The Past, Present and Future of Plant Activator Targeting Salicylic Acid Signal Pathway
Misbah Naz,
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Dongqin Zhang,
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Kangcen Liao
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et al.
Published: July 17, 2024
Plant
activators
have
emerged
as
promising
alternatives
to
conventional
pesticides
for
crop
disease
manage-ment
due
their
unique
mode
of
action.
By
priming
the
plant's
innate
immune
system,
these
compounds
can
induce
systemic
acquired
resistance
against
a
broad
spectrum
pathogens
without
directly
inhibiting
proliferation.
Key
advantages
plant
include
prolonged
defense
activity,
lower
effective
dosages,
and
negligible
risk
developing
pathogen
resistance.
Among
various
defensive
pathways
tar-geted,
salicylic
acid
(SA)
signaling
cascade
has
been
extensively
explored,
leading
successful
devel-opment
commercial
like
benzothiadiazole
widespread
application
in
protection.
While
action
sites
many
SA-targeting
preliminarily
mapped
different
steps
along
pathway,
comprehensive
understanding
precise
mechanisms
remains
elusive.
This
review
provides
historical
perspective
on
activator
development
outlines
diverse
screening
strategies
employed
across
multiple
levels,
from
whole-plant
bioassays
molecular
transgenic
approaches.
We
expound
intricate
components,
biological
relevance,
regulatory
circuits
governing
SA
while
criti-cally
examining
structural
features,
bioactivities,
proposed
modes
classical
such
derivatives,
analogs,
other
small
molecules.
Insights
field
trials
as-sessing
practical
applicability
are
also
discussed.
Furthermore,
we
highlight
current
status,
challenges,
future
prospects
realm
globally,
with
focus
recent
en-deavors
China.
Collectively,
this
aims
synthesize
existing
knowledge
provide
roadmap
research
toward
more
potent
mechanistically
understood
activa-tors
that
fortify
immunity
disease.
Language: Английский
Hidden Biocontrol Agents: The World of Insect-Pathogenic Fungi
Kamel A. Abd–Elsalam,
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Rawan K. Hassan,
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Toka E. Abdelkhalek
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et al.
Published: Jan. 1, 2025
Language: Английский
Algorithms for Plant Monitoring Applications: A Comprehensive Review
Algorithms,
Journal Year:
2025,
Volume and Issue:
18(2), P. 84 - 84
Published: Feb. 5, 2025
Many
sciences
exploit
algorithms
in
a
large
variety
of
applications.
In
agronomy,
amounts
agricultural
data
are
handled
by
adopting
procedures
for
optimization,
clustering,
or
automatic
learning.
this
particular
field,
the
number
scientific
papers
has
significantly
increased
recent
years,
triggered
scientists
using
artificial
intelligence,
comprising
deep
learning
and
machine
methods
bots,
to
process
crop,
plant,
leaf
images.
Moreover,
many
other
examples
can
be
found,
with
different
applied
plant
diseases
phenology.
This
paper
reviews
publications
which
have
appeared
past
three
analyzing
used
classifying
agronomic
aims
crops
applied.
Starting
from
broad
selection
6060
papers,
we
subsequently
refined
search,
reducing
358
research
articles
30
comprehensive
reviews.
By
summarizing
advantages
applying
analyses,
propose
guide
farming
practitioners,
agronomists,
researchers,
policymakers
regarding
best
practices,
challenges,
visions
counteract
effects
climate
change,
promoting
transition
towards
more
sustainable,
productive,
cost-effective
encouraging
introduction
smart
technologies.
Language: Английский
Metal pollution-induced alterations in soil fungal community structure and functional adaptations across regional scales
Journal of Hazardous Materials,
Journal Year:
2025,
Volume and Issue:
494, P. 138553 - 138553
Published: May 9, 2025
Language: Английский
Rational design and discovery of novel hydrazide derivatives as potent succinate dehydrogenase inhibitors inspired by natural d/l‐camphor
Peng Dai,
No information about this author
Zihua Ma,
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Guangfu Yi
No information about this author
et al.
Pest Management Science,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Oct. 18, 2024
Abstract
BACKGROUND
Succinate
dehydrogenase
inhibitors
(SDHIs)
have
rapidly
become
one
of
the
fastest‐growing
categories
fungicides
used
against
plant
pathogenic
fungi.
Recent
research
advancements
emphasized
that
structural
modifications
SDHIs
using
naturally
sourced
scaffolds
represent
an
innovative
strategy
for
developing
new,
highly
effective,
broad‐spectrum
fungicides.
A
novel
series
d/l
‐camphorhydrazide
derivatives
potentially
targeting
fungal
succinate
(SDH)
were
designed,
synthesized
and
evaluated
their
antifungal
effects
Rhizoctonia
solani
,
Fusarium
graminearum
Valsa
mali
Botrytis
cinerea
.
RESULTS
Amongst
them,
compounds
A1‐7
(
d
‐camphor)
A2‐7
l
displayed
excellent
in
vitro
activity
R.
with
median
effective
concentration
(EC
50
)
values
0.38
0.48
μg
mL
−1
which
obviously
superior
to
boscalid
(0.87
).
A2‐5
‐camphor,
EC
=
3.27
exhibited
good
V.
(2.13
−
1),
A2‐21
(5.2
A1‐5
(5.15
showed
F.
below
(5.85
Preliminary
mechanistic
studies,
scanning
transmission
electron
microscopy,
indicated
compound
induced
disordered
entanglement
hyphae,
shrinkage
hyphal
surfaces,
vacuole
swelling
rupture,
disrupted
normal
growth.
Additionally,
production
accumulation
reactive
oxygen
species,
mitochondrial
membrane
potential,
effectively
inhibited
germination
formation
sclerotia
Moreover,
molecular
docking
results
SDH
enzyme
assays
yielded
promising
outcomes.
CONCLUSION
In
this
study,
designed
optimized
emerged
as
candidates
SDH‐targeting
fungicides,
demonstrating
strong
activity.
These
hold
potential
new
agents
further
research.
©
2024
Society
Chemical
Industry.
Language: Английский
Fungal spore seasons advanced across the US over two decades of climate change
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Oct. 24, 2024
Abstract
Phenological
shifts
due
to
climate
change
have
been
extensively
studied
in
plants
and
animals.
Yet,
the
responses
of
fungal
spores—crucial
organisms
that
play
important
roles
ecosystems
act
as
airborne
allergens—remain
understudied.
This
knowledge
gap
global
biology
hinders
our
understanding
its
ecological
public
health
implications.
To
bridge
this
gap,
we
acquired
a
long-term
(2003
∼
2022),
large-scale
(the
continental
US)
dataset
spores
collected
by
US
National
Allergy
Bureau.
We
first
pre-processed
spore
data
gap-filling
smoothing.
Afterward,
extracted
ten
metrics
describing
phenology
(e.g.,
start
end
season)
intensity
peak
concentration
integral)
seasons.
These
were
derived
using
two
complementary
but
not
mutually
exclusive
approaches—ecological
approaches,
defined
percentiles
total
allergenic
thresholds
concentration,
respectively.
Using
linear
mixed
effects
models,
quantified
annual
temporal
these
across
US.
revealed
significant
advancement
onset
seasons
both
(11
days,
95%
confidence
interval:
0.4
23
days)
(22
6
38
approaches
over
decades.
Nevertheless,
an
cycle
allergy
season
tended
decrease
time.
The
earlier
was
significantly
correlated
with
climatic
variables,
such
warmer
temperatures
altered
precipitations.
Overall,
findings
suggest
possible
climate-driven
advanced
seasons,
highlighting
importance
mitigation
adaptation
decision-making.
Language: Английский