Reducing Uneven Fruit Ripening and Improving the Quality of Durian (Durio zibethinus Murr.) Fruit Using Plastic Mulching Combined with Polyhalite Fertilizer
Agronomy,
Год журнала:
2025,
Номер
15(3), С. 631 - 631
Опубликована: Март 1, 2025
Uneven
fruit
ripening
(UFR)
is
currently
causing
a
decrease
in
the
quality
and
value
of
“Ri
6”
durian
fruit.
The
soil
moisture
nutrient
(K,
Ca,
Mg)
levels
present
during
development
stage
are
two
main
factors
affecting
UFR
However,
measurements
that
can
be
used
to
determine
rate
remain
unknown.
Therefore,
this
study
sought
evaluate
impact
plastic
mulching
(PM)
polyhalite
fertilizer
(PH)
on
improving
A
field
was
conducted
at
three
different
orchards
Vietnamese
Mekong
Delta
(VMD)
throughout
seasons
(2022–2023
2023–2024).
We
PM
month
before
harvesting,
combined
with
PH
applied
stage.
Four
treatments
were
used:
(T1)
control;
(T2)
PM,
harvesting;
(T3)
PH,
application
(3
kg
tree−1
year−1);
(T4)
+
year−1)
harvesting.
farmer’s
fertilization
practice
(450
g
N–450
P–450
K
per
period)
all
treatments.
Parameters
such
as
physicochemical
properties,
quality,
leaf
mineral
concentration
investigated
harvesting
results
show
using
decreased
(>15%)
but
increased
concentrations
K,
Mg,
Ca
both
leaves,
thereby
reducing
(>80%)
compared
control.
Additionally,
applying
aril
proportion
(>18%)
total
soluble
solids
(approximately
5%)
comparison
In
conclusion,
combining
improved
quality.
we
recommend
farmers
apply
these
methods
their
physiological
disorders
enhance
thus
contributing
achieving
sustainable
production
VMD.
Язык: Английский
Flood susceptibility assessment using deep neural networks and open-source spatial datasets in transboundary river basin
VIETNAM JOURNAL OF EARTH SCIENCES,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 16, 2025
The
Mekong
Basin
is
the
most
critical
transboundary
river
basin
in
Asia.
This
provides
an
abundant
source
of
fresh
water
essential
for
development
agriculture,
domestic
consumption,
and
industry,
as
well
production
hydroelectricity,
it
also
contributes
to
ensuring
food
security
worldwide.
region
often
subject
floods
that
cause
significant
damage
human
life,
society,
economy.
However,
flood
risk
management
challenges
this
are
increasingly
substantial
due
conflicting
objectives
between
several
countries
data
sharing.
study
integrates
deep
learning
with
optimization
algorithms,
namely
Grasshopper
Optimisation
Algorithm
(GOA),
Adam
Stochastic
Gradient
Descent
(SGD),
open-source
datasets
identify
probably
occurring
basin,
covering
Vietnam
Cambodia.
Various
statistical
indices,
Area
Under
Curve
(AUC),
root
mean
square
error
(RMSE),
absolute
(MAE),
coefficient
determination
(R²),
were
used
evaluate
susceptibility
models.
results
show
proposed
models
performed
AUC
values
above
0.8,
specifying
DNN-Adam
model
achieved
0.98,
outperforming
DNN-GOA
(AUC
=
0.89),
DNN-SGD
0.87),
XGB
0.82.
Regions
very
high
concentrated
Delta
along
River
findings
supporting
decision-makers
or
planners
proposing
appropriate
mitigation
strategies,
planning
policies,
particularly
watershed.
Язык: Английский
Modelling and predicting annual rainfall over the Vietnamese Mekong Delta (VMD) using SARIMA
Discover Geoscience,
Год журнала:
2024,
Номер
2(1)
Опубликована: Июнь 20, 2024
Abstract
Climate
and
rainfall
are
extremely
non-linear
complicated
phenomena,
which
require
numerical
modelling
to
simulate
for
accurate
prediction.
We
obtained
local
historical
data
12
meteorological
stations
in
the
Vietnamese
Mekong
Delta
(VMD)
45-year
period
1978–2022,
predict
annual
trends.
A
statistical
time
series
predicting
technique
was
used
based
on
autoregressive
integrated
moving
average
(ARIMA)
model.
utilized
seasonal
ARIMA
process
of
form
(p,1,q)(P,1,Q)
our
study
area.
The
best
(SARIMA)
models
were
then
selected
autocorrelation
function
(ACF)
partial
(PACF),
minimum
values
Akaike
Information
Criterion
(AIC)
Schwarz
Bayesian
(SBC).
model
with
external
regressors
(SARIMAX)
discovered,
a
SARIMA
various
orders
estimated
diagnosed.
To
evaluate
fitting,
we
Nash–Sutcliffe
coefficient
(Nash)
root-mean-square
error
(RMSE).
has
shown
that
(1,
1,
1)(2,
1)
11
appropriate
analyzing
forecasting
future
patterns
at
particular
station
VMD.
results
showed
is
more
reliable
provides
projections
than
other
commonly
methods,
notably
interval
forecasts.
found
interpretable
near-term
location-specific
predicts
can
be
provided
by
SARIMA-based
Язык: Английский
Hydrological dynamics of the Kalisindh and Parbati Rivers: An integrated analysis in the context of the Eastern Rajasthan Canal Project (ERCP)
Results in Engineering,
Год журнала:
2024,
Номер
21, С. 101960 - 101960
Опубликована: Март 1, 2024
This
study
conducts
a
comprehensive
analysis
of
hydrological
patterns
in
the
Kalisindh
and
Parbati
Rivers,
highlighting
Eastern
Rajasthan
Canal
Project
(ERCP)
as
pivotal
for
bolstering
regional
water
security.
Employing
an
array
data
sources,
this
research
utilizes
Polynomial
Regression
neural
network
forecasting
to
dissect
flow
patterns,
identifying
significant
virgin
peaks
mid-1980s
early
2000s
River,
notable
peak
2006–2007
River.
Analysis
reveals
that
specific
discharge
rate
River
is
diminishing
at
twice
with
annual
decreases
approximately
0.0038
cumecs/km2
Parbati,
compared
0.0019
Kalisindh.
Furthermore,
runoff
volumes
indicate
specifically
Khatoli
Gauge
&
Discharge
(G&D)
site,
experiences
significantly
higher
runoff—28,137.912
million
cubic
meters
(MCM)—in
contrast
15,795.094
MCM
Barod
G&D
site.
The
findings
accentuate
necessity
science-based
management
strategies
effectively
combat
scarcity
climate
change
impacts.
ERCP
emerges
crucial
initiative
sustainable
Rivers
Rajasthan,
underscoring
its
potential
serve
model
river
basin
management.
Язык: Английский
Effects of Environmental Changes on Flood Patterns in the Jing River Basin: A Case Study from the Loess Plateau, China
Land,
Год журнала:
2024,
Номер
13(12), С. 2053 - 2053
Опубликована: Ноя. 29, 2024
Human
activities
and
climate
change
have
significantly
influenced
the
water
cycle,
impacting
flood
risks
security.
This
study
centers
on
Jing
River
Basin
in
Chinese
Loess
Plateau,
analyzing
hydrological
patterns
progression
using
HEC-HMS
model
under
changing
conditions.
The
findings
indicate
that
substantially
affects
predictions,
increasing
peak
flows
volumes
by
up
to
10.9%
11.1%,
respectively.
It
is
essential
recognize
traditional
models
may
underestimate
posed
these
changes,
emphasizing
necessity
for
updated
methods
incorporating
climatic
human
factors.
Changes
land
use,
such
as
expansion
of
grasslands
forests,
reduced
discharges
volumes.
Consequently,
combined
impacts
use
changes
intensified
frequencies,
necessitating
strategies
manage
effectively.
dynamics
flooding
are
impacted
particularly
minor
floods
occur
frequently,
highlighting
influence
trends.
Within
Basin,
been
shaped
both
variations
activities,
leading
an
increase
extreme
events
concerns
regarding
Using
model,
this
examines
hydrology
focusing
design
storm
various
characteristics
different
scenarios.
Climate
has
resulted
higher
volume
surges
ranging
from
6.3%
10.9%,
while
shifts
decreases
farmland
grasslands,
caused
declines
7.2%
4.7%
effects
variation
utilization
complex
implications
patterns,
with
milder
moderate
showing
a
more
significant
impact
shorter
return
periods
facing
increased
consequences.
These
underscore
interconnected
nature
change,
need
comprehensive
address
challenges
ensure
sustainable
management
region.
Язык: Английский
Multi-scale characteristics of drought propagation from meteorological to hydrological phases: variability and impact in the Upper Mekong Delta, Vietnam
Natural Hazards,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 14, 2024
Язык: Английский
Is Vietnam’s Mekong Delta Facing Wet Season Droughts?
Earth Systems and Environment,
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 3, 2024
Язык: Английский
Climate risks and resilience in urbanizing areas of the Vietnamese Mekong Delta: future action-orientated research needs
Elsevier eBooks,
Год журнала:
2024,
Номер
unknown, С. 131 - 156
Опубликована: Ноя. 15, 2024
Язык: Английский
Monsoonal Extreme Rainfall in Southeast Asia: A Review
Water,
Год журнала:
2024,
Номер
17(1), С. 5 - 5
Опубликована: Дек. 24, 2024
In
recent
years,
extreme
rainfall
and
related
disasters,
including
floods
landslides,
have
led
to
significant
property
damage
loss
of
life
globally.
Southeast
Asia
(SEA)
is
particularly
impacted
by
these
rainfall-driven
events.
This
study
reviews
research
development
approaches
understand
the
current
status
monsoonal
in
SEA,
with
importance
impacts
natural
anthropogenic
factors.
Natural
factors,
individual
combined
effects
various
climatic
phenomena,
such
as
Madden–Julian
Oscillation
(MJO),
El
Niño–Southern
(ENSO)
cold
surges
(CSs),
on
patterns.
Anthropogenic
emissions
changes
land
use,
also
play
a
crucial
role
producing
extremes.
review
identifies
key
challenges,
uncertainty
both
available
datasets
climate
models,
emphasising
needs
for
model
improvement
better
adaptation
complex
regional
geographical
environments.
The
findings
enhance
understanding
response
strategies
events
mitigate
associated
negative
impacts.
Язык: Английский