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IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 67, NO. 4, NOVEMBER 2020 1157
An Effective Yield Estimation System
Based on Blockchain Technology
Murat Osmanoglu , Bulent Tugrul , Tuncay Dogantuna , and Erkan Bostanci
Abstract—Price fluctuation in agricultural products that ad-
versely affects the actors of the market is a serious issue influenced
by many factors. Uncertainty in yield estimation of the products
can be counted as one of the major factors. It is a fact that an
effective yield estimation method may help decision-making actors
to develop effective and stable production and price policies. There
are traditional and remote sensing methods aimed at calculating
the correct yield estimate. However, these methods produce out-
puts only after the sowing season of the products. In this case,
decision makers do not have enough instruments in hand to ensure
price stability. Generally, the existing yield estimation systems are
designed in a centralized setting. However, effective tracking may
not be possible due to problems in the data flow. In this article,
we will propose a blockchain-based solution that carries out yield
estimation of agricultural products. Our solution brings all par-
ticipants interested in agriculture together and produces an early
yield estimation. Thus, the necessary precautions for the excessive
imbalances that may arise in agricultural products will be planned
in advance.
Index Terms—Blockchain, smart contract, yield estimation.
I. INTRODUCTION
YIELD in agricultural production is defined as the total
amount of product harvested during a production sea-
son. The accurate estimate of the yield is an important issue
for both farmers and agricultural investors, as well as other
components of agricultural production, such as consumers and
related government agencies. In its simplest form, the valid yield
estimation will give farmers the opportunity to plan their storage
requirements and the ways in which to sell the product more
efficiently. In addition, the correct estimate of yield will enable
the actors in the market to develop a stable and sustainable
agricultural policy.
In agricultural production, traditional and remote sensing
methods are employed for the yield estimation [1], [2]. Tradi-
tional methods employ empirical-statistical models that require
Manuscript received June 30, 2019; revised December 9, 2019; accepted
January 29, 2020. Date of publication June 30, 2019; date of current version
October 9, 2020. Review of this manuscript was arranged by Department Editor
K.-K. R. Choo. (Corresponding author: Murat Osmanoglu.)
Murat Osmanoglu, Bulent Tugrul, and Erkan Bostanci are with the
Ankara University, Ankara 06560, Turkey (e-mail: mosmanoglu@ankara.edu.tr;
btugrul@ankara.edu.tr; ebostanci@ankara.edu.tr).
Tuncay Dogantuna is with the Coordination Unit for Information Sys-
tems, Agriculture and Rural Development Support Institution, Tarim Ve
Kirsal Kalkinmayi Destekleme Kurumu, Ankara 06550, Turkey (e-mail:
tuncay.dogantuna@tkdk.gov.tr).
Color versions of one or more of the figures in this article are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TEM.2020.2978829
either agrometeorological or survey data provided during the
growth period of crops obtained from the fields. In traditional
methods, experts visit the agricultural lands at specific periods
during the harvest season and report the necessary data based
on their observations. Methods using agrometeorological data
try to map the relationship between climate data and crop yield.
Traditional methods may produce incorrect results because the
data collection process is subjective. Also, this kind of data
collection takes a lot of time and delays. In addition, these
models have limited practical applicability on a national scale
due to different factors such as changes in soil properties, plant
diseases, and pesticide use.
There are also other traditional yield estimation methods
based on sampling methodology. However, these methods can
be employed after crops are actually harvested from the field.
Therefore, the decision maker cannot take necessary precautions
before a problem occurs about yield amount and price. Early
assessment of crop yields is, therefore, necessary, especially
in countries that depend on agricultural products as their main
ingredients of the economy. Consequently, relying on traditional
methods, it will be hard for decision makers to take the necessary
precautions in order to establish a sustainable agricultural policy.
On the other hand, precision farming has been carrying out
in most countries for several years. Sensors that measure the
required predictor variables help scientists to build models that
are more complex. In this sense, remote sensing methods, which
eliminate the disadvantages of traditional methods, use data
collected from sensors and satellite images captured between
the sowing and harvesting of crops since 1970. These images
are often used to calculate various vegetation indices such as;
normalized difference vegetation index (NDVI) and vegetation
condition index. Subtracting the actual from the average NDVI
image of the same period presents vegetation anomalies. How-
ever, they hardly provide suitable data on yield estimation.
There are also solutions that combine both traditional and
remote sensing methods. However, both methods can be em-
ployed only after the sowing season. A system that allows yield
estimation before planting seeds will allow farmers to revise
their production plans and even turn to another crop that may
be considered more profitable. In addition, with the help of such
system, decision-making actors such as government agencies or
agricultural cooperatives will develop effective and permanent
production and price policies. Our solution aims to achieve this
goal.
Blockchain is an effective technology that enables the re-
alization of continuously growing list of transactions. It was
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1158 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 67, NO. 4, NOVEMBER 2020
first introduced by Nakamoto [3] to as a peer-to-peer electronic
cash system named as Bitcoin. Due to the data’s immutability,
transparency, and decentralized nature, it has also been used to
build practical applications in different fields such as finance,
supply-chain managements, and social services. Besides, Food
and Agriculture Organization has emphasized the importance of
blockchain applications in agriculture [4]. Blockchain applica-
tions in agriculture are mainly concentrated on the supply chain
management [5]. Thus, all growth and transportation stages of
agricultural products can be monitored, and problems in any part
of the supply chain can be easily detected.
In this article, we will propose a decentralized and distributed
solution to the problems we address previously by providing an
effective yield estimation mechanism using blockchain technol-
ogy. Our solution can be considered as an extension of the work
presented in [6].
A. Our Contribution
In this article, we propose an efficient yield commitment sys-
tem. Our system can be viewed as a platform that allows farmers
to share their farming plans for the oncoming harvest season with
the other players of the market. It also enables farmers to observe
the others’ plan and to revise their investments and take the
necessary steps for the oncoming season, accordingly. We utilize
the blockchain technology to design our platform that provides
a censorship resistant, tamper proof, and strongly immutable
public ledger of time-stamped transactions. Specifically,
1) We first formalize the problem and address the security
concerns that will be required to get an effective yield com-
mitment platform. In more details, we identify four differ-
ent roles for a yield commitment system: producer, auditor,
platform, and registration authority. To avoid the single
point of failure, we consider the platform that is operated
by a set of network players. Particularly, we will construct
the platform on top of a permissioned blockchain network.
Also, we require a well established identities for the pro-
ducers and auditors in order to prevent a malicious player
from creating multiple identities and mount a Sybil attack.
On the other hand, we illustrate some technical chal-
lenges that should be encountered when designing such
platform.
a) Producers employ smart contract to submit their yield
commitments. Smart contracts allow the network play-
ers to monitor and validate the yield commitments
in an effective and transparent way. However, smart
contracts require a neutral third party, considered as
“oracle”, that verifies whether the commitments are
fulfilled or not. In our context, oracles will be auditors,
and it is really hard to get a fully trusted oracle even if
it is built in decentralized fashion.
b) A yield commitment system requires an efficient
mechanism that enforces the producers when they
do not fulfill their commitments in order to avoid a
malicious producer to manipulate the other players.
However, this should not discourage producers to de-
clare commitments.
2) We, then, construct a yield commitment system on top of
a permission blockchain network that meets the security
requirements we address, and overcome the technical
challenges we specify. There will be two entities in our
system: farmers (natural players who own a farm land and
raise field crops) and administrators (officers that represent
the agricultural authorities of different regions or different
crops such as provincial agricultural directorates, agricul-
tural unions, or regional farmers’ organizations). Farmers
support two roles in the system: producers and auditors,
and administrators also support two roles in the system:
platform and registration authority. Our system requires
farmers to obtain a certificate from the corresponding
administrator, which legally proves the ownership of the
farmer for the associated farmland in order to register in
the system. On the other hand, our platform starts with an
initial set of administrators that possess well established
identities. However, it also enables a new administrator
to register in the platform as the agricultural authority of
a new region, i.e., when a new administrator applies to
register in the system, one of the existing administrator
take a vote among all the existing administrators in order
to approve the application by initiating a smart contract,
which terminates as “YES” if the number of approvals is
majority, “NO” otherwise.
In our system, we consider the time as a sequence of discrete
units, called as “time slots”. Time slots are associated with
administrators in round-robin fashion. In each time slot, the
associated administrator, called primary, will create a block
with all the smart contracts and transactions he/she has re-
ceived in the associated time slot together with the hash of
the previous block appended in the ledger, and add the block
to the ledger using a three-phase protocol proposed in [7].
Similar to [7], our platform provides both safety and liveness
in presence of at most (n−1)/3faulty administrators out
of a total of nadministrators. We also introduce two transac-
tions, detection and slot-change transactions, that enables ad-
ministrators to make progress when the primary administrators
fails on block generation in the associated time slot. Since
administrators can reach all the transactions propagated in the
network, any malicious behavior of the primary can easily be
detected.
Moreover, we introduce a key concept “reputation” that en-
forces producers to stick to their commitments. In our system,
the reputation can be viewed as a reliability score that producers
earn when they fulfill their commitments, and lose when they do
not stick to their commitment. Also, the entities in our platform
can decide whether they consider the commitments of a producer
when making investment for the upcoming harvest season by
looking at his/her reputation value. Besides, in an effective
yield commitment system, the rational players enhance their
investment plans depending on the commitments accumulated
in the platform. So, a producer having a poor reputation score
will not obtain a desired profit since the other players of the
market ignore his/her commitments when making investment.
Thus, reputation will also be an effective tool to incentivize
producers to fulfill their commitments. Furthermore, we also use
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OSMANOGLU et al.: EFFECTIVE YIELD ESTIMATION SYSTEM BASED ON BLOCKCHAIN TECHNOLOGY 1159
reputation to enforce auditors to fulfill their duties, i.e., when the
primary administrator detects that an auditor has not provided
his/her report for the commitment, which has the associated
time slot as due date for the reports, the primary will decrease
the reputation score of the auditor. Since we choose auditors
among farmers, reputation will also be an efficient mechanism
to motivate auditors to do their duties.
B. Related Works
The main goal of blockchain is to ensure data consistency and
integrity by providing a distributed and decentralized database.
The first application of blockchain technology, which provides
a mechanism of trust among the participants, was proposed
in the field of finance [3]. Mattern [8] examined blockchain
applications in agricultural finance. He reviews the underly-
ing technology in terms of costs and benefits. He also high-
lights the design considerations that a convenient blockchain
application should follow. Moreover, it has been realized that
this technology will offer new solutions for many different
fields.
In agriculture, blockchain has been used in different areas
such as agricultural food supply management [9], food safety
and integrity [10], transparency in agricultural trade and mon-
itoring [11], crop quality assurance tracking [12]. Bermeo-
Almeida et al. [13] presented that 60% of scientific articles
based on blockchain technologies in agriculture have focused
on food supply chain management. Tse et al. [14] evaluated
the concept of blockchain technology to integrate it into the
process of information security of the food supply chain. They
compared it with the traditional supply chain system. They
also proposed a supply chain system for production processors,
brokers, and consumers by implementing a distributed ledger
system. Similarly, Papa [11] focused on the use of blockchain
technology, which provides traceability in agricultural sector.
He also claimed that his solution allows for transparency and
monitoring in agricultural trade among participants. Lucena
et al. [12] presented a case study of how grain quality can be
assured on a hyperledger platform. There are also supply-chain
management solutions that integrate Internet of Things (IoT)
technology to blockchain platform [15], [16]. Awan et al. [17]
discussed a variety of IT-related technologies that can be used in
smart farming and offer a new solution that combines IoT with
blockchain. They claim that their solution builds a framework
for equal opportunities for all participants.
In addition, there are studies exploring the advantage of
blockchain in precision agriculture. The IoT devices used in
greenhouses should be remotely monitored and controlled.
However, there is always a security and privacy concern while
transferring data from devices to main servers. Patil et al. [18]
proposed a distributed ledger mechanism, which stores trans-
actions. In order to use farm management information system
more effectively, Branco et al. [19] proposed a solution using
both the IoT and blockchain technology to store distributed
environmental measurement values and control the production
process of mushroom. Wu and Tsai [20] offer a secure network
topology that transfers data generated by the Internet of Things
(IoT) devices on farms based on blockchain. Their solution is
resistant to distributed denial-of-service attacks (DDOS) and
deploys an identity authentication mechanism.
II. PROBLEM FORMULATION
In this section, we give a detailed definition of the problem
and its security requirements.
A. Yield Commitment System
There are four roles in the model of a yield commitment
mechanism: producers, auditors, a platform, and registration
authorities. A producer, identified by F, periodically announces
yield commitments for the products he/she raises to the members
of the system by declaring a commitment, denoted by Cas “the
crop xwill be planted in yamount of the land Lbelonging to
the producer Ffor the upcoming season”. An auditor, makes
an observation for the commitment that he/she was assigned,
and reports his/her observation with a numerical number Rthat
indicates at which rate the producer meets his/her commitment.
The platform in this model can be viewed as a medium that
monitors both the declarations of producers and the reports of
auditors, and records them in a database. The platform is either
maintained by a single authority or a network of players. The
registration authority manages the registration process of pro-
ducers and auditors by assigning each entity a unique credential
if he/she satisfies the conditions.
In this article, we consider the platform that is managed
by a set of network players. Let us briefly explain the reason
with the following scenario: suppose there is a central authority
managing the platform and there are some malicious producers
that try to manipulate the market in order to maximize their
profit. The malicious producers may declare false commitments,
which they will not fulfill in order to mislead the market players,
i.e., they may declare a yield commitment of a certain amount
for a particular product X that will be more than they plan. In
this case, the produced amount of the product X will be lower
than expected for the next harvest season. So, the unit price
of the product will increase, and the malicious producers will
earn much more than they are supposed to. In an ideal system,
this behavior is expected to be easily detected. However, if the
malicious producers have enough power to control the central
authority, they may keep this act without being detected and
design the market at their will. Thus, to avoid such scenario to be
happened, or in general, to avoid the single point of failure, it will
be better to distribute the control among a set of network players.
In a yield commitment system, if an established identity is
not required to register in the system, a malicious player may
create multiple identities, and can control a large fraction of
the system. He/she may later use this power to manipulate the
market players, or even to mount a Sybil attack. To prevent
such misbehaviors, a yield commitment system requires the well
established identities. We remark that a registration authority
can be employed to establish identities for farmers, and realized
by either the platform, or the certificate authority that enables
the authentication service. Note that our yield commitment
system consists of three roles as shown in Figure 1: producers,
auditors, and administrators that support the roles, the platform
and registration authorities.
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1160 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 67, NO. 4, NOVEMBER 2020
Fig. 1. Yield commitment system.
B. Security Model
We identify the security requirements for a decentralized yield
commitment system.
1) Security Against a Malicious Producer: A malicious pro-
ducer may declare a yield commitment of the rate different than
he/she has planned in order to mislead the other producers to
increase his/her profit. Security in this case requires an efficient
tool that punishes the producer when he/she does not meet
his/her commitment. Moreover, this tool can also be used to
incentivize the producers to fulfill their commitments. Besides,
a malicious producer may prefer not to declare a commitment,
and to hide his/her plan from the other players of the market.
By doing so, he/she may adjust his/her plan according to the
commitments of the others to maximize his/her profit. Obvi-
ously, this will make the others to loose money. Thus, the yield
commitment system should enforce producers to periodically
declare yield commitments, and punish them if they prefer not
to. On the other hand, a malicious producer may try to change
the existing commitments that damage his/her reputation, so that
he/she pretends to be an honest producer that meets his/her com-
mitments, and prevents his/her reputation to stand as damaged.
To avoid such case, the commitments should be recorded in an
immutable way.
2) Security Against a Malicious Auditor: A malicious audi-
tor may try to report a rate for the commitment he/she has been
assigned without making enough observations. Furthermore,
he/she may report a rate without visiting the corresponding
farmland. Besides, a malicious auditor may report a “wrong
rate” for the commitment to damage the producer’s reputation.1
To ensure the security for these cases, the yield commitment
system should enable the platform to verify that the auditor
indeed visited the corresponding farmland and makes enough
1A wrong rate, here, is the rate given for a commitment that does not reflect
the existing situation of the corresponding farmland.
observations. On the other hand, a malicious producer may
corrupt the auditor assigned to his/her commitment, and make
him/her to report a rate higher than the actual one. Security in
this case will be achieved through assigning an auditor to each
commitment independent of the owner of the commitment.
3) Security Against a Malicious Administrator: As we stated
previously, the platform in our system is managed by a set of
network players, which we call as administrators. A malicious
administrator may record a yield commitment or the report of
an auditor for a specific commitment to the database different
than the actual one in order to alter the reputation of the owner
of the commitment. Moreover, he/she may simply ignore the
commitments of a particular producer or the corresponding re-
ports to damage the producer’s reputation. Security in these cases
requires an effective mechanism that enforce the administrators
to act honestly, and to record all the valid commitments and all
the reports to the database as they are. Besides, a malicious
administrator may prefer not to do anything when he/she is
supposed to, and to remain silent. Clearly, this situation will
affect the efficiency of the system in negative way. So, the yield
commitment system should enable such behavior to be easily
detected and repaired. On the other hand, a malicious producer
may corrupt an administrator, and make him/her to change
the existing commitments and the corresponding reports that
damage his reputation. To avoid such cases, all the commitments
and the reports should be recorded in an immutable way.
C. Technical Challenges
One of the advantages that the blockchain possesses is the
smart contracts. A smart contract is a piece of codes consisting
of predefined terms agreed by the counter parties of the contract.
When these terms are met, the smart contract autonomously
executes itself and produces an output to the network. While
smart contracts have substantial benefits such as providing trans-
parency and efficiency, and decreasing the cost of maintaining
the blockchain, they struggle several limitations. In most cases,
the terms of smart contracts are linked to the real world oc-
currences, and smart contracts are not self-sufficient in terms
of receiving and verifying information from the real world. So,
smart contracts need a third party, called as “oracle,” to remove
the gap between the real-world events and the blockchain. An
oracle, here, can be viewed as an agent that observes and
verifies the real-world events, and reports this information to
the blockchain and smart contracts. Since smart contracts are
executed depending on the data provided by oracles, oracles
hold substantial power over smart contracts. Thus, designing a
correct oracle is crucial to get a smart contract that is properly
executed.
In a yield commitment system, producers can employ smart
contracts to submit their yield commitments. Smart contracts
enable the network players to monitor and validate the commit-
ments in an efficient and transparent way. However, as we elab-
orated previously, smart contracts require a neutral third party,
considered as “oracle,” that verifies whether the commitments
are fulfilled or not. In our context, oracles will be “auditors” that
provide the information about the commitments to the smart
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OSMANOGLU et al.: EFFECTIVE YIELD ESTIMATION SYSTEM BASED ON BLOCKCHAIN TECHNOLOGY 1161
contracts. We remark that an ideal (fully-trusted) oracle is really
hard to achieve even if it is built in decentralized fashion [21].
However, we can still develop some mechanism that enables the
yield commitment system to obtain credible information about
the commitments.
Challenge 1: Designing a practical mechanism that enables
the yield commitment system to obtain credible information
from auditors
As we stated previously, a malicious producer may try to
manipulate the other players of the system by declaring a yield
commitment that he/she is not planning to fulfill. So, the yield
commitment system requires an efficient mechanism that pun-
ishes the producers when they do not fulfill their commitments
in order to avoid such cases. However, if the system overdoes
the punishment, then making commitments might become risky
for the producers. So, such mechanism may discourage the pro-
ducers to declare commitments. Moreover, since the producers
in the system have to periodically declare yield commitments
for their farmlands, it may discourage the producers to even
register in the system. Thus, we need to be careful in designing
such mechanism: it enforces the producers to stick to their
commitments, but at the same time it does not discourage them
to register in the system.
Challenge 2: Designing an efficient mechanism to enforce
the producers to stick to their commitments without discour-
aging them to declare commitments, or to even register in the
system.
III. DEFINITIONS
In this section, we will give the definitions of some primitives
that will be used in our proposed protocols.
A. Hash Functions
Hash function is a mathematical tool that compresses an
input of arbitrary length to a short fixed length string. The
output of a hash function on an input message is mostly called
message digest. A hash function is called collision resistant if it
is computationally infeasible to find two different inputs of any
length that have same digest.
B. Digital Signature Schemes
Digital signature is an authentication mechanism that verifies
to the receiver the origin of the message, which is actually
received from the user. There is a pair of keys in digital signature
system that is called a secret key and a public key. A user creates
a signature on a message using his/her secret key. Anyone who
has the users public key can easily verify that the signature is
generated by the user. Similar to hand-written signatures, dig-
ital signatures present two properties; authenticity (a signature
convinces a verifier that it was indeed generated by the owner
of the public key) and integrity (the signature was not modified
during transition). A digital signature scheme is called unforge-
able if no one can create a valid signature without the secret
key.
C. Distributed Ledgers
Distributed ledger is a database shared through a network
of multiple sites, corporation or region. In the corresponding
network, all shareholders have privilege to take a copy of the
ledger on its own. All copies of the ledger are periodically
updated when any alteration is occurred. The security and ac-
curacy of the assets stored in the ledger are maintained through
the cryptographic tools such as cryptographic hash functions
and digital signature scheme. Entries of the ledger can also be
updated by one, some or all of the participants, according to
rules agreed by the network. A robust distributed ledger has two
properties: safety and liveness. The former one ensures that all
nonfaulty players in the network agree on a total order for the
transactions recorded in the ledger, and the latter one ensures
that an honestly generated transaction is eventually accepted by
all nonfaulty players.
D. Blockchains
Blockchain is an efficient mechanism that enables the realiza-
tion of a distributed ledger. It can be considered as a set of blocks,
which contains an ordered records of transactions. Every block
is pointed by the next block with a reference, which is a hash
value of the block called parent block. There is a special block,
named as Genesis block, which is the first block of blockchain.
Transaction counter and transactions constitute the body of the
block. Note that the number of transactions in a block and the
size of each transaction determine the maximum number of
transactions that can be placed in a block.
E. Smart Contracts
Smart contracts are computer programs that autonomously
execute the terms of a contract. They are triggered by addressing
a transaction to them. Then, they are executed independently
and automatically in a prescribed manner on every node in
the network, according to the data that were included in the
triggering transaction.
IV. CONSTRUCTION
In this section, we explain our platform that enables the
producers to share their farming plan with the other players
of the market, and makes them to have positions based on
the information the producers share for the oncoming harvest
season. In other words, the platform establishes the optimal
consensus among the producers and the other related players.
As we stated in Section II, we will build our system on
top of a blockchain network. In general, blockchain networks
can be categorized under two types: permissionless and per-
missioned [22]. A permissionless blockchain allows anyone to
participate in the network and to create blocks. On the other
hand, in a permissioned blockchain, only an authorized set of
entities is allowed to create blocks and to maintain the ledger.
Permissioned blockchains possess a lot of advantages over
permissionless blockchain due to its ability to allow the use of
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1162 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 67, NO. 4, NOVEMBER 2020
parallel computing and better scaling. Since the entities are ap-
peared with their original identities in our system, permissioned
blockchain protocols [23], [24] will be sufficient to effectively
build our platform.
A. Entities in Our System
In our system, every participant holds a public key-signing key
pair (sk,pk)of a digital signature scheme that will be used to
ensure the integrity and the authenticity of messages it creates,
and every participant is identified with the hash of its public
key, i.e., h(pk). However, instead of directly using h(pk),we
use letters to refer the hash of the public keys, i.e., different
letters are used to identify different roles.
There will be two entities that are involved in our protocol:
farmers and administrators. Farmers are the natural players or
the legal entities who own a farm land and raise field crops
corresponding to the region of the land. They support two roles in
our system: producer and auditor, i.e., they periodically declare a
yield commitment for crops that can be raised in their farm lands
as producers, and they can be assigned to a commitment as an
auditor that makes an observation, and reports his observation
with a numerical number that indicates at which rate the producer
meets his/her commitment. Note that farmers have to get a
certificate from the agricultural authority of their region in order
to register the platform and to declare a yield commitment.
Administrators are the officers that represent the agricul-
ture authorities of different regions or different crops such
as provincial agricultural directorates, agricultural unions, or
regional farmers’ organizations. They take in hand two roles
in our system; the platform and the registration authority, i.e.,
they are responsible for providing certificates to the farmers
and maintaining the platform. Besides, they have the ability to
deploy and validate smart contracts. Since administrators pro-
vide certificates to the farmers for the registration and maintain
the platform, having administrators possessing an established
identity is essential to get a secure yield commitments system.
So, we should be attentive to devise the admission process of
administrators to the system.
1) Registration: We start with an initial set of administrators
that possess well established identities. The identifiers of the
administrators {(Ai1,i
1),...,(Aim,i
m)}in the initial set will
be specified at the genesis block B0where i1,...,i
mare the
integer values used to determine the order in block generation.
Note that our system allows a new administrator, which is not a
member of the initial set, to register as the agricultural authority
of a new agricultural division. When a new candidate A∗applies
to register in the system, one of the existing administrators,
say Aj, initializes a smart contract S∗to take a vote among all
the existing administrators in order to approve the application.
The smart contract S∗works as follows: each administrator Ai
sends his vote to the smart contract S∗, i.e., if he approves the
admission, he/she sends 1; otherwise, he/she sends 0.Ifthe
number of approvals is majority among all the votes, then, the
smart contract S∗outputs 1; otherwise, it outputs 0.Ifthe
smart contract S∗outputs 1, then, the administrator Ajfinds
the last registration transaction created for the administrators,
Fig. 2. Block structure.
and extracts the integer value, say k, from the transaction.
Aj, then, assigns the integer value k+1 to A∗and creates a
registration transaction to announce him/her to the network as a
new administrator.
The registration process for a farmer is realized in a simpler
way. When a farmer Fuwants to join in the system, he/she first
requests a certificate from the agriculture authority of his region.
If he/she meets the necessary conditions, the corresponding au-
thority creates the certificate certuby signing his/her identity Fu,
and gives certuto Fu. The certificate certuproves that the farmer
Fuowns the farm land he/she claims in the corresponding region.
The farmer Fu, then, provides the certificate certuto one of the
administrators as a request for the registration. The administrator
Aifirst checks the validity of the certificate by verifying whether
certuis a valid signature of Fu. Note that administrators assign
the positive integers 1,2,...as the numerical values to the farm-
ers according to the registration order, i.e., 1 is assigned to the
first farmer registered in the system. Assigning such numerical
values to farmers enables us to count the total number of farmers
registered in our system, but more importantly to efficiently
choose random auditors among farmers for the commitments.
After the validation of the certificate certu, the administrator
Aifirst finds the last registration transaction created for the
farmers in the ledger, extracts the integer value, say , from
the transaction. Ai, then, assigns the integer value +1to Fu,
and creates a registration transaction to announce him/her to the
network as a new player.
B. Block Format
As we emphasized previously, we design the yield commit-
ment system as a blockchain network that consists of a sequence
of blocks B0,B
1,B
2,..., where B0is the genesis block. As
given in Figure 2, each block contains a set of transactions and
smart contracts created in a certain time period, the hash of the
previous block, the current time stamp,2the block index, and a
signature of all these records.
In our system, time is divided into a sequence of discrete
units, called slots, and each time slot stkis indexed with an
integer k∈{1,2,...}. Note that each slot stkis associated with
(at most) one block in the ledger. Our platform associates each
administrator Aito the slot stkwhere i=kmod (N+1)and N
is the integer value assigned to the last administrator registered
in the system. In other words, the administrator Aiwill be
2The time-stamp recorded to the blocks will be used as an indicator that the
players registered in the platform follow to determine the sowing time and the
harvest time of the products.
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OSMANOGLU et al.: EFFECTIVE YIELD ESTIMATION SYSTEM BASED ON BLOCKCHAIN TECHNOLOGY 1163
responsible to create the block Bkwhere i=kmod (N+1)
and Nis the integer value assigned to the last administrator.
In block creation, the administrators follow the Byzantine
fault tolerance algorithm proposed by [7] to agree on a total
order for the execution of the smart contracts and transactions,
i.e., for the time segment stk, the administrator Aiwill be the
primary and all the other administrators will be backups where
i=kmod (N+1). The primary Aiwill form the block Bkwith
all the smart contracts and transactions he has received in the
corresponding time slot together with the hash of the previous
block h(Bk−1), the corresponding time slot as the current time
stamp, the block index k, and a signature of all these records, and
execute a three-phase protocol to add the block Bkto the ledger.
Our system provides both safety and liveness as explained in
Section III, in presence of at most (n−1)/3faulties out of a
total of nadministrators.
Our platform ensures liveness by enabling administrators to
make progress when the primary administrator fails on block
generation in the associated time slot. The failure of the primary
administrator can be occurred in the following ways: the primary
may add an incorrect record to the block he creates, or he
may not add a record he has received to the block, or even he
may prefer not to create the block. Since administrators can
see all the transactions propagated in the network, the first two
scenarios can easily be detected. When an administrator detects
any such case, i.e., an incorrect record added to the newly created
block, or a record not contained in the newly created block, he
initiates a slot-change protocol for the current slot, say stk,by
propagating a detection transaction to the network. If the primary
administrator of the slot stk+1 receives 2(n−1)/3valid
detection transactions, he will combine all the valid detection
transactions together with all the other transactions and smart
contracts he/she has received in the time slots stkand stk+1,
into the block Bk+1, and execute a three-phase protocol to add
the block Bk+1 to the ledger.
Note that the primary administrators should create and propa-
gate the blocks in a certain time period. To determine whether the
primary is active or not, a backup administrator starts a timer at
the end of the last three-phase protocol, and stops it when he/she
receives any message from the current primary. If the timer of
the backup administrator Aiexpires in the slot stk,Aiinitiates
a slot-change protocol for stkby propagating a slot-change
transaction to the network. If the primary administrator of the
slot stk+1 receives 2(n−1)/3valid slot-change transactions,
he will combine all the valid slot-change transactions together
with all the other transactions and smart contracts he has received
in the time slots stkand stk+1, into the block Bk+1 , and execute
a three-phase protocol to add the block Bk+1 to the ledger.
C. Declaring a Yield Commitment
In our system, farmers have to periodically announce a yield
commitment to the network.3This commitment will be a dec-
laration that determines the farmer’s intention, i.e., “the crop X
will be planted in Y amount of the farmland Z for the coming
3After this section, we will use the terms farmer and producer interchangeably.
harvest season”. Farmers make this declaration by initiating a
smart contract. They also attach their signature to the contract
to ensure the authenticity of the data.
1) Choosing Random Auditors: As we emphasized in Sec-
tion II, a yield commitment system requires an auditor to validate
whether the commitment is fulfilled or not. To this aim, a farmer
can be assigned to the commitment as an auditor through the
smart contract initiated for it. However, since the farmer creates
the smart contract, he/she can manipulate this process in a way
that the smart contract chooses an auditor that can easily be
corrupted by the farmer. Thus, the intervention on assigning an
auditor to a commitment should be obstructed for the farmers.
In our system, the randomness that will be used by the smart
contract to choose an auditor for the commitment, will be
obtained from a source that cannot be intervened by the farmer,
i.e., the smart contract Cjwill take the hash of the last block Bv,
h(Bv), added to the chain as the random input, and determine
afarmerOjas an auditor among all the registered farmers by
choosing a random integer jfrom []using this randomness,
where []is the integer assigned to the last farmer registered in the
platform. However, as we elaborated in Section II, a malicious
auditor may provide a wrong report that does not reflect the
actual situation of the farmland. So, instead of relying on just
one auditor, it will be better to distribute the observation task
among a set of auditors, i.e., the smart contract Cjwill assign
three farmers Oj,1,Oj,2, and Oj,3to each commitment as the
auditors.
After assigned to the commitment Cj, each auditor Oj,k has
to visit the corresponding farmland in a certain time, and has
to report a rate regarding to his observation. This rate will be a
numerical value p∈[0,1] that indicates at which rate the farmer
fulfills the commitment. Each auditor Oj,k, then, creates a report
transaction to announce his/her rate for the commitment to the
network.
On the other hand, our system can be extended in a way
that it requires auditors to prove that they have indeed visited
the corresponding farmland and made enough observations. In
this case, auditors will attach a location proof to their reports,
which verifies their presence at the corresponding farmland in
the specified time period [25].
We remark that each crop has a specific sowing time and a
specific harvest time, and farmers should consider these periods
when they declare commitments, i.e., farmers need to specify at
which time auditors should provide their rate for the commitment
in terms of time slots. Auditors should also consider these time
slots when they visit the farmlands and make observations for
the reports.
D. Reputation Mechanism
In this section, we introduce a key concept, “reputation”, that
forces farmers to stick to their commitments. As we stated in
Section II, to maximize their profit, farmers may manipulate the
other players of the network by declaring an incorrect commit-
ment, or by not fulfilling the commitment they have declared, or
by preferring not to declare a commitment to hide their plans.
However, this act ruins the market, and causes the other players,
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1164 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 67, NO. 4, NOVEMBER 2020
which might have made investments based on the commitments,
to loose their investments. Reputation enables us to avoid such
cases.
The reputation value can be viewed as a credential that
farmers earn when they fulfill their commitments, and they
loose otherwise. It will be an indicator for the reliability level
of farmers. By looking at the reputation value of a farmer,
other farmers can determine whether they should consider the
commitments of the farmer when making investments for the
oncoming harvest season. On the other hand, an effective yield
commitment system will incentivize the rational producers to
make investments depending on the commitments accumulated
in the platform. Since commitments of a farmer having a poor
reputation score will not be included in the investment plans of
the other farmers, that farmer will not obtain a desired profit for
the corresponding seasons. Thus, reputation enables our system
to incentivize farmers to fulfill their commitments.
Recall that administrators broadcast a registration transaction
to announce a new farmer to the network as a legitimate player.
Every registration transaction includes an initial reputation value
Rufor the new farmer Futhat is set as 1/2. The reputation
value Ruof Fuis updated at each commitment based on the
performance of the farmer Fu. Briefly, each farmer Fuinitiates a
smart contract to declare a commitment, and every smart contract
Cjproduces a score Pjthat represents the performance of the
owner of the contract, when it terminates. The score Pjthat Cj
produces will be either a real number from [0, 1] or the symbol
⊥, i.e., if no auditor reports a rate for the contract, the score
Pjwill be ⊥; otherwise the score will be the average of the
rates pj,k reported by the auditors of the commitments. If the
smart contract Cjproduces the symbol ⊥as Pj, administrators
will not consider this commitment as a valid commitment, and
they will not update the reputation of the farmer based on this
commitment.
On the other hand, if the smart contract Cjproduces a real
number between [0, 1] as Pj, the primary administrator of
the corresponding time slot will create an updating-reputation
transaction by taking the score Pjinto consideration. The key
question here should be how does the primary administrator
compute the reputation value in the transaction? (how does he
compute the new reputation score of the corresponding farmer?).
A naive approach will be computing the new reputation value
as the average of the scores that the farmer has taken from every
commitment he made and the initial reputation value, i.e., let n
be the number of scores the farmer has taken and R∗
ube the initial
reputation value of the farmer Fu, then, the new reputation value
will be (R∗
u+Pj)/(n+1) where Pjis the score Fuhas
taken from the commitment Cj. However, if the new reputation
value will be produced in this way, then a successful farmer that
have fulfilled a large number of commitments may prefer not to
act according to the new commitments he/she makes in order
to manipulate other players since his/her reputation will slightly
be damaged.
To keep a farmer more alive and more faithful to his word,
the primary administrator computes the reputation value as the
average of the last reputation value and the score that the farmer
has taken from the last commitment he made, i.e., let Rube
the last reputation value of the farmer Fuand let Pjbe the
score the farmer has taken, then the new reputation value will be
(Ru+Pj)/2. Note that if the farmer Fuhas just registered in the
system and has not made any commitment yet, the last reputation
value Ruwill be the initial reputation value; otherwise, Ruwill
be the reputation value in the last updating-reputation transaction
created for Fu.
We remark that farmers have to periodically declare com-
mitments to share their farming plans. We can also utilize the
concept “reputation” to enforce that. In each time slot, the pri-
mary administrator, say Ai, also checks whether farmers declare
yield commitments or not. If he detects a farmer Futhat has not
declared a yield commitment, he/she updates the reputation of
Fuin the following way: if the farmer Fuhas just registered in the
system and has not made any commitment yet, Aicalculates the
new reputation value as R∗
u/2where R∗
uis the initial reputation
value; otherwise, Aifinds the last updating-transaction in the
ledger created for Fuand extracts the last updated reputation Ru
from the transaction, and similarly calculates the new reputation
value as Ru/2.
On the other hand, having auditors not neglecting their duties
is necessary to get an efficient yield commitment system. Repu-
tation can also be used to enforce auditors to fulfill their duties.
Recall that farmers need to specify when the smart contracts
created as their commitments should be terminated in terms
of time slots. That particular time slot will be the due date
of the commitment for the auditors to multicast their report
to the network. If the primary administrator, say Ai, detects
that an auditor Oj,k has not provided his/her rate pj,k for the
commitment Cjhe/she was assigned in the associated time slot
that is specified as the due date for the reports, Aifinds the last
updating-transaction in the ledger created for Oj,k and extracts
the last updated reputation Rufrom the transaction. Aithen
creates an updating reputation transaction for Oj,k with the new
reputation value as Ru/2. Besides, each primary administrator
randomly chooses a commitment Cjamong all the commitments
whose due date is the associated time slot. The primary, then,
visits the farmland of the commitment Cj, and checks whether
the auditors have provided “true” report or not. Based on his/her
observation, the primary administrator updates the reputation
values of all three auditors by creating updating reputation
transactions.
E. Transactions in Our System
There are six types of transactions defined in our system:
registration, updating reputation, revocation, detection, slot-
change, and reporting. The first five are created by adminis-
trators, and the last one is created by auditors. Each transaction
is signed by the one creating it, and added to the ledger by
administrators.
1) Registration: A registration transaction is created by an
administrator to announce a farmer as a legitimate player, or to
announce the agricultural authority of a new agricultural division
as a new administrator, to the network. It has the following form:
(registration,F
u(orAj),certu(or ⊥),R
u(or ⊥),
u,sigi,pki)
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OSMANOGLU et al.: EFFECTIVE YIELD ESTIMATION SYSTEM BASED ON BLOCKCHAIN TECHNOLOGY 1165
1) Fuis the unique identifier of the new farmer and Ajis the
unique identifier of the new administrator.
2) certuis the certificate given to the farmer Fuby the
registration authority.
3) Ruis the initial reputation value for the farmer Fu.
4) uis a positive integer assigned to the farmer Fuor to the
administrator Aj.
5) sigiis the signature of registration,F
u,certu,R
uunder
the public key pki.
6) pkiis the public key of the administrator Aicreating the
transaction.
The initial reputation value Ruwill be set as 1/2for each
farmer Fu, and be updated at each commitment based on the
performance of the farmer. If certuis a valid certificate prepared
for the farmer Fuand sigiis a valid signature under the public
key pki, then it is considered a valid registration transaction. We
remark that farmers are only allowed to create yield commit-
ments if there is a valid registration transaction recorded in the
chain for them.
Note that administrators are not required to provide a cer-
tificate to register in the system. Also, the reputation value is
generated for only farmers. Thus, the ⊥symbol is placed into
the corresponding pieces of the registration transaction created
for a new administrator.
2) Updating Reputation: An updating-reputation transaction
is also created by an administrator to update the reputation of
the corresponding farmer according to the report provided by the
auditors assigned to one of the commitments the farmer creates.
It has the following form:
(update,F
u,c
j,R
u,sigi,pki)
1) Fuis the unique identifier of the farmer to be registered
in.
2) cjis the counter that indicates the number of consecutive
commitments during, which the reputation of the farmer
Fustays below a certain threshold T.
3) Ruis the reputation value for the farmer Fu.
4) sigiis the signature of update,F
u,c
j,R
uunder the
public key pki.
5) pkiis the public key of the administrator creating the
transaction.
Before creating the transaction, the administrator Aifirst
looks for the last updating-reputation transaction prepared for
the farmer Fuin the chain. If there is such transaction, Aichecks
whether the new reputation Rubecomes less than T.Ifthisis
the case, it increases the counter cjby 1; otherwise, it sets the
counter as 0. If there is no such transaction, Aichecks whether
the reputation Rudrops below T. If this is the case, Aisets the
counter cjas 1; otherwise, it sets the counter cjas 0.
3) Revocation: A revocation transaction is created by an
administrator to revoke the farmer that has not performed well
in his recent commitments. It has the following form:
(revocation,F
u,sigi,pki)
1) Fuis the unique identifier of the farmer to be registered
in.
2) sigiis the signature of revocation,F
uunder the public
key pki.
3) pkiis the public key of the administrator creating the
transaction.
A revocation transaction of a farmer Fuis only created if
the counter in the last upgrading-reputation transaction of Fuis
equal to the threshold tand Fufails on the last commitment.
which has not been terminated.
4) Detection: A detection transaction is created by an ad-
ministrator to inform the network about the malicious behavior
of the primary administrators when they try to add an incorrect
record to the block they create, or to ignore a record they have
received in the corresponding time slot. The transaction has the
following form:
(detection,k,tx
∗,sigi,pki)
1) kis the index of the time slot where the malicious act is
detected.
2) tx∗is the transaction containing the original record.
3) sigiis the signature of update,k,tx
∗under the public
key pki.
4) pkiis the public key of the administrator creating the
transaction.
Note that administrators use the detection transactions to start
a slot-change protocol for the time slot where the malicious
behavior is detected, i.e., they initiate the protocol for the time
slot stkby propagating a detection transaction to the network,
and receiving 2(n−1)/3valid detection transactions will be
enough for the primary administrator of the slot stk+1 to skip
the slot stkand to start the slot stk+1.
5) Slot Change: A slot-change transaction is created by a
backup administrator of a time slot to initiate a slot-change
protocol when the primary administrator of the corresponding
slot does not create and broadcast the block in a certain time
period. The transaction has the following form:
(slot −change,k,sigi,pki)
1) kis the index of the time slot that the backup administrator
creates the transaction.
2) sigiis the signature of update,k,under the public key
pki.
3) pkiis the public key of the administrator creating the
transaction.
6) Reporting: A reporting transaction is created by an auditor
to report a rate regarding to his observation on the commitment
he has been assigned. It has the following form:
(reporting,O
j,k,p
j,k,C
j,sigk,pkk)
1) Oj,k is the identifier of the auditor assigned to the corre-
sponding commitment Cj.
2) pj,k is the rate value given to the commitment Cjby Oj,k.
3) Cjis the identifier of the commitment.
4) sigkis the signature of the message
reporting,O
j,k,p
j,k,C
junder the public key pkk.
5) pkkis the public key of the auditor Oj,k.
Recall that farmers in our declare commitments by initiating a
smart contract. Every smart contract is associated with a unique
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1166 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 67, NO. 4, NOVEMBER 2020
address. In our system, this address will be considered as the
identifier of the commitment.
V. S ECURITY ANALYSIS
In this section, we discuss the security issues related to the
protocol we proposed. As we stated before, in our platform, any
transaction or any smart contract is broadcast to the network to-
gether with the signature of its content under the public key of the
one creating it. The unforgeability of the underlying signature
scheme ensures that a player cannot create a transaction or smart
contract on behalf of another player, and no one in the system
can change the content of a transaction or a smart contract after
it is deployed to the system.
In our system, administrators add a new block to the ledger by
embedding the hash of the last block in the chain to the new one.
Due to the collision resistant property of the underlying hash
function, it will computationally infeasible for administrators to
change the content of the blocks added to the ledger.
A. Not Fulfilling Commitments
In a yield commitment system, farmers review their produc-
tion policies based on the information the other farmers’ share
for the oncoming harvest season. Farmers, then, determine an
optimal rate for the yield of the product they raise, and share this
rate through a commitment in the network. Moreover, they stick
to the commitment in order to obtain an optimal profit. However,
a malicious producer may manipulate the market by not fulfilling
his/her commitments or not declaring a commitment in order
to maximize his/her profit, and cause the other players of the
platform to loose their investments.
To avoid such cases, we introduced a key concept “reputation”
which is a real number from [0,1] associated to each farmer in
the platform. Reputation value Ruis initially set as 1/2with
the registration transaction for each farmer Fu, and updated at
each commitment by the primary administrators based on the
performance of the farmer. The reputation value can be viewed as
an indicator that shows the reliability of farmers. In other words,
parties in the platform determine whether they should consider
the commitments of a specific farmer by looking at his/her
reputation value when they make their investment plans for the
oncoming harvest season. As we explained before, farmers will
maximize their profit when their commitments are included in
the investment plans of the other farmers. To do so, farmers try
to keep their reputation score high. Thus, the reputation value
forces farmers to act honestly and to stick to their commitments.
B. Neglecting Audits
In our system, farmers periodically declare a yield commit-
ment to the network for each harvest season by initiating a smart
contract. As we stated in Section II, an efficient yield commit-
ment system requires a neutral third party, called “auditor” in our
context, to verify whether the commitment is fulfilled or not. Our
platform chooses auditors among farmers for each commitment
through a smart contract initiated for it. After assigned to a
yield commitment, each auditor makes an observation for the
commitment and reports his observation to the network.
As we discussed in Section II, a malicious auditor may report
a wrong rate to impair the reputation of the producer, or may
report a rate without visiting the corresponding farmland, or
may simply neglect his duty and report nothing for the com-
mitment. First of all, instead of relying on just one auditor,
our system assigns three auditors to each commitment through
the smart contract created for it. Also, it requires auditors to
add a location proof to their reports, which shows that they
have indeed visited the corresponding farmland in the specified
time period. Besides, if the primary administrator detects that
an auditor has not broadcast his/her rate for the commitment
he/she was assigned in the associated time slot, the primary
administrator degrades the reputation of the auditor through an
upgrading reputation transaction. Moreover, for each time slot,
the primary administrator randomly picks one of the auditors and
checks whether he has provided a true report or not by visiting the
corresponding farmland. If the primary realizes that the auditor
has provided a wrong rate, he/she degrades the reputation of the
auditor.
On the other hand, a malicious producer may create smart
contracts in a way that they choose the auditors that the producer
knows. Then, he may make the auditors to report a higher
rate even if he does not meet the commitments. To avoid such
case, each smart contract takes the hash of the last block in
the ledger, and uses this hash as randomness to choose auditors
among all the farmers registered in the system. Since the blocks
considered, here, as the source for the randomness are created by
administrators, producers cannot intervene the auditor selection
process.
C. Updating Reputation With Baseless Rates
In our system, we consider the time as a sequence of discrete
unites that we call time slots, and associate each time slot with an
administrator in round-robin fashion, i.e., each administrator Ai
is associated with the time slot stk, where i=kmod (N+1)
and Nis the integer value assigned to the last administrator reg-
istered in the system. For each time slot, the associated admin-
istrator, called as primary, will create the block Bkwith all the
smart contracts and transactions he/she has received in the cor-
responding time slot together with the hash of the previous block
h(Bk−1), the corresponding time slot as the current time stamp,
the block index k, and a signature of all these records, and append
it to the ledger by using a three-phase protocol presented in [7].
A malicious primary, here, may write a yield commitment or
the report of an auditor created in the associated time slot into
the block he creates different than the actual one. Also, he/she
may prefer not write a specific commitment or a specific report
into the block, and simply ignore it. To prevent such behaviors,
we introduce a special transaction, called detection transaction,
that enables administrators to inform the network about the
malicious behavior of the primary, and to initiate a slot-change
protocol in order to make progress. Since administrators can see
all the transactions propagated in the network, such behaviors
can easily be detected.
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OSMANOGLU et al.: EFFECTIVE YIELD ESTIMATION SYSTEM BASED ON BLOCKCHAIN TECHNOLOGY 1167
On the other hand, a malicious primary may prefer to remain
inactive and not to create block in the associated time slot. In
our system, administrator keep a timer to trace inactive primary
administrators. If administrators will not hear any message
from the primary, they will initiate a slot-change protocol by
multicasting a slot-change transaction in order to move to a new
time slot.
VI. CONCLUSION
Yield estimation was one of the most crucial instruments used
by the market players to devise an effective investment plan.
However, current yield estimation methods provide data only af-
ter sowing-time of crops, and do not provide timely and accurate
results before planting season. On the other hand, designing a
mechanism that allows yield estimation before the sowing-time
will enable the players in agriculture to develop effective and
permanent production policies. Moreover, the conditions of the
food market will be informed in advance and effective counter
measures will be taken for the volatility that may occur in
the market. Within this aim, In this article, we proposed an
efficient yield commitment system that allows farmers to share
their farming plans for the oncoming harvest season with the
other players of the market. Our platform also enables farmers
to observe others’ plan and to revise their investments and
to take necessary steps for the oncoming season, accordingly.
We utilized the blockchain technology to design our platform
that provides a censorship resistant, tamper proof, and strongly
immutable public ledger of time-stamped transactions.
Although the proposed platform provides a robust yield es-
timation mechanism, it can still be improved to more efficient
one. First, the platform can be extended in a way that it provides
an estimation for the total yield of a particular product in the
upcoming harvest season, to the corresponding farmers before
they create the commitments. The estimation can be calculated
using the commitment rates of the corresponding product that
were shared in previous seasons. Second, the platform can be
supported with a user-friendly DApp in order to make it easier for
farmers to adapt. Third, the current version of the platform allows
farmers to declare only a single commitment for a particular
harvest season. However, it would be better for them to update
their commitments a couple of times based on the commitments
shared by the other farmers. Finally, the notion “reputation” can
also be used to even encforce the administrators to follow the
protocol.
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1168 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 67, NO. 4, NOVEMBER 2020
Murat Osmanoglu received his Ph.D. degree in com-
puter science from University of Connecticut, US in
2015.
His Ph.D. thesis introduced new cryptographic
primitives considering the notion grade. He is cur-
rently with the Security and Blockchain Lab, Ankara
University, Ankara, Turkey. His current research in-
terests include cryptography, blockchain technology,
and information security.
Bulent Tugrulreceived his Ph.D. degree in computer
engineering from the Anadolu University, TURKEY
in 2014.
His Ph.D. thesis is on secure spatial interpolation
methods. He is currently an Assistant Professor with
Ankara University, Ankara, Turkey. His current re-
search interests include information security, geo-
statistics, data mining, and big data.
Tuncay Dogantuna received his master’s degree
in forensic informatics from Ankara University,
TURKEY in 2019.
His master’s thesis is on a yield estimation sys-
tem by using blockchain technology. He is currently
a Network and Security Expert at Agricultural and
Rural Development Support Institution in Turkey.
His current research interests include cyber security,
cyber threat intelligence, blockchain, and precision
agriculture.
Erkan Bostanci received the B.Sc. degree in com-
puter engineering, the M.Sc. degree in real-time bat-
tlefield simulation from Ankara University, Ankara,
Turkey, in 2007 and 2009, respectively, and the Ph.D.
degree from the School of Computer Science and
Electronic Engineering, University of Essex, Essex,
U.K., in 2014, with his thesis on real-time user track-
ing for augmented reality.
He was a Research Assistant with the Computer
Science Department, Ankara University. In June
2014, he joined the Gendarmarie Schools Command
as a Planning Officer Designate, where he conducted the research for developing
a vision-based system for analyzing crime scenes. He was promoted to Second
Lieutenant in January 2015. After completing his military service, he was with
Ankara University as an Assistant Professor. In 2018, he was promoted to
Associate Professor. He recently developed a vision-based user-tracking system
for various augmented reality applications for cultural heritage in particular. He
setup the SAAT Laboratory in the department for conducting research with the
main aim of incorporating AI approaches such as fuzzy decision making and
evolutionary computation for solving a wide range of real-world problems from
dental trauma diagnosis to finding optimal parameters in high-energy physics
problems. His research interests include different yet closely related aspects
of computer science from image processing, computer vision, and graphics to
artificial intelligence and fuzzy logic as well as mathematical modeling and
statistical analysis.
Dr. Bostanci has been involved in technical committees for several confer-
ences as well as organizing international conference for several years and acted
as a Reviewer for various journals.
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