Sustainability of Maize–Soybean Rotation for Future Climate Change Scenarios in Northeast China
Journal of Agronomy and Crop Science,
Год журнала:
2025,
Номер
211(2)
Опубликована: Март 1, 2025
ABSTRACT
Climate
change
poses
a
global
challenge
to
agricultural
production
and
food
security,
especially
in
developing
countries.
In
Northeast
China,
major
grain‐producing
region,
the
Maize–Soybean
rotation
is
crucial
for
sustainable
development.
However,
previous
studies
have
mainly
focused
on
single
crops
lacked
attention
soil
health
regional
scale
analysis.
This
study
utilises
APSIM
model
predict
crop
yields
organic
carbon
(SOC)
under
two
Representative
Concentration
Pathways
4.5
8.5
(RCP4.5
RCP8.5)
future
climate
scenarios
different
latitude
regions
of
China.
The
result
shows
that
has
significant
spatial
temporal
variations
yield
storage
system.
Compared
baseline
(1980–2010),
maize
from
−11.6
42.8
kg
10a
−1
(RCP4.5)
7.1
39.8
(RCP8.5),
soybean
vary
−13.1
3.9
−16.2
−5.6
(RCP8.5).
SOC
increases
slowly
0
20
cm
decreases
40
cm,
resulting
decrease
21–334
ha
26–280
(RCP8.5)
predicted
storage.
PLS‐PM
results
show
precipitation
negative
impact
accumulation,
temperature
rise
RCP8.5
scenario
positively
correlated
with
yields,
correlation
stronger
RCP8.5,
which
higher
explanation
changes.
significantly
affects
stocks
system
Northeastern
during
extreme
weather.
Therefore,
adaptation
strategies
should
fit
local
needs,
early‐maturing
opt
drought‐resistant,
early
varieties
employ
conservation
tillage
water‐saving
methods,
while
medium
late‐maturing
areas
select
late
varieties,
adjust
sowing
enhance
fertiliser
efficiency.
Язык: Английский
Enhancing Precision Farming Innovations for Global Food Security Through Agricultural Extension Services
Advances in environmental engineering and green technologies book series,
Год журнала:
2025,
Номер
unknown, С. 119 - 142
Опубликована: Апрель 4, 2025
Precision
farming
depends
on
agricultural
extension
because
it
provides
farmers
with
the
knowledge,
skills,
and
support
they
need
to
adopt
successfully
use
precision
agriculture
technologies.
By
offering
guidance
practical
aspects
of
agriculture,
services
assist
in
overcoming
technical
challenges
optimizing
their
technology.
Additionally,
facilitate
farmers'
access
technologies,
such
as
software,
tools,
which
could
otherwise
be
unaffordable
individual
farmers.
Agricultural
can
help
overcome
barriers
adopting
boost
productivity
efficiency,
sustainable
development
by
carrying
out
these
duties.
technology
is
essential
for
assuring
effective
ethical
food
production
this
era
global
security.
As
develops,
its
incorporation
into
methods
holds
potential
transform
sector
satisfying
expanding
needs
a
dynamic
community..
Язык: Английский
Role of Crop Water Requirement and Irrigation Scheduling in Sustainable Agriculture
Advances in environmental engineering and green technologies book series,
Год журнала:
2025,
Номер
unknown, С. 235 - 256
Опубликована: Апрель 4, 2025
Optimal
water
supply
is
vital
for
farming,
ensuring
efficient
crop
production
and
conservation.
Water
management
seeks
to
maximize
resource
use
while
minimizing
negative
effects
on
availability.
Understanding
crop-specific
requirements
influenced
by
factors
like
climate,
soil
type,
plant
growth
stage
crucial.
Accurate
estimation
of
these
needs
necessary
effective
irrigation
planning
reduce
waste.
Techniques
such
as
weight-based
methods,
tensiometers,
weather-based
approaches
Hargreaves
Pan
Evaporation
help
in
estimating
needs.
Irrigation
scheduling,
ranging
from
simple
fixed
schedules
complex
strategies
that
account
moisture
condition,
key
optimizing
use.
Unchecked
can
cause
waterlogging
salinity,
requiring
conservation,
management,
recycling.
A
comprehensive
approach
combining
knowledge,
technology,
collaboration
needed
sustainable
agriculture.
Язык: Английский
Machine Learning for Precision Agriculture and Crop Yield Optimization
Advances in computational intelligence and robotics book series,
Год журнала:
2025,
Номер
unknown, С. 189 - 234
Опубликована: Март 28, 2025
The
swift
advancement
of
machine
learning
(ML)
has
altered
several
industries,
including
agriculture,
by
providing
innovative
ways
addressing
complex
challenges
related
to
modern
farming.
This
chapter
discusses
the
use
ML
in
precision
emphasizing
its
capacity
maximize
crop
output
and
improve
agricultural
practices.
It
studies
supervised,
unsupervised,
reinforcement,
deep
methodologies
evaluate
extensive
datasets
derived
from
remote
sensing
technologies,
soil
sensors,
climate
data,
equipment.
Principal
applications
include
predictive
modeling
for
yield
estimation,
pest
disease
identification,
health
assessment,
irrigation
optimization,
fertilization.
also
examines
problems
limits
implementation
data
quality
farmer
acceptance.
Язык: Английский
Evaluating coastal agroecological dynamics using Landsat-derived vegetation and environmental indices embedded in Decision Support System and Monitoring Tools: insights from Guyana towards achieving SDGs
Discover Sustainability,
Год журнала:
2025,
Номер
6(1)
Опубликована: Май 8, 2025
Язык: Английский
Abiotic Stress and Climate Change
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 1 - 16
Опубликована: Май 9, 2025
Climate
change
is
intensifying
abiotic
stresses
such
as
drought,
salinity,
extreme
temperatures,
and
pollution,
posing
significant
threats
to
agricultural
productivity
ecosystem
stability.
In
response
these
challenges,
technological
innovation
plays
a
crucial
role
in
developing
effective
adaptation
strategies.
This
contribution
first
examines
the
effects
of
stress
on
ecosystems
production,
highlighting
biochemical
physiological
impacts.
It
then
explores
emerging
solutions,
including
artificial
intelligence,
precision
agriculture,
biotechnology,
machine
learning-assisted
crop
selection.
The
analysis
also
considers
integration
predictive
models
IoT
technologies
for
sustainable
management
natural
resources.
Finally,
critical
reflection
ethical
limitations
proposed
solutions.
Recommendations
will
be
made
promote
environmental
policies
aligned
with
Sustainable
Development
Goals
(SDGs)
ESG
standards,
ensuring
an
inclusive
ecological
transition.
Язык: Английский