A deep learning model for estimating body weight of live pacific white shrimp in a clay pond shrimp aquaculture
Intelligent Systems with Applications,
Год журнала:
2024,
Номер
24, С. 200434 - 200434
Опубликована: Сен. 1, 2024
This
paper
presents
a
novel
approach
to
address
the
crucial
challenge
of
accurately
determining
total
weight
shrimp
within
aquaculture
ponds.
Precise
estimation
is
in
mitigating
issues
overfeeding
and
underfeeding,
thus
enhancing
efficiency
productivity
farming.
The
proposed
system
leverages
image
processing
techniques
detect
individual
live
extract
pertinent
features
for
clay
pond
environment.
Specifically,
an
automated
feed
tray
captures
images
shrimp,
which
are
then
processed
using
combination
Detectron2,
PyTorch,
CUDA
(Compute
Unified
Device
Architecture)
detection.
Essential
such
as
area,
perimeter,
width,
length,
posture
extracted
through
analysis,
enabling
accurate
weight.
An
Artificial
Neural
Network
(ANN)
model,
utilizing
these
features,
predicts
with
coefficient
determination
(R2)
94.50%
when
incorporating
all
features.
Furthermore,
our
integrates
user-friendly
web
application
that
empowers
farmers
monitor
trends,
facilitating
precision
feeding
strategies
effective
farm
management.
study
contributes
low-cost
solution
deep
learning
model
estimate
Pacific
white
ponds,
daily
calculations,
helping
optimize
quantities,
providing
size
distribution
insights,
reducing
Feed
Conversion
Ratio
(FCR)
greater
profitability.
procedure
feature
extraction
also
provided,
including
calculation
length
well
shimp
classification.
Язык: Английский
100 Years of Penaeid Domestication and Meta-Analysis of Breeding Traits
Reviews in Fisheries Science & Aquaculture,
Год журнала:
2025,
Номер
unknown, С. 1 - 20
Опубликована: Май 7, 2025
Язык: Английский
Shrimp phenotypic data extraction and growth abnormality identification method based on instance segmentation
Computers and Electronics in Agriculture,
Год журнала:
2024,
Номер
229, С. 109701 - 109701
Опубликована: Дек. 2, 2024
Язык: Английский
100 years domestication of penaeid shrimp and meta-analysis of breeding traits
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Июнь 27, 2024
Abstract
Penaeid
shrimp
farming
plays
a
pivotal
role
in
ensuring
future
food
security
and
promoting
economic
sustainability.
Compared
to
the
extensive
long
history
of
domestication
observed
terrestrial
agriculture
species,
selective
breeding
penaeids
are
relatively
recent
endeavors.
Selective
aimed
at
improving
production
traits
holds
significant
promise
for
enhancing
efficiency
reducing
environmental
impact
farming,
thereby
contributing
its
long-term
Assessing
genotype-by-environment
(G-by-E)
interactions
is
essential
programs
ensure
that
improved
penaeid
strains
perform
consistently
across
different
environments,
with
genomic
selection
proving
more
effective
than
sib-testing
alone
mitigating
sensitivity.
Genome
editing
tools
like
CRISPR/Cas9
offer
potential
accelerate
genetic
gains
by
enabling
rapid
introduction
desired
changes,
advancements
showing
promising
results
achieving
high
transfection
embryos.
Additionally,
artificial
intelligence
machine
learning
being
leveraged
streamline
phenotyping
enhance
decision-making
accuracy
managing
predicting
disease
outbreaks.
Herein,
we
provide
an
overview
update
on
shrimp,
including
current
status
principal
farmed
key
milestones
history,
targeted
programs,
advantages
integrating
genomeic
traits,
directions
shrimp.
Язык: Английский
Body weight prediction models of Macrognathus pancalus (Hamilton, 1822) from morphometric traits using principal component analysis
Indian Journal of Fisheries,
Год журнала:
2024,
Номер
71(2)
Опубликована: Июнь 30, 2024
In
the
present
study,
an
attempt
was
made
to
evaluate
body
weight
of
barred
spiny
eel
based
on
morphologic
traits.
Ten
morphometric
characters
and
five
meristic
counts
were
measured
for
38
specimens,
ranging
in
standard
length
from
77.80
149.60
mm
2.02
17.89
g
weight.
All
data
sets
standardised
using
z-transformationmethod.
The
Kaiser-Meyer-Olkin
(KMO)
test
performed
measure
sample
adequacy
level,
which
found
be
0.85.
significance
correlation
matrix
all
traits
tested
with
Bartlett’s
sphericity,
significant
(χ2
=
793.360,
df
105,
p<0.01).
Four
fifteen
principal
components
(PCs)
explained
around
85%
total
variation.
first
component
(PC1)
contributed
57.52%
variation
represented
by
positive
high-loading
factors
pre-dorsal
(PDL),
pre-anal
(PAL),
(SL).
second
(PC2)
10.90%
anal
fin
rays
(AFR)
dorsal
(DFR).
third
fourth
9.26
7.41%
showed
high
loading
pectoral
(PFR),
caudal
(CFR),
respectively.
estimated
communalities
ranged
0.658
eye
diameter
(ED)
0.978
(PDL).
species’
predicted
stepwise
multiple
regression
interdependent
four
extracted
PCs.
Stepwise
revealed
that
a
combination
three
variables,
such
as
depth
(BD),
post-orbital
(POL),
best
predict
species
coefficient
determinant
value
(r2
93).
Therefore,
study
confirms
is
function
variables
rather
than
orthogonal
variables.
Keywords:
Body
measurements.
Macrognathus
pancalus,
Meristic
counts.
Prediction
model
Язык: Английский
Length–Weight Relationships of the Prized Sea Cucumber Holothuria lessoni from In Situ and Ex Situ Measurements
Journal of Marine Science and Engineering,
Год журнала:
2024,
Номер
12(12), С. 2283 - 2283
Опубликована: Дек. 12, 2024
Fisheries
science
draws
on
morphometric
data
for
stock
assessments.
Length–weight
relationships
are
essential
estimating
body
weight
from
length
measurements
taken
either
underwater
(in
situ)
or
out
of
the
water
(ex
situ).
We
examined
models
high-valued
sea
cucumber,
Holothuria
lessoni.
From
77
specimens
captured
in
2024
(mean
±
SD:
1774
372
g),
we
measured
and
width
situ
ex
situ,
then
weighed
animals
situ.
compared
using
four
biometric
parameters.
The
fitted
were
more
statistically
significant
(p
<
0.001)
when
to
measurements.
length–weight
relationship
our
study
was
with
those
two
previous
studies
same
species
at
location.
Each
generated
significantly
different
relationships.
These
findings
suggest
that
should
be
re-evaluated
regular
intervals,
as
they
may
evolve
over
time.
Our
indicates
estimation
(and
width)
must
rely
established
corresponding
whether
made
results
could
provide
reliable
certain
holothuroids.
Язык: Английский