Notulae Botanicae Horti Agrobotanici Cluj-Napoca,
Год журнала:
2024,
Номер
52(2), С. 13728 - 13728
Опубликована: Май 21, 2024
Nitrogen
fertilizer
levels
significantly
affect
crop
growth
and
development,
necessitating
precision
management.
Most
studies
focus
on
nitrogen
nutrient
estimation
using
vegetation
indices
textural
features,
overlooking
the
diagnostic
potential
of
color
features.
Hence,
we
investigated
cotton
nutrition
status
unmanned
aerial
vehicle
(UAV)
image
features
index
(NNI).
Random
frog
algorithm
-
random
forest-screened
feature
sets
correlated
with
NNI,
which
were
substituted
into
four
machine
learning
algorithms
for
NNI
modeling.
The
composite
scores
(F)
optimal
calculated
coefficient
variation
method
comprehensive
diagnosis.
Validation
model
determining
critical
concentration
in
yielded
a
determination
R2
=
0.89,
root
mean
square
error
RMSE
0.50
g
(100
g)-1,
absolute
MAE
0.44,
demonstrating
improved
performance.
Additionally,
our
novel
constructed
based
exhibited
R2c
0.97,
RMSEc
0.02,
MAEc
R2v
0.85,
RMSEv
0.05,
MAEv
0.04.
Polynomial
fitting
indicated
that
was
reliable
following
criterion:
0.48
<
F2
0.67
overapplication,
whereas
or
>
deficiency.
This
study
demonstrates
superior
effectiveness
UAV
RGB
quick,
accurate
diagnosis
levels,
will
help
guide
application.
Sustainability,
Год журнала:
2024,
Номер
16(3), С. 982 - 982
Опубликована: Янв. 23, 2024
Improving
tourism’s
ecological
efficiency
and
facilitating
harmony
between
tourism
development
the
environment
are
profitable
conducive
to
sustainable
development.
In
this
study,
we
investigated
relationship
eco-efficiency
for
environmental
protection
by
incorporating
unexpected
outputs
calculate
eco-efficiencies,
analyzing
three-dimensional
spatial
variation
and,
finally,
considering
effects
of
nine
comprehensive
factors
on
extent
in
efficiencies:
economic
development,
openness,
social
consumption,
digital
economy,
transportation
infrastructure,
government
intervention,
technological
innovation,
energy
passenger
turnover.
First,
an
slack-based
measure
model
was
applied
efficiencies
21
cities
Guangdong
Province
from
2009
2021.
Second,
natural
breakpoint
method
trend
surface
analysis
were
used
identify
spatiotemporal
differences
trends
these
efficiencies.
Finally,
geographical
detector
utilized
analyze
elements
affecting
temporal
Overall,
at
a
high
level,
showing
obvious
changes.
Compared
with
2021,
overall
shifted
north,
low
south,
west,
east
east.
The
distribution
north–south
east–west
directions
is
“U”
shape,
relatively
significant.
We
suggest
roles
such
as
level
technical
driving
force
transportation,
standard
consumption.
This
study
provides
constructive
approach
elevating
regards
factors.
Sustainability,
Год журнала:
2024,
Номер
16(8), С. 3491 - 3491
Опубликована: Апрель 22, 2024
In
the
Xinjiang
region,
sustainable
management
of
water
resources,
energy,
and
food
is
crucial
for
regional
development.
This
study
establishes
a
coupling
evaluation
index
energy–food–water
(EFW)
systems
from
perspectives
supply,
consumption,
efficiency.
Using
an
integrated
EFM-CDD-RDD-CCDM
approach,
assessment
coordination
levels
EFW
in
14
cities
within
was
conducted
period
2004
to
2020.
Additionally,
method
obstacle
degree
identification
utilized
determine
main
barriers
affecting
systems.
Key
findings
included
following.
(1)
terms
individual
system
indices,
resource
exhibited
overall
higher
(ranging
0.30
0.72)
with
comparatively
minor
spatial
variability,
while
energy
(from
0.18
0.81)
0.12
0.83)
showed
greater
temporal
fluctuations.
From
2020,
improvements
were
observed
systems,
whereas
decline
noted
subsystem.
(2)
Prior
2011,
food–water
energy–food
upward
trend,
energy–water
decreased
annually
by
2.62%,
further
highlighting
tensions
between
development
constraints
Xinjiang.
(3)
The
comprehensive
ranged
0.59
0.80;
there
oscillatory
increase.
2016,
across
municipalities
generally
improved,
regions
on
western
side
southern
slope
Tianshan
Mountains,
Altai
northwestern
edge
Junggar
Basin
exhibiting
highest
levels,
followed
three
prefectures
(4)
posed
its
divisions
decreasing
trend
identified
as
factor
degrees
(increasing
44%
52%).
Therefore,
it
imperative
accelerate
transition
optimization
lead
production
areas
research
provides
scientific
basis
Xinjiang’s
strategies
highlights
potential
directions
future
management.
Notulae Botanicae Horti Agrobotanici Cluj-Napoca,
Год журнала:
2024,
Номер
52(2), С. 13728 - 13728
Опубликована: Май 21, 2024
Nitrogen
fertilizer
levels
significantly
affect
crop
growth
and
development,
necessitating
precision
management.
Most
studies
focus
on
nitrogen
nutrient
estimation
using
vegetation
indices
textural
features,
overlooking
the
diagnostic
potential
of
color
features.
Hence,
we
investigated
cotton
nutrition
status
unmanned
aerial
vehicle
(UAV)
image
features
index
(NNI).
Random
frog
algorithm
-
random
forest-screened
feature
sets
correlated
with
NNI,
which
were
substituted
into
four
machine
learning
algorithms
for
NNI
modeling.
The
composite
scores
(F)
optimal
calculated
coefficient
variation
method
comprehensive
diagnosis.
Validation
model
determining
critical
concentration
in
yielded
a
determination
R2
=
0.89,
root
mean
square
error
RMSE
0.50
g
(100
g)-1,
absolute
MAE
0.44,
demonstrating
improved
performance.
Additionally,
our
novel
constructed
based
exhibited
R2c
0.97,
RMSEc
0.02,
MAEc
R2v
0.85,
RMSEv
0.05,
MAEv
0.04.
Polynomial
fitting
indicated
that
was
reliable
following
criterion:
0.48
<
F2
0.67
overapplication,
whereas
or
>
deficiency.
This
study
demonstrates
superior
effectiveness
UAV
RGB
quick,
accurate
diagnosis
levels,
will
help
guide
application.
