Research on the impact of climate change on green and low-carbon development in agriculture
Ecological Indicators,
Год журнала:
2025,
Номер
170, С. 113090 - 113090
Опубликована: Янв. 1, 2025
Язык: Английский
Data from a survey of coffee cultivation in lowland and highland areas to support agriculture during climate change.
Data in Brief,
Год журнала:
2024,
Номер
56, С. 110881 - 110881
Опубликована: Авг. 25, 2024
This
survey
aimed
to
acquire
and
generate
significant
information
on
coffee
cultivation
in
high
low
elevations
support
agriculture
during
climate
change.
dataset
helps
understand
highland
lowland
areas
with
diverse
climates
environmental
conditions
for
researchers
use
this
data
improve
production
techniques.
In
the
business
scope,
provides
a
critical
vision
value
proposition
of
maintain
conservation
wealth
creation
chain.
Similarly,
chains
can
as
an
example
assess
sustainability
carbon
literacy.
The
structured
interviews
field
trips
were
conducted
at
plantations
southern
northern
Thailand.
transcript
results
manually
coded
thematic
analysis.
offers
insights
into
anthropogenic
plant
migration
distribution
academics
valuable
resource
good
reference
agricultural
biodiversity
research.
Today,
faces
many
challenges,
such
change,
water
shortage,
improper
land
management.
altitudes
may
help
others
grow
crops
ever-changing
climates.
Язык: Английский
Impact of Digital Agro-Technology Services on Technical Efficiency and Income of Small-Scale Farmers: Empirical Study from Mango Production in China
Agriculture,
Год журнала:
2024,
Номер
14(12), С. 2143 - 2143
Опубликована: Ноя. 26, 2024
With
the
market-driven
approach
to
agricultural
technical
services
and
application
of
digital
technology,
agro-technical
have
gradually
emerged
as
a
novel
service
model.
However,
there
is
lack
empirical
research
on
effectiveness
this
in
academic
literature.
To
address
gap,
study
measured
impact
efficiency
income
levels
mango
farmers,
using
data
collected
from
131
farmers
Hainan
Province,
China,
2022
2024.
This
employed
endogenous
switching
regression
model
(ESRM)
inverse
probability-weighted
adjustment
(IPWRA)
analyze
data,
addressing
endogeneity
through
instrumental
variable
method
by
replacing
core
explanatory
variables
conducting
sub-regional
for
robustness
testing.
The
main
conclusions
are
follows:
Under
counterfactual
assumption
ESRM,
who
adopt
would
experienced
decrease
0.025
(a
decline
3.6%)
if
they
had
not
adopted
service.
Conversely,
did
it
seen
an
increase
0.047
(an
7.3%)
chosen
do
so.
Additionally,
under
post-treatment
effect
estimation
IPWRA,
compared
receive
service,
those
so
saw
15.6%.
analysis
results
methods
such
K-nearest
neighbors
matching
also
confirm
conclusion.
Therefore,
evident
that
agro-technology
play
significant
role
improving
small-scale
farmers.
Язык: Английский