Approaches for the amelioration of adverse effects of drought stress on soybean plants: from physiological responses to agronomical, molecular, and cutting-edge technologies
Plant and Soil,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 14, 2025
Язык: Английский
Molecular mechanisms underlying plant responses to low phosphate stress and potential applications in crop improvement
New Crops,
Год журнала:
2025,
Номер
unknown, С. 100064 - 100064
Опубликована: Янв. 1, 2025
Язык: Английский
Machine learning-assisted evaluation of antioxidant and metal chelating capacities in in vitro propagated Ceratophyllum demersum L. under different LED light conditions
Plant Cell Tissue and Organ Culture (PCTOC),
Год журнала:
2025,
Номер
161(2)
Опубликована: Апрель 29, 2025
Язык: Английский
Carbon Nanotubes as Carriers in Plant Science
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 63 - 88
Опубликована: Май 9, 2025
Carbon
nanotubes
have
emerged
as
promising
nanomaterials
in
plant
sciences,
offering
innovative
solutions
for
enhancing
sustainable
agricultural
production.
This
chapter
provides
a
comprehensive
analysis
of
the
structural
variations
CNTs,
including
single-walled,
stacked-cup,
and
multi-walled
nanotubes,
their
applications
gene
delivery,
biosensing,
development
nano-pesticides
nano-insecticides.
CNTs
facilitate
improved
nutrient
uptake,
promote
growth,
enhance
stress
tolerance
through
unique
physicochemical
properties.
Additionally,
interactions
with
plant-associated
microbes
soil
microbial
communities,
health
fertility
are
discussed.
However,
challenges
related
to
CNT
toxicity,
environmental
persistence,
effects
on
physiology
necessitate
further
research.
The
also
explores
integration
machine
learning,
artificial
intelligence,
multi
omics
approaches
optimizing
breeding,
precision
agriculture,
crop
improvement.
Язык: Английский
Maturity Prediction in Soybean Breeding Using Aerial Images and the Random Forest Machine Learning Algorithm
Remote Sensing,
Год журнала:
2024,
Номер
16(23), С. 4343 - 4343
Опубликована: Ноя. 21, 2024
Several
studies
have
used
aerial
images
to
predict
physiological
maturity
(R8
stage)
in
soybeans
(Glycine
max
(L.)
Merr.).
However,
information
for
making
predictions
the
current
growing
season
using
models
fitted
previous
years
is
still
necessary.
Using
Random
Forest
machine
learning
algorithm
and
time
series
of
RGB
(red,
green,
blue)
multispectral
taken
from
a
drone,
this
work
aimed
study,
three
breeding
experiments
plant
rows,
how
are
impacted
by
number
factors.
These
include
type
camera
used,
between
flights,
whether
with
data
obtained
one
or
more
environments
can
be
make
accurate
an
independent
environment.
Applying
principal
component
analysis
(PCA),
it
was
found
that
compared
full
set
8–10
flights
(R2
=
0.91–0.94;
RMSE
1.8–1.3
days),
five
fights
before
harvest
had
almost
no
effect
on
prediction
error
(RMSE
increase
~0.1
days).
Similar
accuracy
achieved
either
affordable
camera,
excess
green
index
(ExG)
important
feature
predictions.
model
trained
two
fielding
notes
check
cultivars
planted
test
season,
R8
stage
predicted,
2020,
2.1
days.
Periodically
adjusted
could
help
soybean
programs
save
when
characterizing
cycle
length
thousands
rows
each
season.
Язык: Английский
Challenges and Solutions in Multi-Class Bone Marrow Classification Using EfficientNetB5
Опубликована: Окт. 25, 2024
Язык: Английский
Addressing Bone Marrow Classification Hurdles Using EfficientNetB5 Technique
Опубликована: Окт. 25, 2024
Язык: Английский
Emerging Biomarkers in Early Disease Detection: A Narrative Review
International Journal of Clinicopathological Correlation,
Год журнала:
2024,
Номер
8(2)
Опубликована: Дек. 27, 2024
The
early
diagnosis
of
diseases
is
a
fundamental
aspect
contemporary
medicine,
crucial
for
enhancing
patient
prognosis
and
alleviating
healthcare
system
burdens.
Biomarkers—measurable
indicators
biological
processes
or
disease
states—have
emerged
as
pivotal
tools
in
diagnostics.
This
review
focuses
on
novel
biomarkers
detection
cancer,
cardiovascular
diseases,
inflammatory
conditions,
with
special
emphasis
liquid
biopsies,
circulating
tumor
DNA
(ctDNA),
cardiac
troponins,
cytokines,
exosome-based
markers.
Furthermore,
advancements
omics
technologies
artificial
intelligence
are
highlighted
transformative
this
field.
Despite
their
potential,
challenges
such
validation,
standardization,
practical
integration
into
clinical
workflows
persist.
Addressing
these
through
collaborative
research
will
ensure
play
central
role
diagnostics,
ultimately
advancing
global
outcomes.
Язык: Английский