Phytopathology,
Год журнала:
2024,
Номер
114(8), С. 1733 - 1741
Опубликована: Май 29, 2024
In
the
past
decade,
there
has
been
a
recognized
need
for
innovative
methods
to
monitor
and
manage
plant
diseases,
aiming
meet
precision
demands
of
modern
agriculture.
Over
last
15
years,
significant
advances
in
detection,
monitoring,
management
diseases
have
made,
largely
propelled
by
cutting-edge
technologies.
Recent
agriculture
driven
sophisticated
tools
such
as
optical
sensors,
artificial
intelligence,
microsensor
networks,
autonomous
driving
vehicles.
These
technologies
enabled
development
novel
cropping
systems,
allowing
targeted
crops,
contrasting
with
traditional,
homogeneous
treatment
large
crop
areas.
The
research
this
field
is
usually
highly
collaborative
interdisciplinary
endeavor.
It
brings
together
experts
from
diverse
fields
pathology,
computer
science,
statistics,
engineering,
agronomy
forge
comprehensive
solutions.
Despite
progress,
translating
advancements
decision-making
or
automation
into
agricultural
practice
remains
challenge.
knowledge
transfer
extension
particularly
challenging.
Enhancing
accuracy
timeliness
disease
detection
continues
be
priority,
data-driven
intelligence
systems
poised
play
pivotal
role.
This
perspective
article
addresses
critical
questions
challenges
faced
implementation
digital
management.
underscores
urgency
integrating
technological
traditional
integrated
pest
highlights
unresolved
issues
regarding
establishment
control
thresholds
site-specific
treatments
necessary
alignment
technology
use
regulatory
frameworks.
Importantly,
paper
calls
intensified
efforts,
widespread
dissemination,
education
optimize
application
management,
recognizing
intersection
technology's
potential
its
current
practical
limitations.
IEEE Transactions on Systems Man and Cybernetics Systems,
Год журнала:
2023,
Номер
53(6), С. 3718 - 3727
Опубликована: Янв. 4, 2023
Agricultural
metaverse
(AgriVerse)
aims
to
optimize
the
production
chain
by
saving
costs,
increasing
efficiencies,
and
breaking
information
silos,
in
order
achieve
sustainable
agriculture.
While
AgriVerse
is
featured
virtual-real
interaction
of
agriculture-related
processes
based
on
heterogeneous
data,
knowledge,
models,
link
between
intensively
studied
plant
modeling
vague.
This
article
presents
briefly
research
contents
modeling,
analyzes
ongoing
transition
at
age
artificial
intelligence
(AI),
envisions
future
with
support
agricultural
foundation
model,
decentralized
organization
(DAO)
science
(DeSci)
model.
Three
application
scenarios
are
presented.
The
opportunities
challenges
discussed.
work
expected
identify
key
issues
bring
practitioners
diverse
backgrounds
together
into
community.
npj Ocean Sustainability,
Год журнала:
2023,
Номер
2(1)
Опубликована: Окт. 9, 2023
Abstract
Digital
twins,
a
nascent
yet
potent
computer
technology,
can
substantially
advance
sustainable
ocean
management
by
mitigating
overfishing
and
habitat
degradation,
modeling,
preventing
marine
pollution
supporting
climate
adaptation
safely
assessing
geoengineering
alternatives.
Concomitantly,
digital
twins
may
facilitate
multi-party
spatial
planning.
However,
the
potential
of
this
emerging
technology
for
such
purposes
is
underexplored
to
be
realized,
with
just
one
notable
project
entitled
European
Twins
Ocean.
Here,
we
consider
promise
sustainability
across
four
thematic
areas.
We
further
emphasize
implementation
barriers,
namely,
data
availability
quality,
compatibility,
cost.
Regarding
oceanic
availability,
note
issues
coverage,
depth
temporal
resolution,
limited
sharing,
underpinned,
among
other
factors,
insufficient
knowledge
processes.
Inspired
prospects
informed
impending
difficulties,
propose
improve
quality
about
oceans,
take
measures
ensure
standardization,
prioritize
in
areas
high
conservation
value
following
‘nested
enterprise’
approach.
Summary
We
examine
the
link
between
labour
market
developments
and
new
technologies
such
as
artificial
intelligence
(AI)
software
in
16
European
countries
over
period
2011–9.
Using
data
for
occupations
at
three-digit
level,
we
find
that
on
average
employment
shares
have
increased
more
exposed
to
AI.
This
is
particularly
case
with
a
relatively
higher
proportion
of
younger
skilled
workers.
While
there
exists
heterogeneity
across
countries,
only
very
few
show
decline
AI-enabled
automation.
Country
this
result
seems
be
linked
pace
technology
diffusion
education,
but
also
level
product
regulation
(competition)
protection
laws.
In
contrast
findings
employment,
little
evidence
relationship
relative
wages
potential
exposures
technologies.
Food and Energy Security,
Год журнала:
2025,
Номер
14(1)
Опубликована: Янв. 1, 2025
ABSTRACT
Plant
phenomics
deals
with
the
measurement
of
plant
phenotypes
associated
genetic
and
environmental
variation
in
controlled
environment
agriculture
(CEA).
Encompassing
a
spectrum
from
molecular
biology
to
ecosystem‐level
studies,
it
employs
high‐throughput
phenotyping
(HTP)
approaches
quickly
evaluate
characteristics
enhance
yields
crops
smart
facilities.
HTP
uses
parameters
for
accuracy,
such
as
software
sensors,
well
hyperspectral
imaging
pigment
data,
thermal
water
content,
fluorescence
photosynthesis
rates.
They
provide
information
on
growth
kinetics,
physiological
biochemical
characteristics,
genotype–environment
interaction.
Artificial
intelligence
(AI)
machine
learning
(ML)
are
used
large
volume
phenotypic
data
predict
rates,
determine
optimal
time
plants,
or
detect
diseases,
nutrient
deficiencies,
pests
at
an
early
stage.
The
lighting
factories
is
adjusted
based
specific
phase
using
different
light
intensities,
spectrums,
durations
germination,
vegetative
growth,
flowering
stages,
hydroponics
method
providing
nutrients,
CRISPR
(Clustered
Regularly
Interspaced
Short
Palindromic
Repeats)
improving
certain
resistance
drought.
These
systems
crop
production,
yields,
adaptability,
input
use
by
optimizing
utilizing
precision
breeding
techniques.
AI
combination
several
disciplines,
promoting
understanding
plant–environment
interactions
relation
problems
resource
use,
climate
change.
It
affects
their
capacity
develop
that
capture
inputs,
minimize
chemical
application,
resilient
Phenomics
cost‐effective,
reduces
contributes
more
sustainable
agricultural
practices,
being
economically
environmentally
sound.
Altogether,
central
CEA
due
its
capitalize
potential
within
advance
sustainability
food
security.
Through
phenomic
research,
next
advancements
likely
be
even
revolutionary
terms
practices
worldwide.
IEEE/CAA Journal of Automatica Sinica,
Год журнала:
2022,
Номер
9(12), С. 2055 - 2062
Опубликована: Дек. 1, 2022
Briefing:
The
demand
for
food
is
tremendously
increasing
with
the
growth
of
world
population,
which
necessitates
development
sustainable
agriculture
under
impact
various
factors,
such
as
climate
change.
To
fulfill
this
challenge,
we
are
developing
Metaverses
agriculture,
referred
to
AgriVerse,
our
Decentralized
Complex
Adaptive
Systems
in
Agriculture
(DeCASA)
project,
a
digital
smart
villages
created
alongside
Sciences
(DeSci)
and
Autonomous
Organizations
(DAO)
Cyber-Physical-Social
(CPSSs).
Additionally,
provide
architectures,
operating
modes
major
applications
DeCASA
Agri-Verse.
For
achieving
foundation
model
based
on
ACP
theory
federated
intelligence
envisaged.
Finally,
discuss
challenges
opportunities.
