CABI Agriculture and Bioscience,
Год журнала:
2024,
Номер
5(1)
Опубликована: Авг. 17, 2024
Abstract
In
an
era
marked
by
rapid
global
changes,
the
reinforcement
and
modernization
of
plant
health
surveillance
systems
have
become
imperative.
Sixty-five
scientists
present
here
a
research
agenda
for
enhanced
modernized
to
anticipate
mitigate
disease
pest
emergence.
Our
approach
integrates
wide
range
scientific
fields
(from
life,
social,
physical
engineering
sciences)
identifies
key
knowledge
gaps,
focusing
on
anticipation,
risk
assessment,
early
detection,
multi-actor
collaboration.
The
directions
we
propose
are
organized
around
four
complementary
thematic
axes.
first
axis
is
anticipation
emergence,
encompassing
innovative
forecasting,
adaptive
potential,
effects
climatic
cropping
system
changes.
second
addresses
use
versatile
broad-spectrum
tools,
including
molecular
or
imaging
diagnostics
supported
artificial
intelligence,
monitoring
generic
matrices
such
as
air
water.
third
focuses
known
pests
from
new
perspectives,
i.e.,
using
novel
approaches
detect
species
but
also
anticipating
detecting,
within
species,
populations
genotypes
that
pose
higher
risk.
fourth
advocates
management
commons
through
establishment
cooperative
long-term
data-driven
alert
information
dissemination.
We
stress
importance
integrating
data
multiple
sources
open
science
databases
metadata,
alongside
developing
methods
interpolating
extrapolating
incomplete
data.
Finally,
advocate
Integrated
Health
Surveillance
in
One
context,
favoring
tailored
solutions
problems
recognizing
interconnected
risks
plants,
humans,
animals
environment,
food
insecurity,
pesticide
residues,
environmental
pollution
alterations
ecosystem
services.
Biological Control,
Год журнала:
2022,
Номер
176, С. 105100 - 105100
Опубликована: Ноя. 7, 2022
Trichoderma-bacteria
co-inoculations
have
a
synergistic
effect
on
plant
benefits.•
biocontrollers
similar
results
than
chemical
pesticides.•
Compatibility
and
formulation
are
key
steps
in
co-inoculants.
Smart Agricultural Technology,
Год журнала:
2024,
Номер
8, С. 100480 - 100480
Опубликована: Май 28, 2024
Plant
diseases
can
significantly
reduce
crop
yield
and
product
quality.
Visual
inspections
of
plants
by
human
observers
for
disease
identification
are
time-consuming,
costly,
prone
to
error.
Advances
in
artificial
intelligence
(AI)
have
created
opportunities
the
rapid
diagnosis
non-destructive
classification
plant
pathogens.
Several
machine
vision
techniques
been
developed
identify
classify
automatically
based
on
morphology
specific
symptoms.
The
use
deep
learning
models
has
achieved
acceptable
results,
but
they
require
large
datasets
training,
which
be
labor-intensive,
computationally
costly
This
problem
solved,
a
point,
using
data
augmentation
generative
AI
order
increase
size
datasets.
Furthermore,
combination
feature
extraction
was
used
accurate
detection
classification.
In
some
cases,
traditional
base
classifiers
trained
with
small
including
basic
shape,
color,
texture
features
feasible
efficient
diseases.
performance
such
depends
primarily
extracted
from
images;
therefore,
plays
vital
role
identifying
Feature
engineering,
process
most
relevant
variables
raw
develop
an
predictive
model,
is
explored
this
paper.
Plant Nano Biology,
Год журнала:
2024,
Номер
9, С. 100079 - 100079
Опубликована: Июнь 2, 2024
The
growing
world's
population
and
increasing
demand
for
food
production
can
lead
to
major
security
safety
challenges.
different
varieties
of
pathogens
such
as
bacteria,
fungi,
viruses,
pests,
insects,
etc.
are
the
causes
crop
loss.
So,
implementation
biosensors
in
field
agriculture
be
a
beneficial
tool
solve
this
problem.
Biosensors
help
promote
sustainable
by
early
detection
pathogens,
fertilizers,
herbicides,
pesticides,
moisture,
diseases
crops
animals,
well
presence
heavy
metal
ions,
toxins.
Additionally,
it
also
measure
parameters
including
soil
pH,
chlorophyll
content,
photosynthetic
protein
total
nutrient
uptake
(macronutrients
micronutrients)
plants,
With
these
biosensors,
farmers
increase
yields,
optimize
fertilization
techniques,
preserve
resources
detecting
measuring
particular
nutrients.
Artificial
Intelligence
(AI)
Internet
Things
(IoT)
technology
greatly
transforms
state
traditional
addressing
various
challenges,
pest
management
post-harvest
issues.
In
review,
types
utilized
agricultural
monitoring
related
plants
but
some
obstacles
need
addressed.
This
article
mainly
focuses
on
electrochemical
optical
plant
wearable
etc.,
their
applications
advantages
along
with
adoption
AI
IoT
smart-
farming
discussed.
Measurement Sensors,
Год журнала:
2023,
Номер
26, С. 100713 - 100713
Опубликована: Фев. 22, 2023
The
term
"smart
agriculture"
describes
how
farming
is
carried
out
in
the
modern
day
as
technology
develops.
Application
of
diverse
insect
protection
and
agricultural
production
tactics
crucial
for
crop
monitoring.
structure
it
now
has
problems.
A
particular
core
Graphical
Processing
Unit
(GPU)
used
to
manage
numerous
sensors
connected
surveillance
pest
management.
Parallel
Distributed
Simulation
Framework
(PDSF)
with
Internet
Things
(IoT)
proposed
management
monitoring
tools.
It
lessens
pressure
on
a
certain
GPU,
evenly
distributes
workload
over
all
available
GPUs
at
simultaneously,
delivers
data
dashboards
even
when
it's
broken.
procedure
will
decrease
system
performance.
In
PDSF
multi-threading
paradigm,
each
GPU
unit
workloads
specific
additional
cores.
To
carry
various
tasks,
four
levels
this
system—crop
management,
identification
control,
output
activities,
input
functional
areas—are
distributed
among
them.
information
processed
simultaneously
handled
an
efficient
controlled
manner.
improves
performance
measures
98.65%.
Frontiers in Plant Science,
Год журнала:
2024,
Номер
15
Опубликована: Май 13, 2024
Environmental
stresses
are
the
main
constraints
on
agricultural
productivity
and
food
security
worldwide.
This
issue
is
worsened
by
abrupt
severe
changes
in
global
climate.
The
formation
of
sugarcane
yield
accumulation
sucrose
significantly
influenced
biotic
abiotic
stresses.
Understanding
biochemical,
physiological,
environmental
phenomena
associated
with
these
essential
to
increase
crop
production.
review
explores
effect
factors
content
highlights
negative
effects
insufficient
water
supply,
temperature
fluctuations,
insect
pests,
diseases.
article
also
explains
mechanism
reactive
oxygen
species
(ROS),
role
different
metabolites
under
stresses,
function
stress-related
resistance
genes
sugarcane.
further
discusses
improvement
approaches,
a
focus
endophytic
consortium
endophyte
application
plants.
Endophytes
vital
plant
defense;
they
produce
bioactive
molecules
that
act
as
biocontrol
agents
enhance
immune
systems
modify
responses
through
interaction
provides
an
overview
internal
mechanisms
growth
offers
new
ideas
for
improving
fitness
productivity.
