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 American Journal of  
Food Science and Technology (AJFST)

Integration of  Data Science and Block Chain to Secure Food Safety in Bangladesh
Prasenjit Sarker1*, Chironjit Sarker2, Khadija Huq3

Volume 4 Issue 1, Year 2025
ISSN: 2834-0086 (Online)

DOI: https://doi.org/10.54536/ajfst.v4i1.4787
https://journals.e-palli.com/home/index.php/ajfst

Article Information ABSTRACT

Received: March 20, 2025

Accepted: April 22, 2025

Published: May 15, 2025

Accessibility to safe food & nutrition is sin-qua-non for physical & mental health. Ironically, 
securing safe food & nutrition has been going concern around the world. World Health 
Organization (WHO) states that 1.6 million people worldwide become ill every day from 
contaminated food caused by bacteria, viruses, parasites. In Bangladesh, this issue is very 
severe to light upon instantaneously. Most of  the food stuffs manufactured and processed 
in Bangladesh are unsafe for consumption or adulterated to varying degrees. Excessive use 
of  formalin & DDT in food along with toxic colour in food and unhygienic food handling  
are the significant reasons of  cancer specially breast cancer, liver cancer, & pancreatic cancer  
along with adverse effects on reproductive issue & child mortality. Besides, factories for 
counterfeit products including chocolates, milk, oils , cosmetics of  branded companies have 
been found in all most every district of  country. The purpose of  our study is to understand 
the current scenario of  food contamination at  every level of  supply chain as well as to 
explore how data  science & block chain can be coined together to ensure food safety for 
consumers. Like the densely population, different confrontations for examples sluggish law 
enforcement, ignorance, social security, lower economic pattern have to be solaced down to 
develop proper frame work to secure food safety in Bangladesh.

Keywords

Ignorance, Law Enforcement, Safe 
Food, Social Security, Unhygienic

1 Janata Bank PLC, Bangladesh
2 Department of  Accounting, University of  Dhaka, Bangladesh
3 Foreign Teacher, The Camfirst School, Cambodia
* Corresponding author’s e-mail: prasenjitsarker48@gmail.com

INTRODUCTION
Securing food safety is very hard nut to crack down 
especially in densely populated country like Bangladesh. 
Though good food is prerequisite for good health, 
stakeholders involved in every level of  food supply chain 
are not concerned enough to secure food safety rather 
they commit themselves into different dimensions of  
food contamination as  proper law enforcement along 
with market monitoring, ethics and morality are absent 
in this regard.
The excessive contamination of  food jeopardizes health 
issue at severe stage causing cancer, kidney disease, and 
skin disease etc. No steps come to fruition unless the 
state considers this issue as concerned factor. 
Our study endeavors to explore the root causes behind 
food adulteration, pitfalls of  state management, syndicate 
business etc. Moreover, Integration of  data science 
& block chain technology   may bring this problem to 
fruition.

Research Objectives
This research endeavors to explore 

a) The current scenario of  food contamination as well 
as counterfeit products of  Bangladesh

b) How Data Science & Block Chain can be combined 
together to secure food safety & ensure authentic 
consumable goods.

Scope of  the Study
This study delves into finding out the process & 
developing data base management that will help to 
extract current scenario of  food contamination at every 

level of  supply chain in the agro-based products largely 
sold out in an open space called bazaar in Bangladesh. 
It can connect administration, ministry, law enforcement 
department & other assigned departments under a same 
umbrella. Additionally, this study may also help out to 
correlate other sub continental markets like India, Sri 
Lanka or other countries facing same kinds of  challenges 
& desiring solution to secure food safety.

LITERATURE REVIEW
Food has been contaminated at every level of  supply 
chain (Noman, 2013). Our study fills the gap of  that 
study by developing central data base module that the 
records of  every participants of  the supply chain will be 
centrally stored  that may lead to strong law enforcement 
as data is always available.
Different challenges faced by entrepreneurs specially at 
supply chain management to initiate a start –up (Sarker, 
2020). In our study, a central data base will be proposed. 
This data base will be connected & conducted by 
government administration and every player of  the supply 
chain will be under surveillance that will definitely reduce 
the risks of  supply chain especially for entrepreneurs.
A comprehensive model including real time keeping 
system, different types of  QR models etc can contribute 
food supply chain management using block chain (Asha 
et al., 2020). Our study will propose a model that will very 
adaptive for Bangladeshi market.
Different challenges including budgetary constrain to 
develop block chain & data science technology  include 
data mining challenges as growing surge of  data around 
the world (Chen et al.,2019).Our study proposes how 



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budget for centrally developed data base management 
along with data science & block chain can be coined with 
national budget.
Several measures for example Radio Frequency 
Identification (RFID), tamper proof  protected system, 
shared data etc can play vital role to adopt block chain 
technology in live stock farming (Patel et al., 2023). Our 
study will propose adaptive measures to all levels of  
supply chain management in agricultural sector.
IOT (Internet of  Things) refers a network of  physical 
objects that are connected to the internet & can exchange 
data with other devices & system (Ping et al., 2018). In 
our study, we endeavor to explore how IOT will help us 
to work on developing proper supply chain management 
with private ledger with controlled network.
The convergence of  data science & block chain explores 
several benefits of  data science & block chain while coined 
together like security & privacy, credibility & transparency, 
data sharing, protection of  data sovereignty ( Peng & Liu, 
2020). In our study will extract how convergence of  data 
science & block chain contributes record keeping system 
of  distributed ledger to secure food safety at every level 
of  supply Chain Management. 
Block chain technology can contribute agro-food supply 
chain (Shahid et al., 2020).Our study endeavors to find out 
how integration of  data science & block chain will create 
private distributed ledger for the commercial private 
factories to prevent counterfeit products on large scale.
Several opportunities & challenges of  block chain 
technology should have been explored on large scale (Zheng 
et al., 2018).Our study will find out different challenges 
to implement block chain technology in the context of  
agricultural based food supply chain of  Bangladesh.
There is insufficiency of  tags’ description of  safe food 
in Bangladesh (Shehen, 2024). Our study will explore 
encryption method in which data base incurs all 
information about food supply chain participants.

MATERIALS AND METHODS
To examine the research objectives, this study includes 
both qualitative & quantitative measures. 

Research Design
Qualitative Measures
In  data collection process, qualitative data have been 
collected & analyzed  from different sources for examples- 
various journals, books, business magazines , internet etc.

Quantitative Measures
In this study, quantitative measures have been conducted 
using several statistical tools for example- mean, media, 

mood, and regression & correlation analysis along with 
some computational tools including MS Office, SPSS 
etc. Besides, several interviews of  assigned persons have 
been conducted at field levels of  the administrations. To 
explore the current scenario of  food contamination of  
Bangladesh, several hypotheses testing have been done to 
understand what factors actually instigate the all level of  
suppliers to commit food contamination. To test those 
hypotheses, 330 respondents have been met to give their 
insights on the interval scale weighted 1 for very negative 
response & 5 for very positive scale. Moreover, z-test 
along with 95 percent confidence level have been done.
H0: Amoral mentality does not instigates food 
contamination
H1: Amoral mentality instigates food contamination

Dependant Variable
Food Contamination

Independent Variable
Amoral Mentality
H0: Weak law enforcement does not encourage level of  
corruption of  food suppliers
H1: Weak law enforcement encourages corrupted food 
suppliers

Dependant Variable
Corruption of  food suppliers

Independent Variable
Law enforcement
H0: Assigned authorities does not lack proper 
technological knowledge to secure food safety
H1: Assigned authorities lack proper technological 
knowledge to secure food safety

Dependant Variable
Proper technological knowledge

Independent Variable
Food security
H0: Agricultural Sector does not fail to attract educated 
entrepreneurs to secure food safety
H1: Agricultural Sector fails to attract educated 
entrepreneurs

Dependant Variable
Food safety

Independent Variable
Educated Entrepreneurs

Table 1: Hypotheses Testing Framework
Statement Scale/ 

Question
Distribution Table Confidence 

Level
Test 
Type

Sample Size

Amoral mentality 
does not instigate 
food contamination

Likert Scale Z-Test Distribution 
Table

95 Percent One 
-Tailed

330



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Am. J. Food. Sci. Technol. 4(1) 90-98, 2025

Sample Size Determination
For Large Population: n= Z2.p.(1-p)/E2 (95% Confidence 
Level ,5% margin of  error& p is 0.5) n=1.962.0.5.05/0.052  
=384.16  people needed. In our survey, 55 persons have 
not responded. Consequently, 330 respondents are 
considered to be sample size 

RESULT AND DISCUSSION
The Current Scenario of  Food Contamination as 
well as Counterfeit Products of  Bangladesh
Accessibility to good food is becoming very hard nut to 
crack down in Bangladesh. Since Bangladesh is a very 
densely populated country, to secure food safety is very 
challenging as there is no environmental plan, proper 
law enforcement, poor literacy etc. About more than 
3500-4000 tones of  solid wastes per day from industrial 
discharge, fossil fuels , sewage sludge and municipality 
waste have been generated in Dhaka city. Consequently, 
these heavy metals  like arsenic, cadmium, chromium, 

Weak law 
enforcement does not 
encourages corrupted 
food suppliers

Likert Scale Z-Test Distribution 
Table

95 Percent One 
-Tailed

330

Assigned authorities 
does not lack 
proper technological 
knowledge to secure 
food safety

Likert Scale Z-Test Distribution 
Table

95 Percent One 
-Tailed

330

Agricultural Sector 
does not fail to 
attract educated 
entrepreneurs

Likert Scale Z-Test Distribution 
Table

95 Percent One 
-Tailed

330

Statement Strongly 
Disagree (1)

Disagree 
(2)

Uncertain 
(3)

Agree (4) Strongly 
Agree (5)

Sample 
Mean

Standard 
Deviation

Amoral mentality 
does not instigate 
food contamination

187 98 2 27 16 1.74 1.12

Weak law 
enforcement does not 
encourages corrupted 
food suppliers

249 55 1 15 10 1.43 .94

Assigned authorities 
does not lack 
proper technological 
knowledge to secure 
food safety

173 86 16 41 14 1.9 1.35

Agricultural Sector 
does not fail to 
attract educated 
entrepreneurs

193 79 8 27 23 1.81 1.53

Table 2: Hypothesis Testing Formula
Sample Mean (x̄) Standard Deviation Upper Limit Lower Limit
∑xi/n √(x- X̄)2/n-1 µ+Z(standard deviation/√n) µ-Z(standard deviation/√n)

Table 3:
Contaminants Ill-Purpose
Formalin Preservation of  Fish, Meat, 

Milk
Calcium Carbide Fruit to ripen
Brick Dust Chili powder
Urea To whiten rice & puff   rice
Saw Dust Loose tea
Melamine Milk Powder
Soap Ghee
Artificial Sweetener, 
coal tear & textile dyes

Sweetmeat

Sulfuric Acid Milk Condensation
DDT To dry fish
Ethylene Oxide To ripen Bananas, papaya and 

other fruits



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copper, lead, mercury etc are absorbed by vegetables  
through soil and cause serious health diseases like cancers, 
kidney failure etc. According to Public Health Laboratory 
of  Dhaka City Corporation, proportionate contaminated 
food items ranges from 70 to 90 percent. More than 
76 percent food items in the market have been found 
adulterated.  Moreover, According to the International 
Centre for Diarrhea Disease & Research , Bangladesh, 50 
percent of  the food samples ( over 150 items of  random –
test) were found adulterated. In agricultural sector, textile 
dyes are spread on fish ( a very vital source of  protein), 
vegetables, fruits etc.
Approximately, 30 million people experience at least one 
form of  food borne disease each year in Bangladesh (Al 
Banna et al.,2021) , Nevertheless, the food safety system 
& the regulatory framework in the country are still in 
their fancy (world university)
To explore the current scenario more transparently, 
we have conducted hypothesis test with the raw data 
collected from different respondents involved in different 
levels of  food supply chain.
H0: Amoral mentality does not instigates food 
contamination
H1: Amoral mentality instigates food contamination

Dependant Variable: Food Contamination
Independent Variable: Amoral Mentality
To test this hypothesis, Likert Scale, very essential for 
attitude testing, has been used where strongly disagree 
has been given the weight 1 and strongly agree has been 
given the weight 5 as well. On the basis of  the weight, 
the hypothesis can be rewritten as below:H0: μ = 4H1: 
μ< 4To test this hypothesis, agree with the statement 
given to the 55 respondents has been given the weight 
4.Subsequently, the calculated sample mean(X̄) is 1.72 
with the standard deviation of  1.044 and the test has been 
conducted with the 5 percent significance level. 

Lower Limit
μ-Z(standard deviation/√n)= 4-1.65(1.12/√55)=4 
-0.1017= 3.89
z-Test: Two Sample for Means

Result  
This test has been conducted as left one tailed z test 
where as sample mean (X̄) 1.7484 which is lower than 
lower limit i.e 3.89 & belongs to the area of  the rejection. 
Moreover, Critical Value< Z value; -1.2815< 36.288. So, 
It can be concluded that H0 (null hypothesis) is rejected 
& consequently, Ha (alternative hypothesis) is accepted. 
So, It can be said that “Amoral mentality instigates food 
contamination”.
H0: Weak law enforcement does not encourage level of  
corruption of  food suppliers
H1: Weak law enforcement encourages corrupted food 
suppliers

Dependant Variable:  Corruption of  Food Suppliers
Independent Variable: Law Enforcement

Table 4:
Column1 Variable 1 Variable 2
Mean 1.748484848 0
Known Variance 1.27 0.000001
Observations 330 1
Hypothesized Mean 
Difference

4

z -36.28888017
P(Z<=z) one-tail 0
z Critical one-tail 1.281551566
P(Z<=z) two-tail 0
z Critical two-tail 1.644853627

Table 5:
Column1 Column2 Column3
z-Test: Two Sample for Means
 Variable 1 Variable 2
Mean 1.43030303 0
Known Variance 0.89 0.000001
Observations 330 1
Hypothesized Mean 
Difference

4

z -49.47244549
P(Z<=z) one-tail 0
z Critical one-tail 1.281551566
P(Z<=z) two-tail 0
z Critical two-tail 1.644853627  

Lower Limit
μ -Z(standard deviation/√n)= 4-1.65(.94/√330)= 4 
-0.085= 3.915

Result
This test has been conducted as left one tailed z test 
where as sample mean (X̄) 1.43030 which is lower than 
lower limit i.e 3.91 & belongs to the area of  the rejection. 
Moreover, Critical Value< Z value; -1.2815< 49.47. So, It 
can be concluded that H0 (null hypothesis) is rejected & 
consequently, Ha (alternative hypothesis) is accepted. So, 
It can be said that “Weak law enforcement encourages 
corrupted food suppliers’’
H0: Assigned authorities does not lack proper 
technological knowledge to secure food safety
H1: Assigned authorities lack proper technological 
knowledge to secure food safety

Dependant Variable: Proper Technological Knowledge
Independent Variable: Food Security



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Lower Limit
μ -Z(standard deviation/√n)= 4-1.65(1.35/√330)=4 
-0.1226= 3.8774

Result
This test has been conducted as left one tailed z test 
where as sample mean (X̄) 1.9 which is  lower than lower 
limit i.e 3.8774 & belongs to the area of  the rejection. 
Moreover, Critical Value< Z value; -1.2815< 28.274. So, 
It can be concluded that H0 (null hypothesis) is rejected 
& consequently, Ha (alternative hypothesis) is accepted. 
So, It can be said that Assigned authorities lack proper 
technological knowledge to secure food safety
H0: Agricultural Sector does not fail to attract educated 
entrepreneurs to secure food safety
H1: Agricultural Sector fails to attract educated entrepreneurs

Dependant Variable:  Food safety
Independent Variable: Educated Entrepreneurs

Result
This test has been conducted as left one tailed z test 
where as sample mean (X̄) 1.81 which is  lower than 
lower limit i.e 3.862 & belongs to the area of  the rejection. 
Moreover, Critical Value< Z value; -1.2815< 25.980. So, 
It can be concluded that H0 (null hypothesis) is rejected 
& consequently, Ha (alternative hypothesis) is accepted. 
So, It can be said that Agricultural Sector fails to attract 
educated entrepreneurs.
In Bangladesh, negative societal attitude, lack of  
technological innovations, venture capital fund 
unavailability, political instability are triggered as 
challenges to attract educated entrepreneurs in agricultural 
sector(sarker,2020). Without proper education & trainings 
moral values, food safety can’t be ensured as the reasons 
being that the maximum participants in the  supply chain 
lack of  proper education, moral values and directed by 
extreme materialism.

Hypocrisy Directed by Lack of  Moral Values
All participants involved in the supply chain give their 
consent not to support any food contamination at any 
level of  supply chain while selling or manufacturing 
consumable goods. Ironically, they shift liabilities on 
other head and claim themselves to be honest even after 
being exposed to be involved in food contamination 
, which  is, to some extent, related to Psychological 
term “ Hypocrisy”. Occurrence of  hypocrisy when the 
by society most despised types pretend to be the most 
revered type (Hallman & spiro, 2022). In Bangladesh, 
maximum people pretend to be honest by maintaining 
their religious values & other morals but maximum 
business are disguised in the name of  religion and they 
commit food contamination, unethical food stock only 
for seeking more profits jeopardizing the health of  
consumers to very severe state.
State has become completely failure to raise real ethical 
values since childhood though various educational 
institutions are working to build morals but people of  all 
levels accepts morals for others not for themselves. Lack 
of  resources, poor human resource management, poor 
technological innovation, over population problems are 
the facts should be come into fruition.
State along with proper law enforcement authorities 
should move forward to make stance against suppliers 
in food supply chain involved in food contamination. 
Several psychological studies are recommended to be 
done about the psychological state of  the people of  
Bangladesh in a large frame even if  it is a very long term 
process but it will make sense in future to direct a nation 
in a unified way.

Combination of  Data Science & Block Chain to 
Secure Food Safety as well as to Ensure Authentic 
Consumable Goods
Technological Surge:Data Science & Block Chain
The escalating of  data generation in contemporary 
society has fueled innovation while raising concerns 

Table 6:
Column1 Column2 Column3
z-Test: Two Sample for Means
 Variable 1 Variable 2
Mean 1.9 0
Known Variance 1.82 0.000001
Observations 330 1
Hypothesized Mean 
Difference

4

z -28.27490806
P(Z<=z) one-tail 0
z Critical one-tail 1.281551566
P(Z<=z) two-tail 0
z Critical two-tail 1.644853627

Table 7:
Column1 Column2 Column3
z-Test: Two Sample for Means
 Variable 1 Variable 2
Mean 1.812121212 0
Known Variance 2.34 0.000001
Observations 330 1
Hypothesized Mean 
Difference

4

z -25.98015141
P(Z<=z) one-tail 0
z Critical one-tail 1.281551566
P(Z<=z) two-tail 0
z Critical two-tail 1.644853627  

Lower Limit
μ -Z(standard deviation/√n)= 4-1.65(1.53/√330)=4 
-0.138= 3.862



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about the security and transparency of  data transaction 
(Tatineni &Boppana, 2021). This research delves into 
synergy between data science & block chain to safeguard 
food safety at every level of  supply chain along with data 
integrity and unprecedented data transparency as well.
The ceaseless surge of  data generation in the contemporary 
world necessitates the data insightfulness from big 
data to be mined out.  Data mining significantly plays 
pivotal rule to extract the effective data to understand 
the real problem as well as to design effective module as 

comprehensive solution. 
Ciphering involves both data encryption and data 
decryption using the mathematical algorithm to secure 
data integrity and data transparency. This process 
transforms readable data into unrecognizable form called 
cipher text. Subsequently, the conversion of  cipher text 
into plain text is called decryption. Moreover, private 
key is widely used for encrypting data and private key 
is used for decrypting data remaining very secret & non 
recoverable if  forgotten.

Figure 1: Process of  Block Chain Technology

Types of  Encryption
Symmetric Encryption
Symmetric Encryption, less secured than asymmetric 
encryption, uses a single key for both encryption and 
decryption. It is often used for encrypting data stored locally.

Asymmetric Encryption
Asymmetric Encryption uses two keys called public 
key and private key. Moreover, public key is used for 
encrypting data and private key is used for decrypting 
data. It is more resistant to cyber attack and more flexible 

as it involves only two parties.
Although, It is more complex than symmetric encryption, 
It allows to create digital signature used to verify the 
authenticity and integrity of  a message file.

Block Chain
A block chain is a distributed database or ledger that 
maintains ceaseless progressing lists of  ordered records 
called bocks. Cryptography links each block using 
cryptography and every block contains the cryptographic 
hash of  previous block, a timestamp, and data transaction.

Figure 2: Block Chain Technology along with distributed Ledgers



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In 2008, Satoshi Nakamoto invented block chain to 
serve as the ledger of  public transaction related to crypto 
currency bitcoin- first digital currency to solve the double 
–spending problem without need of  central server or 
trusted authority.
Blockchain  originated as a result of  bitcoin , a technological 
innovation that is a sent out data source along with the 
constantly improving files viewed as block. Furthermore, 
It is always expanding as brand new blocks are put by 
miners to it (every ten minutes) to capture the newest 
transaction .Block chain is the process of  decentralization 
which gives each party the right to access the entire 
database and can verify the record throughout the entire 
database without involving of  middleman or single party 
control.  Block chain technology is the unprecedented 
solution for data security .Fabrication or temperament of  
data seems to be near to impossible in system as every 
node records all data. If  any sort of  data twisting happens, 
it must be verified by the all participants of  the ledgers 
using hashing which interlinks previous link to next block.

Data Science & Block Chain Integration
The surge of  data science technology is fueling the risks 
of  data management at similar pace. Data leakage, data 
temperament, low quality of  data needs to be addressed in 
data risk management. Data science  relates to block chain 
with high data quality, traceability, built in anonymity & 
large data volume(Hussain & kishoth,2022).Block chain 
technology is the comprehensive solution for aggravating 
risk of  data management. In case of  data sharing, block 
chain technology brings point to point transmission, 
consensus mechanism, and encryption algorithm as 

well as the solution for the data risk management. Block 
chain technology ensures data security, data privacy, data 
credibility, data transparency, and protection of  data 
sovereignty (Peng & Liu,2021).  Although the integration 
of  data science and block chain technology is growing 
faster, It still involves some challenges for example data 
scalability, data accuracy, data insightfulness etc.

Data Scalability
In data science technology, a lot of  data needs to be 
sorted out , processed and analyzed  called data mining. A 
large scale of  data needs large storage capacity. Sometime 
it seems to be very difficult to manage a large number 
of  data from big data which incurs costs for research & 
development and incapacitates the company to thrive out 
competitive advantage.
Although block chain brings many advantages that other 
technology doesn’t have, it is still exposed to scalability 
issue that prevents real time trading (Caret et al., 2017).

Data Accuracy for Research & Development
The immense protection of  data some time obstructs 
researchers to get the real & accurate data which is very 
important to predict future market and make decision 
over current market as well. The integration of  data 
science & block chain constructs very sophisticated 
network in which mining data for predictive analysis 
is very challenging. It is still very hard nut to crackle to 
extract real data insights from big data for accurate market 
analysis.  A large number of  data sets require more secured 
storage. The verification process in the distributed ledger & 
auditing of  big data are still challenging (Aujla et al., 2022).

Figure 3: Proposed Model integrating Data Science & Block Chain



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According to Shehen (2024), tags’ descriptions of  safe 
food are insufficient in Bangladesh.A model integrating 
data science & block chain has been proposed where 
a centralized data base monitored and handled by 
government stores all sets of  data incurred from the 
stakeholders   involved in the  whole supply chain. Here, 
in a proposed model, concerned ministry of  government 
is linked with all components of  chain of  command 
maintaining proper protocol including  district level to 
upazila  level. Moreover, all buyers & sellers should be 
enlisted in to their concerned authority of  their business 
area & should provide all necessary information about 
product for example where he collects his / her products 
from? A data collection center should be existed in the 
bazaar which collects data from sellers & buyers end (in 
wholesale market). The whole data base should be linked 
with centralized data base (private distributed ledger) 
solely controlled by ministry of  agriculture. 
Besides, ministery should provide QR-code marked eco 
friendly shopping bags for end level consumers by which 
consumer can access to all data regarding the products 
including manufacturer, whole seller, retailer, product 
specification etc.  This shopping bags should be provided 
by enlisted data collection center & bazaar monitoring 
cell who will collect information about businessmen 
involved in that bazaar & distribute that QR-code marked 
shopping bags which will provide the information about 
businessmen at bazzar level collecting from the mother 
database controlled by ministry level.

Step by Step Progression
➢ Setting up Data Collection center at every bazzar 

(Whole sale & Retail perishable goods market)
➢ Enlisting categorically all whole sale sellers & 

wholesale buyers and giving them registration number 
specified for specific place i.e. no one can use registration 
number for more than one bazzar/ markets
➢ In whole sale market, buyers & sellers both provide 

information about products for example- who does he /
she purchase product from ? or who does he/she sell the 
products to?
➢ In wholesale market buyers gets QR marked bags 

provided by ministry containing all information about 
seller
➢ In retail market, consumer (end customer) gets 

the QR marked bags containing all information about 
manufacturer, whole seller & retailer as well.
By doing all that, consumers at end level can get to all 
information about products & easily claim about involved 
party if  any sort of  food contamination occurs. This 
process can be revolutionary step to stance against food 
contamination. In addition, law enforcement authority 
can easily trace out which party is directly engaged with 
the food contamination and ensure punishment in a 
perfect way. Due to this process, there will be no room 
for passing one’s sinful responsibility on other’s neck.

CONCLUSION
In this study, we endeavor to explore the current 
scenario about food safety in Bangladesh. Besides, by 
ensuring the proper process of  the proposed model will 
certainly ameliorate the current situation of  food safety 
of  Bangladesh and definitely will contribute to ensure 
transparency, integrity, proper law enforcement and 
commitment towards consumers. A proper stance against 
food contamination will lead to ensure sound health & 
mind as well & obviously reduce medical expenses & 
health hazards as well.

Acknowledgement
The authors of  this research are very grateful to the 
respondents who have spontaneously participated in 
survey.  

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