Abstract
Background
The
cotton
whitefly
(
Bemisia
tabaci
)
is
a
major
global
pest,
causing
significant
crop
damage
through
viral
infestation
and
feeding.
Traditional
B.
recognition
relies
on
human
eyes,
which
requires
large
amount
of
work
high
labor
costs.
pests
overlapping
generations,
reproductive
capacity,
small
size,
migratory
behavior
present
challenges
for
the
real-time
monitoring
early
warning
systems.
This
study
aims
to
develop
an
efficient,
high-throughput
automated
system
detection
whiteflies.
In
this
work,
novel
tool
fast
identification
quantification
was
developed
based
deep
learning-based
model.
approach
enhances
effectiveness
control
by
facilitating
earlier
its
establishment
in
cotton,
thereby
allowing
quicker
implementation
management
strategies.
Results
We
compiled
dataset
1200
annotated
images
whiteflies
leaves,
augmented
using
techniques
like
flipping
rotation.
modified
YOLO
v8s
model
replacing
C2f
module
with
Swin-Transformer
introducing
P2
structure
Head,
achieving
precision
0.87,
mAP
50
0.92,
F1
score
0.88
ablation
studies.
Additionally,
we
employed
SAHI
image
preprocessing
integrated
algorithm
Raspberry
Pi,
GUI-based
visual
interface.
Our
preliminary
analysis
revealed
higher
density
leaves
afternoon
middle-top,
middle,
middle-down
plant
sections.
Conclusion
Utilizing
enhanced
learning
model,
have
achieved
precise
counting
whiteflies,
enabling
application
hardware
devices
Pi.
highly
suitable
research
requiring
accurate
including
phenotypic
analyses.
Future
will
focus
deploying
such
equipment
fields
manage
infestations.
Frontiers in Plant Science,
Год журнала:
2025,
Номер
15
Опубликована: Фев. 21, 2025
Tomato
(Solanum
lycopersicum
L.)
cultivation
is
crucial
globally
due
to
its
nutritional
and
economic
value.
However,
the
crop
faces
significant
threats
from
various
pests,
including
Tuta
absoluta,
Helicoverpa
armigera,
Leptinotarsa
decemlineata,
among
others.
These
pests
not
only
reduce
yield
but
also
increase
production
costs
heavy
reliance
on
pesticides.
Traditional
pest
detection
methods
are
labor-intensive
prone
errors,
necessitating
exploration
of
advanced
techniques.
This
study
aims
enhance
in
tomato
using
AI-based
language
models.
Specifically,
it
integrates
YOLOv8
for
segmentation
tasks
ChatGPT-4
generating
detailed,
actionable
insights
detected
pests.
was
chosen
superior
performance
agricultural
detection,
capable
processing
large
volumes
data
real-time
with
high
accuracy.
The
methodology
involved
training
model
images
plant
damage.
achieved
a
precision
98.91%,
recall
98.98%,
mAP50
98.75%,
mAP50-95
97.72%
tasks.
For
tasks,
97.47%,
98.81%,
99.38%,
95.99%.
metrics
demonstrate
improvements
over
traditional
methods,
indicating
model's
effectiveness.
integration
further
enhances
system
by
providing
detailed
explanations
recommendations
based
approach
facilitates
expert
consultation,
making
management
accessible
untrained
producers,
especially
remote
areas.
study's
results
underscore
potential
combining
models
revolutionize
practices.
Future
research
should
focus
these
domain-specific
improve
accuracy
reliability.
Additionally,
addressing
computational
limitations
personal
devices
will
be
broader
adoption.
promises
democratize
information
access,
promoting
more
resilient,
informed,
environmentally
conscious
farming.
Plant Signaling & Behavior,
Год журнала:
2024,
Номер
20(1)
Опубликована: Дек. 26, 2024
Biochemical
and
molecular
mechanisms
have
been
essential
to
reduce
various
insect
attacks
on
plants.
The
biochemical
methods
are
wide
involving
direct
indirect
defenses.
defensive
chemical
substances
secreted
effectively
the
wound
caused
by
herbivores
(insects
phytopathogens)
Plants
responded
producing
VOCs
which
draw
natural
enemies
of
insects
phytopathogens.
progress
observed
in
cognition
stimulus
plants
their
potential
control
responses
is
characterized
modification
shifts
our
attention
development
endogenous
resistance
preserving
crops.
main
objective
implementing
a
biotechnological
mechanism
crop
production
employ
durable
multimechanistic
alternatives
pests
via
plant
produces
upon
encountering
attack.
Environmental Microbiology Reports,
Год журнала:
2025,
Номер
17(1)
Опубликована: Янв. 27, 2025
ABSTRACT
Sour
rot
(SR)
is
a
late‐season
non‐Botrytis
affecting
grapevines,
resulting
from
complex
interplay
of
microorganisms,
including
non‐
Saccharomyces
yeasts
and
acetic
acid
bacteria.
Nonmicrobial
factors
contributing
to
disease
development
encompass
vectors
(e.g.,
Drosophila
spp.),
the
presence
wounds
or
microcracks
on
grape
berry
surfaces,
environmental
conditions
during
ripening.
The
microbial
complexes
within
SR‐affected
grapes
exhibit
variability
among
different
bioclimates
seasons,
with
certain
microorganisms
predominating
under
specific
conditions.
This
study
examined
influence
microbiome
composition
associated
bunches,
utilising
data
41
locations
across
three
distinct
Italian
bioclimates.
We
selected
nine
yeast
two
bacterial
species
frequently
isolated
sour‐rotted
for
analysis.
growth
responses
these
temperature
were
assessed
by
categorising
them
into
four
ecophysiological
clusters.
Furthermore,
we
analysed
distribution
their
respective
clusters
results
indicate
that
microbiomes
involved
in
SR
can
vary
according
bioclimatic
grape‐growing
area.
Further
research
required
comprehend
ecological
requirements
define
niches
understand
geographical
epidemiology,
enhance
management
strategies.
Abstract
Whitefly
(
Bemisia
tabaci
(Genn.)
is
an
important
pest
in
pepper
Capsicum
spp.)
production,
not
only
because
infestations
lower
the
quality
of
fruits
but
also
whiteflies
transfer
viruses.
Therefore,
resistant
varieties
are
urgently
needed.
In
this
research,
we
searched
for
accessions
to
B.
MEAM1.
Forty
underwent
screening
through
a
no-choice
clip
cage
assay,
evaluating
adult
survival
and
oviposition
rate
female
whiteflies.
Accessions
with
low
were
validated
by
assessing
whitefly
population
buildup
whole
plant
assay.
Lastly,
nymphal
development
scored
three
most
accessions.
Accession
Zuchtmaterial
Nr.1
demonstrated
ability
reduce
reproduction
halted
at
egg
first
stage,
thus
repressing
buildup.
Additionally,
observed
that
glandular
trichomes
type
VI
found
exhibited
negative
correlation
survival,
rate,
number
all
stages
Thus,
conclude
Nr.
1
could
serve
as
useful
source
resistance,
possible
role
resistance
mechanism.
Deleted Journal,
Год журнала:
2024,
Номер
76(2), С. 447 - 460
Опубликована: Фев. 19, 2024
The
whitefly,
Bemisia
tabaci
Mediterranean
(MED),
is
an
invasive
pest
of
several
crops,
including
soybeans.
objective
this
study
was
to
evaluate
the
resistance
soybean
genotypes
B.
MED,
in
addition
influence
possibly
related
physical
and
morphological
factors.
A
no-choice
test
carried
out
with
90
genotypes.
Subsequently,
35
materials
were
selected
for
further
multiple-choice
tests.
Trichomes
leaf
color
plants
observed,
aim
correlating
these
factors
preference
colonization
MED.
KS
4202,
TMG
1188
RR,
M
7739
IPRO,
65l65
PI
229358
least
preferred
by
adults
In
test,
lowest
numbers
eggs
nymphs
per
square
centimeter
observed
Dowling,
229358,
IAC
24,
4202.
19,
1288
1182
99R09,
2375
IPRO
presented
assay.
Plants
higher
trichome
density
MED
and,
consequently,
more
heavily
colonized
insects.
leaves
lower
luminosity
reduced
green
yellow
intensity
attractive
whiteflies.
summary,
RR
exhibited
both
assays,
thus
indicating
their
potential
as
promising
sources
Abstract
Background
Transgenic
plants
expressing
proteins
that
target
the
eggs
of
ubiquitous
plant
pest
Bemisia
tabaci
(whitefly)
could
be
an
effective
insecticide
strategy.
Two
approaches
for
protein
delivery
are
assessed
using
mCherry
reporter
gene
in
transgenic
tomato
plants,
while
accommodating
autofluorescence
both
plant,
phloem-feeding
whitefly
and
pedicle-attached
eggs.
Results
Both
strategies
were
segregated
to
homozygous
genotype
digital
PCR.
The
first
strategy
uses
a
glycotransferase
secretion
signal
peptide.
Despite
bright
apoplastic
accumulation,
is
not
evident
second
targets
vivo
eggs,
where
transgene
was
fused
transduction
domain
(PTD)
facilitate
uptake
into
hemolymph
as
well
synthetic
vitellogenin
ovary-targeting
sequence.
Phloem-specific
expression
fusion
achieved
from
Commelina
viral
promoter.
Accumulation
sufficient
observed
females
feeding
on
these
nor
their
subsequently
laid
non-transgenic
plants.
Egg
protection
may
mediated
by
protease
activity
which
macerated
Conclusions
proved
desired
tissue-specific
tomato,
but
insufficiently
sensitive
allow
localization
whiteflies
or
Segregated
lines
important
drawing
conclusions.
implications
observations
possible
pest-control
including
preliminary
analogous
chitinase
constructs
discussed.
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Март 26, 2024
Abstract
Under
the
background
of
global
climate
change,
insect
herbivory
phenomenon
has
been
frequent,
which
significantly
affects
growth,
survival,
and
regeneration
forest
plants
in
warm
temperate
zone
China.
Plants
can
adopt
defense
responses
to
adapt
defoliation.
Therefore,
field
experiments
were
conducted
on
five
common
species,
Quercus
acutissima,
serrata,
aliena,
dentata,
Robinia
pseudoacacia.
We
measured
leaf
traits
healthy
trees
defoliated
trees,
explore
response
strategies
species
zones
Our
results
showed
that
native
stored
more
carbon
extreme
environments
for
survival
rather
than
while
alien
tended
active
resource
acquisition
inclined
towards
growth.
Then
content
tannins
flavonoids
R.
pseudoacacia
did
not
increase
after
damage,
secondary
metabolites
such
as
tannins,
flavonoids,
total
phenols
Q.
dentata
increased
damage.
This
indicated
compared
would
invest
resources
defense,
might
reduce
allocation
Thus,
Quercus
have
stronger
resistance
