Fucoxanthin
is
a
carotenoid
that
possesses
various
beneficial
medicinal
properties
for
human
well-being.
However,
the
current
extraction
technologies
and
quantification
techniques
are
still
lacking
in
terms
of
cost
validation,
high
energy
consumption,
long
time,
low
yield
production.
To
date,
artificial
intelligence
(AI)
models
can
assist
improvise
bottleneck
fucoxanthin
process
by
establishing
new
processes
which
involve
big
data,
digitalization,
automation
efficiency
This
review
highlights
application
AI
such
as
neural
network
(ANN)
adaptive
neuro
fuzzy
inference
system
(ANFIS),
capable
learning
patterns
relationships
from
large
datasets,
capturing
non-linearity,
predicting
optimal
conditions
significantly
impact
yield.
On
top
that,
combining
metaheuristic
algorithm
genetic
(GA)
further
improve
parameter
space
discovery
ANN
ANFIS
models,
results
R2
accuracy
ranging
98.28%
to
99.60%
after
optimization.
Besides,
support
vector
machine
(SVM),
convolutional
networks
(CNNs),
have
been
leveraged
fucoxanthin,
either
computer
vision
based
on
color
images
or
regression
analysis
statistical
data.
The
findings
reliable
when
modeling
concentration
pigments
with
66.0%
−
99.2%.
paper
has
reviewed
feasibility
potential
purposes,
reduce
cost,
accelerate
yields,
development
fucoxanthin-based
products.
Environmental Technology & Innovation,
Год журнала:
2023,
Номер
32, С. 103277 - 103277
Опубликована: Июль 13, 2023
Innovation
in
digitalization
and
low-carbon
technologies
are
leading
the
way
for
production
sector.
In
context
of
bioeconomy,
a
path
is
opening
up
integration
bio-based
processes
into
value
chain
as
alternative
schemes
to
fossil
fuel-based
models,
although
process
modeling
optimization
needed
this
approach
at
an
early
stage
design
development.
The
large
number
variables
biorefinery
cascade
scheme
presents
inherent
difficulty
strategy,
considering
conditions
that
allow
higher
productivity
revenues
parallel
with
lower
environmental
burdens.
implementation
artificial
intelligence
(AI)
through
techniques
such
machine
learning
predictive
could
be
considered
efficient
tool
optimization.
Such
require
amounts
historical
data
identify
effects,
synergies
clusters
parameters;
detect
anomalies;
develop
models
predictive,
prescriptive
or
root
cause
analysis;
provide
autonomous
control.
sense,
critical
review
report
aims
overview
available
reports
have
AI
evaluation
identifying
its
potentialities
enable
better
strategies
under
principles
sustainability
circular
economy.
This
useful
development
further
research
on
processes.
work
forefront
innovations
meet
efficiency
criteria
order
information
interest
policy
makers,
stakeholders
industry
professionals.
Fucoxanthin
is
a
carotenoid
that
possesses
various
beneficial
medicinal
properties
for
human
well-being.
However,
the
current
extraction
technologies
and
quantification
techniques
are
still
lacking
in
terms
of
cost
validation,
high
energy
consumption,
long
time,
low
yield
production.
To
date,
artificial
intelligence
(AI)
models
can
assist
improvise
bottleneck
fucoxanthin
process
by
establishing
new
processes
which
involve
big
data,
digitalization,
automation
efficiency
This
review
highlights
application
AI
such
as
neural
network
(ANN)
adaptive
neuro
fuzzy
inference
system
(ANFIS),
capable
learning
patterns
relationships
from
large
datasets,
capturing
non-linearity,
predicting
optimal
conditions
significantly
impact
yield.
On
top
that,
combining
metaheuristic
algorithm
genetic
(GA)
further
improve
parameter
space
discovery
ANN
ANFIS
models,
results
R2
accuracy
ranging
98.28%
to
99.60%
after
optimization.
Besides,
support
vector
machine
(SVM),
convolutional
networks
(CNNs),
have
been
leveraged
fucoxanthin,
either
computer
vision
based
on
color
images
or
regression
analysis
statistical
data.
The
findings
reliable
when
modeling
concentration
pigments
with
66.0%
−
99.2%.
paper
has
reviewed
feasibility
potential
purposes,
reduce
cost,
accelerate
yields,
development
fucoxanthin-based
products.
