Abstract
Global
marine
fish
harvest
has
reached
a
plateau
over
the
last
decade.
Efforts
to
increase
aquaculture
tend
face
limitations
in
water
resources
and
contamination
problems.
Of
current
at
least
50%
is
discarded
as
waste.
The
chemical
microbiological
contaminations
limit
utilization
of
harvested
fish.
There
need
improve
preservation
minimize
spoilage
process
them
into
more
appealing
products.
Instead
resorting
individual
food
processing
methods,
efficiency
could
best
be
increased
by
combination
conventional
modern
or
combinations
methods.
Fish
waste
rich
source
oils
containing
essential
fatty
acids,
polypeptides,
amino
polysaccharides
that
utilized
through
upscaling
scientifically
proven
new
technologies.
Separation
collagens,
gelatins,
bioactive
peptides,
edible
oils,
chitosan
form
primary
stages
products
purification
meet
quality
safety
standards,
desirable
industrial
characteristics.
diversity
information
generated
methods
requires
advanced
data
handling
prediction
systems,
such
artificial
intelligence,
address
get
out
utilization.
International Journal of Management Science Research,
Journal Year:
2025,
Volume and Issue:
8(3), P. 71 - 76
Published: March 31, 2025
Food
safety
has
become
a
critical
global
issue,
requiring
effective
solutions
to
reduce
health
risks
and
economic
losses.
The
rapid
advancement
of
artificial
intelligence
(AI)
deep
learning
(DL)
provides
new
opportunities
address
this
challenge.
This
study
presents
multimodal
food
detection
system
that
integrates
computer
vision
(CV),
natural
language
processing
(NLP),
sensor
data
analysis
comprehensively
monitor
contamination,
quality
deterioration,
supply
chain
security.
Specifically,
the
Swin
Transformer
model
is
employed
for
surface
defect
detection,
while
temporal
convolutional
networks
(TCN)
predict
storage
environment
conditions.
Additionally,
blockchain
federated
technologies
are
incorporated
establish
secure
efficient
data-sharing
framework,
enabling
cross-supply
collaboration
enhancing
traceability
accuracy.
Experimental
results
show
achieves
an
accuracy
rate
over
98%
in
contamination
anomaly
monitoring,
significantly
improving
management.
offers
practical
innovative
approach
intelligent
regulation.
Food Safety and Health,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 20, 2025
ABSTRACT
Food
safety
is
a
critical
public
health
concern
for
preventing
foodborne
illnesses
and
ensuring
consumer
protection.
hazards
may
present
throughout
the
food
supply
chain,
from
farm
to
fork,
posing
significant
risks.
This
comprehensive
review
explored
prevalent
in
Bangladesh
highlighted
smart
sensor
technologies
hazard
detection.
By
reviewing
recent
literature
on
Bangladeshi
web,
this
study
discusses
potential
consequences
of
these
their
detection
methods.
Finally,
evaluation
existing
challenges
sensor‐based
techniques
are
provided.
Bacterial
pathogens,
agrochemical
residues,
toxic
preservatives,
adulteration
highly
chain.
The
key
country
lack
awareness,
unhygienic
practices
handling
preparation,
multiplicity
laws
coordination
among
regulatory
authorities,
bureaucratic
complexities,
inadequate
infrastructure
skilled
human
resources.
Smart
offers
promising
solution
limitations
conventional
determination
techniques,
providing
rapid
accurate
results
with
low
cost,
portability,
ease
operation,
thereby
significantly
enhancing
country’s
scenario.
help
policymakers,
academicians
better
understand
chain
develop
more
effective
strategies
mitigating
risks,
safety,
health.
Foods,
Journal Year:
2025,
Volume and Issue:
14(9), P. 1461 - 1461
Published: April 23, 2025
Seafood
plays
a
vital
role
in
human
diets
worldwide,
serving
as
an
important
source
of
high-quality
protein,
omega-3
fatty
acids,
and
essential
vitamins
minerals
that
promote
health
prevent
various
chronic
conditions.
The
benefits
seafood
consumption
are
well
documented,
including
reduced
risk
cardiovascular
diseases,
improved
cognitive
function,
anti-inflammatory
effects.
However,
the
safety
is
compromised
by
multiple
hazards
can
pose
significant
risks.
Pathogenic
microorganisms,
bacteria,
viruses,
parasites,
addition
to
microbial
metabolites,
prominent
causes
foodborne
diseases
linked
consumption,
necessitating
reliable
detection
monitoring
systems.
Molecular
biology
digital
techniques
have
emerged
tools
for
rapid
accurate
identification
these
pathogens,
enhancing
protocols.
Additionally,
presence
chemical
contaminants
such
heavy
metals
(e.g.,
mercury
lead),
microplastics,
per-
polyfluoroalkyl
substances
(PFASs)
increasing
concern
due
their
potential
accumulate
food
chain
adversely
affect
health.
biogenic
amines
formed
during
degradation
proteins
allergens
present
certain
species
also
contribute
challenges.
This
review
aims
address
nutritional
value
health-promoting
effects
while
exploring
multifaceted
risks
associated
with
contamination,
pollutants,
naturally
occurring
substances.
Emphasis
placed
on
enhanced
surveillance,
traceability,
sustainable
aquaculture
practices,
regulatory
harmonization
effective
strategies
controlling
thereby
contributing
safer
supply
chain.
Abstract
Global
marine
fish
harvest
has
reached
a
plateau
over
the
last
decade.
Efforts
to
increase
aquaculture
tend
face
limitations
in
water
resources
and
contamination
problems.
Of
current
at
least
50%
is
discarded
as
waste.
The
chemical
microbiological
contaminations
limit
utilization
of
harvested
fish.
There
need
improve
preservation
minimize
spoilage
process
them
into
more
appealing
products.
Instead
resorting
individual
food
processing
methods,
efficiency
could
best
be
increased
by
combination
conventional
modern
or
combinations
methods.
Fish
waste
rich
source
oils
containing
essential
fatty
acids,
polypeptides,
amino
polysaccharides
that
utilized
through
upscaling
scientifically
proven
new
technologies.
Separation
collagens,
gelatins,
bioactive
peptides,
edible
oils,
chitosan
form
primary
stages
products
purification
meet
quality
safety
standards,
desirable
industrial
characteristics.
diversity
information
generated
methods
requires
advanced
data
handling
prediction
systems,
such
artificial
intelligence,
address
get
out
utilization.
