. She received a bachelor’s degree from Zhu-
jiang College of South China Agricultural Univer-
sity, China, in 2018. Her current research interests
include blockchain technology, IoT technology,
and traceability, among others.
LONGQIN. XU received an M.S. degree from
the Faculty of Computer, Guangdong University
of Technology, in 2006. She is currently a profes-
sor with the College of Information Science and
Technology, Zhongkai University of Agriculture
and Engineering. Her main research interests are
related to intelligent information systems for agri-
culture, artificial intelligence, machine learning,
data mining and computational intelligence.
ZHIYING. ZHENG is studying for a master’s
degree at Zhongkai University of Agriculture and
Engineering. She received a bachelor’s degree
from Guangdong University of Education, China,
in 2016. Her current research interests include
natural language processing, knowledge graphs,
etc.
SHUANGYIN. LIU received a Ph.D. degree from
the College of Information and Electrical Engi-
neering, China Agricultural University, in 2014.
He is currently a professor with the College of
Information Science and Technology, Zhongkai
University of Agriculture and Engineering. His
current research interests are in the areas of intelli-
gent information systems for agriculture, artificial
intelligence, big data, software engineering, and
computational intelligence.
XIANGTONG. LI is studying for a master’s de-
gree in Zhongkai University of Agriculture and
Engineering. He received a bachelor’s degree from
Hubei University of Science and Technology, Chi-
na, in 2018. His current research interests include
deep learning, IoT technology, Artificial Intelli-
gence, etc.
LIANG. CAO received an M.S. degree in com-
puter technology engineering from Sun Yat-sen
University, Guangzhou, China, in 2008. He is cur-
rently an engineer with the Zhongkai University
of Agriculture and Engineering, Guangzhou. His
recent research interests include computer tech-
nology and Internet of Things technology and
applications.
JINGBIN. LI received a doctorate in mechanical
and electronic engineering from China Agricultur-
al University in 2013. He is now a professor and
doctoral supervisor of Agricultural Engineering in
the School of Mechanical and Electrical Engineer-
ing, Shihezi University. His research interests are
agricultural machinery equipment innovation and
performance design, image information acquisi-
tion and processing.
CHUANHENG. SUN received a doctoral de-
gree in information technology in agriculture from
China Agriculture University, Beijing, China in
2012. He is currently a researcher with the Na-
tional Engineering Research Center for Informa-
tion Technology in Agriculture, Beijing. His re-
cent research interests include food traceabili-
ty, blockchain technology and Internet of Things
technology and applications.
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