IntechOpen eBooks,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 26, 2024
This
chapter
investigates
climate
change’s
impact
on
broiler
chicken
production
and
reproduction.
With
patterns
shifting,
poultry
farming
faces
challenges
in
managing
heat
stress,
ensuring
reproductive
success,
maintaining
overall
yield.
The
physiological
responses
of
chickens
to
changing
environmental
conditions,
including
temperature
fluctuations
extreme
events,
will
be
explored.
Additionally,
adaptation
strategies
management
practices
mitigate
these
impacts
discussed.
By
synthesizing
existing
literature
empirical
evidence,
this
aims
provide
insights
into
understanding
addressing
the
complexities
change
industry,
offering
pathways
for
sustainable
a
climate.
Abstract
In
recent
years,
the
integration
of
artificial
intelligence
(AI)
has
markedly
bolstered
productivity,
especially
in
agriculture,
mitigating
environmental
impacts
like
greenhouse
gas
emissions.
This
shift
employs
a
range
tech,
IT,
sensors,
robotics,
and
AI,
boosting
output
while
curbing
negative
effects.
Challenges
persist,
notably
food
scarcity
climate
threats
for
growing
global
population.
By
2050,
two
billion
more
people
will
need
sustenance,
necessitating
urgent
agricultural
innovation.
article
reviewed
databases
from
1985
to
2023
(Google
Scholar,
Scopus,
ISI
Web
Knowledge),
analyzing
AI’s
role
agriculture.
Keywords
precision
feeding,
welfare,
animal
husbandry,
management
were
used
systematic
literature
review.
Findings
highlight
pivotal
addressing
shortages.
Investment
emerging
is
crucial
sustainable
supply.
E3S Web of Conferences,
Год журнала:
2024,
Номер
491, С. 02015 - 02015
Опубликована: Янв. 1, 2024
This
review
article
explores
the
transformative
impact
of
AI
and
IoT
in
livestock
management,
highlighting
their
pivotal
role
advancing
Agriculture
4.0.
It
delves
into
various
technologies
such
as
robotics,
nanotechnology,
gene
editing,
which
are
reshaping
farming
food
systems
towards
sustainability.
The
paper
emphasizes
significance
digital
phenotyping
poultry,
particularly
enhancing
productivity,
animal
welfare,
sustainability
through
innovative
genomics
research
health
monitoring
platforms.
Additionally,
it
examines
evolution
e-agriculture
India,
focusing
on
government
initiatives
increasing
influence
mobile
technology
farming.
Big
Data
Smart
Farming
is
also
scrutinized,
revealing
its
extensive
beyond
primary
production
potential
supply
chain
dynamics
business
models.
further
assesses
contributions
agricultural
systems,
meeting
challenges
a
rapidly
growing
global
population.
Through
this
comprehensive
analysis,
underscores
necessity
for
ongoing
development
these
areas,
recognizing
opportunities
presented
by
robust,
sustainable,
creating
more
technologically
advanced
future.
Genetics Selection Evolution,
Год журнала:
2024,
Номер
56(1)
Опубликована: Апрель 16, 2024
Abstract
Background
With
the
introduction
of
digital
phenotyping
and
high-throughput
data,
traits
that
were
previously
difficult
or
impossible
to
measure
directly
have
become
easily
accessible,
offering
opportunity
enhance
efficiency
rate
genetic
gain
in
animal
production.
It
is
interest
assess
how
behavioral
are
indirectly
related
production
during
performance
testing
period.
The
aim
this
study
was
quality
behavior
data
extracted
from
day-wise
video
recordings
estimate
parameters
their
phenotypic
correlations
with
pigs.
Behavior
recorded
for
70
days
after
on-test
at
about
10
weeks
age
ended
off-test
2008
female
purebred
pigs,
totaling
119,812
records.
included
time
spent
eating,
drinking,
laterally
lying,
sternally
sitting,
standing,
meters
distance
traveled.
A
control
procedure
created
algorithm
training
adjustment,
standardizing
recording
hours,
removing
culled
animals,
filtering
unrealistic
Results
Production
average
daily
(ADG),
back
fat
thickness
(BF),
loin
depth
(LD).
Single-trait
linear
models
used
heritabilities
two-trait
between
traits.
results
indicated
all
heritable,
heritability
estimates
ranging
0.19
0.57,
showed
low-to-moderate
Two-trait
also
compare
different
intervals
To
analyze
redundancies
period,
averages
various
compared.
Overall,
55-
68-day
interval
had
strongest
correlation
Conclusions
Digital
a
new
low-cost
method
record
phenotypes,
but
thorough
cleaning
procedures
needed.
Evaluating
offers
deeper
insight
into
changes
throughout
growth
periods
relationship
traits,
which
may
be
less
frequent
basis.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Дек. 26, 2023
Abstract
This
study
leverages
Convolutional
Neural
Networks
(CNN)
and
Mel
Frequency
Cepstral
Coefficients
(MFCC)
to
analyze
the
vocalization
patterns
of
laying
hens,
focusing
on
their
responses
both
visual
(umbrella
opening)
auditory
(dog
barking)
stressors
at
different
ages.
The
aim
is
understand
how
these
diverse
stressors,
along
with
hens’
age
timing
stress
application,
affect
vocal
behavior.
Utilizing
a
comprehensive
dataset
chicken
recordings,
from
stress-exposed
control
groups,
research
enables
detailed
comparative
analysis
varied
environmental
stimuli.
A
significant
outcome
this
distinct
exhibited
by
younger
chickens
compared
older
ones,
suggesting
developmental
variations
in
response.
finding
contributes
deeper
understanding
poultry
welfare,
demon-strating
potential
non-invasive
for
early
detection
aligning
ethical
live-stock
management
practices.
CNN
model’s
ability
distinguish
between
pre-
post-stress
vocalizations
highlights
substantial
impact
stressor
application
not
only
sheds
light
nuanced
interactions
stimuli
animal
behavior
but
also
marks
advancement
smart
farming.
It
paves
way
real-time
welfare
assessments
more
informed
decision-making
management.
Looking
forward,
suggests
avenues
longitudinal
chronic
methodologies
across
species
farming
contexts.
Ultimately,
represents
pivotal
step
integrating
technology
offering
promising
approach
transforming
husbandry.
