Blue-Green Systems,
Journal Year:
2024,
Volume and Issue:
6(2), P. 310 - 326
Published: Oct. 9, 2024
ABSTRACT
This
study
investigated
the
efficacy
of
ozone
treatment
on
Vibrio
pathogen
removal
within
a
simulated
earthen
shrimp
pond,
conducted
in
three
phases.
First,
physical
and
chemical
properties
soil,
alongside
pathogen,
were
assessed.
Results
indicated
neutral
pH
levels,
high
organic
matter,
carbon
content,
with
load
1.0
±
0.0
×
103
CFU/mg.
Second,
was
applied,
comparing
its
effectiveness
control
between
treated
untreated
soil
sets.
The
set
exhibited
significantly
lower
(6.00
1.41
CFU/mg)
compared
to
(2.00
2.12
105
CFU/mg),
resulting
97.23%
eradication
efficiency.
Concurrently,
ammonia
rates
decreased
ozone,
indicating
potential
benefits
for
aquaculture.
Finally,
application
pond
over
45
days
effectively
controlled
pathogens.
In
set,
levels
rose
9.48
1.73
CFU/mg,
while
ozone-treated,
they
ranged
from
6.5
1.25
0.29
Shrimp
growth
parameters,
including
average
daily
gain,
survival
rates,
feed
conversion
ratio,
groups,
suggesting
treatment's
feasibility
without
adverse
effects
growth.
Water
quality
parameters
remained
suitable
ranges
cultivation.
These
findings
highlight
ozone's
as
an
effective
method
aquaculture,
implications
industry
sustainability
productivity.
The Science of The Total Environment,
Journal Year:
2024,
Volume and Issue:
920, P. 171047 - 171047
Published: Feb. 17, 2024
Climate
change
is
one
of
the
most
significant
challenges
worldwide.
There
strong
evidence
from
research
that
climate
will
impact
several
food
chain-related
elements
such
as
agricultural
output,
incomes,
prices,
access,
quality,
and
safety.
This
scoping
review
seeks
to
outline
state
knowledge
supply
chain's
vulnerability
identify
existing
literature
may
guide
future
research,
policy,
decision-making
aimed
at
enhancing
resilience
chain.
A
total
1526
publications
were
identified
using
SCOPUS
database,
which
67
selected
for
present
study.
The
assessment
methods
well
adaptation
measures
have
been
employed
alleviate
in
chain
discussed.
results
revealed
a
growing
number
providing
weakening
due
extreme
weather
events.
Our
demonstrated
need
broaden
into
entire
various
forms
climatic
variability
because
studies
concentrated
on
relationships
between
fluctuations
(especially
rainfall,
temperatures,
drought)
production.
lack
about
effects
underlying
socio-economic
consequences
could
result
underperformance
or
failure
Sustainable Production and Consumption,
Journal Year:
2023,
Volume and Issue:
41, P. 242 - 252
Published: Aug. 20, 2023
Recirculating
aquaculture
systems
(RASs)
have
been
identified
as
having
high
potential
for
development,
attributed
to
their
significant
advantages,
such
higher
productivity,
reduced
water
consumption,
and
improved
sustainability.
However,
increased
energy
requirements
due
the
amount
of
recycling
temperature
control
leads
operational
costs
added
environmental
impacts
from
use
fossil
fuels,
causing
a
barrier
widespread
deployment.
This
study
examines
renewable
integration
with
RASs
improve
financial
feasibility,
while
also
presenting
an
overview
its
challenges
system
optimisation
modelling,
which
is
presently
absent
in
existing
literature.
Renewable
coupled
more
efficient
practices
through
process
advanced
monitoring
has
make
sustainable
profitable.
offers
comprehensive
understanding
sustainability
concerning
demands
RASs,
growth
by
adopting
wider
dynamic
directions
problem-solving
using
models.
To
address
intermittency
instability
that
arise
development
RAS,
research
on
economic
needed
meet
design,
planning,
scheduling,
operation,
aquaculture.
Systematic
decision-making
guidelines
greater
efficiency
based
modelling
can
help
UN
Sustainability
Development
Goals
(SDGs).
With
new
technological
advances
energy,
artificial
intelligence
treatment,
system-based
models
may
identifying
types,
technology
options
improvements
should
be
integrated
into
different
transform
competitiveness
industry.
Fishes,
Journal Year:
2024,
Volume and Issue:
9(10), P. 386 - 386
Published: Sept. 28, 2024
Water
quality
early
warning
is
a
key
aspect
in
industrial
recirculating
aquaculture
systems
for
high-density
shrimp
farming.
The
concentrations
of
ammonia
nitrogen
and
nitrite
the
water
significantly
impact
cultured
animals
are
challenging
to
measure
real-time,
posing
substantial
challenge
technology.
This
study
aims
collect
data
samples
using
low-cost
sensors
during
process
construct
predictive
values
nitrite,
which
difficult
obtain
through
environment,
prediction
techniques.
employs
various
machine
learning
algorithms,
including
General
Regression
Neural
Network
(GRNN),
Deep
Belief
(DBN),
Long
Short-Term
Memory
(LSTM),
Support
Vector
Machine
(SVM),
build
models
nitrite.
accuracy
determined
by
comparing
predicted
with
actual
values,
performance
evaluated
Mean
Absolute
Error
(MAE),
Percentage
(MAPE),
Root
Square
(RMSE)
metrics.
Ultimately,
optimized
GRNN-based
model
concentration
(MAE
=
0.5915,
MAPE
28.95%,
RMSE
0.7765)
0.1191,
29.65%,
0.1904)
were
selected.
can
be
integrated
into
an
Internet
Things
system
analyze
changes
over
time
management
routine
conditions,
thereby
achieving
application
environment
