Research Square (Research Square),
Journal Year:
2020,
Volume and Issue:
unknown
Published: Dec. 17, 2020
Abstract
Traditionally,
early
warning
systems
for
food
safety
are
based
on
monitoring
targeted
hazards.
Therefore,
risks
generally
detected
only
when
the
problems
have
developed
too
far
to
allow
preventive
measures.
Successful
should
identify
signals
that
precede
development
of
a
risk.
Moreover,
such
could
be
identified
in
factors
from
domains
adjacent
supply
chain,
so-called
drivers
change
and
other
indicators.
In
this
study,
we
show
first
time,
using
dairy
chain
as
an
application
case,
indicators
may
indeed
represent
detection
Using
dynamic
unsupervised
anomaly
models,
anomalies
were
indicator
data
expected
by
domain
experts
impact
milk.
Detrended
cross-correlation
analysis
was
used
demonstrate
various
preceded
reports
contaminated
Lag
times
more
than
12
months
observed.
Similar
results
observed
6
largest
milk-producing
countries
Europe
(i.e.,
Germany,
France,
Italy,
Netherlands,
Poland,
United
Kingdom).
Additionally,
Bayesian
network
hazards
associated
with
Netherlands.
These
suggest
severe
changes
trigger
become
visible
many
later.
Awareness
relationships
will
provide
opportunity
producers
or
inspectors
take
timely
measures
prevent
problems.
A
fully
automated
system
collection,
processing,
warning,
presented
further
support
uptake
approach.
Comprehensive Reviews in Food Science and Food Safety,
Journal Year:
2020,
Volume and Issue:
19(2), P. 875 - 894
Published: Feb. 16, 2020
Big
data
analysis
has
found
applications
in
many
industries
due
to
its
ability
turn
huge
amounts
of
into
insights
for
informed
business
and
operational
decisions.
Advanced
mining
techniques
have
been
applied
sectors
supply
chains
the
food
industry.
However,
previous
work
mainly
focused
on
instrument-generated
such
as
those
from
hyperspectral
imaging,
spectroscopy,
biometric
receptors.
The
importance
digital
text
nutrition
only
recently
gained
attention
advancements
big
analytics.
purpose
this
review
is
provide
an
overview
sources,
computational
methods,
Text
word-level
(e.g.,
frequency
analysis),
word
association
network
advanced
classification,
clustering,
topic
modeling,
information
retrieval,
sentiment
analysis)
will
be
discussed.
Applications
illustrated
with
respect
safety
fraud
surveillance,
dietary
pattern
characterization,
consumer-opinion
mining,
new-product
development,
knowledge
discovery,
supply-chain
management,
online
services.
goal
intelligent
decision-making
improve
production,
safety,
human
nutrition.
Comprehensive Reviews in Food Science and Food Safety,
Journal Year:
2024,
Volume and Issue:
23(1)
Published: Jan. 1, 2024
Abstract
To
enhance
the
resilience
of
food
systems
to
safety
risks,
it
is
vitally
important
for
national
authorities
and
international
organizations
be
able
identify
emerging
risks
provide
early
warning
signals
in
a
timely
manner.
This
review
provides
an
overview
existing
experimental
applications
artificial
intelligence
(AI),
big
data,
internet
things
as
part
risk
identification
tools
methods
domain.
There
ongoing
rapid
development
fed
by
numerous,
real‐time,
diverse
data
with
aim
risks.
The
suitability
AI
support
such
illustrated
two
cases
which
climate
change
drives
emergence
namely,
harmful
algal
blooms
affecting
seafood
fungal
growth
mycotoxin
formation
crops.
Automation
machine
learning
are
crucial
future
real‐time
systems.
Although
these
developments
increase
feasibility
effectiveness
prospective
tools,
their
implementation
may
prove
challenging,
particularly
low‐
middle‐income
countries
due
low
connectivity
availability.
It
advocated
overcome
challenges
improving
capability
capacity
authorities,
well
enhancing
collaboration
private
sector
organizations.
Trends in Food Science & Technology,
Journal Year:
2021,
Volume and Issue:
126, P. 192 - 204
Published: Sept. 6, 2021
Technology
is
being
developed
to
handle
vast
amounts
of
complex
data
from
diverse
sources.
The
terms
"Big
Data"
and
"Decision
Support
Systems"
(DSS)
refer
computerised
multidimensional
management
systems
that
support
stakeholders
in
making
use
modern
data-driven
approaches
identify
solve
problems
enable
enhanced
decision
making.
Big
Data
has
become
ubiquitous
food
safety.
Information
the
supply
chain
scattered
involves
heterogenicity
format,
scale,
geographical
origin.
Also,
interactions
among
environmental
factors,
contamination,
foodborne
diseases
are
complex,
dynamic,
challenging
predict.
Therefore,
this
state-of-the-art
review
article
focuses
on
underlying
architecture
web-based
technologies
for
safety,
focusing
climate
change
influences.
Challenges
adopting
safety
presented,
future
research
directions
regarding
technologies/methods
summarised
analysed.
analysis
discussion
provided
aim
assist
agri-food
researchers
taking
initiatives
gathering
insights
application
DSS
which
would
alleviate
challenges
facilitate
implementation
risk
assessment
while
considering
possible
implications
change.
Food Control,
Journal Year:
2022,
Volume and Issue:
136, P. 108872 - 108872
Published: Feb. 5, 2022
Traditionally,
early
warning
systems
for
food
safety
are
based
on
monitoring
targeted
hazards.
Optimal
systems,
however,
should
identify
signals
that
precede
the
development
of
a
risk.
Moreover,
such
could
be
identified
in
factors
from
domains
adjacent
to
supply
chain,
so-called
drivers
change
and
other
indicators.
In
this
study,
we
show
first
time
indicators
may
indeed
represent
detection
The
dairy
chain
Europe
was
used
as
an
application
case.
Using
dynamic
unsupervised
anomaly
models,
anomalies
were
detected
indicator
data
expected
by
domain
experts
impact
risks
milk.
Additionally,
Bayesian
network
chemical
hazards
milk
associated
with
Netherlands.
results
showed
frequency
varied
per
country
indicator.
However,
all
countries
period
investigated
(2008–2019),
"raw
price"
"barely
no
indicator"
income
farms".
A
cross-correlation
analysis
number
Rapid
Alert
Food
Feed
(RASFF)
notifications
revealed
significant
correlations
many
but
difference
between
observed.
Interesting,
cross
corelation
"milk
significant,
albeit
lag
5
months
(United
Kingdom)
22
(Italy).
This
finding
suggests
severe
changes
trigger
problems
become
visible
later.
Awareness
relationships
will
provide
opportunity
producers
or
inspectors
take
timely
measures
prevent
problems.
Expert Systems with Applications,
Journal Year:
2024,
Volume and Issue:
248, P. 123477 - 123477
Published: Feb. 13, 2024
Proactive
identification
and
the
management
of
disruption
risks
play
a
crucial
role
in
achievement
global
supply
chain's
aims.
Given
velocity
volume
by
which
such
events
occur,
it
is
impractical
to
expect
chain
managers
determine
occurrence
manually.
pressures
facing
chains
due
COVID-19
crisis,
important
for
proactively
identify
their
manage
them
either
achieve
outcomes
or
develop
plans
resilience
against
can
be
built.
In
this
paper,
we
demonstrate
how
integration
natural
language
processing
reinforcement
learning,
are
fundamental
artificial
intelligence
methods,
used
assist
risk
timely
events.
We
explain
detail
our
proposed
approach,
namely
RL-SCRI
show
its
superiority
over
current
models
achieving
aim.
Algorithms,
Journal Year:
2024,
Volume and Issue:
17(5), P. 176 - 176
Published: April 25, 2024
In
the
food
domain,
text
mining
techniques
are
extensively
employed
to
derive
valuable
insights
from
large
volumes
of
data,
facilitating
applications
such
as
aiding
recalls,
offering
personalized
recipes,
and
reinforcing
safety
regulation.
To
provide
researchers
practitioners
with
a
comprehensive
understanding
latest
technology
application
scenarios
in
pertinent
literature
is
reviewed
analyzed.
Initially,
fundamental
concepts,
principles,
primary
tasks
mining,
encompassing
categorization,
sentiment
analysis,
entity
recognition,
elucidated.
Subsequently,
an
analysis
diverse
types
data
sources
within
domain
characteristics
conducted,
spanning
social
media,
reviews,
recipe
websites,
reports.
Furthermore,
scrutinized
perspective
various
scenarios,
including
leveraging
consumer
reviews
feedback
enhance
product
quality,
providing
recommendations
based
on
user
preferences
dietary
requirements,
employing
for
fraud
monitoring.
Lastly,
opportunities
challenges
associated
adoption
summarized
evaluated.
conclusion,
holds
considerable
potential
thereby
propelling
advancement
industry
upholding
standards.
EFSA Journal,
Journal Year:
2018,
Volume and Issue:
16(7)
Published: July 1, 2018
The
European
Food
Safety
Authority's
has
established
procedures
for
the
identification
of
emerging
risk
in
food
and
feed.
main
objectives
are
to:
(i)
to
carry
out
activities
aiming
at
identifying,
assessing
disseminating
information
on
issues
ensure
coordination
with
relevant
networks
international
organisations;
(ii)
promote
data
sources
collection
/or
generation
prioritised
issues;
(iii)
evaluate
collected
identify
risks.
objective(s)
Standing
Working
Group
Emerging
Risks
(SWG-ER)
is
collaborate
EFSA
risks
(ERI)
procedure
provide
strategic
direction
work
building
past
ongoing
projects
related
ERI
procedure.
SWG-ER
considered
methodologies
place
results
obtained
by
EFSA.
It
was
concluded
that
a
systematic
approach
based
experts'
major
strength
but
present,
it
mainly
focused
single
issues,
over
short
medium
time
horizons,
no
consistent
weighting
or
ranking
applied
clear
governance
follow-up
actions
missing.
analysis
highlighted
weaknesses
respect
collection,
integration.
No
methodology
estimate
value
outputs
terms
avoided
there
urgent
need
communication
strategy
addresses
lack
knowledge
uncertainty
perception
issues.
Recommendations
were
given
three
areas:
Further
develop
system-based
including
integration
social
sciences
improve
understanding
interactions
dynamics
between
actors
drivers
development
horizon
scanning
protocols;
Improve
processing
pipelines
prepare
big
analytics,
implement
validation
system
sharing
agreements
explore
mutual
benefits;
Revise
increase
transparency
communication.
