Heliyon,
Journal Year:
2024,
Volume and Issue:
10(17), P. e36808 - e36808
Published: Aug. 24, 2024
This
study
leverages
the
BERTopic
algorithm
to
analyze
evolution
of
research
within
precision
agriculture,
identifying
37
distinct
topics
categorized
into
eight
subfields:
Data
Analysis,
IoT,
UAVs,
Soil
and
Water
Management,
Crop
Pest
Livestock,
Sustainable
Agriculture,
Technology
Innovation.
By
employing
BERTopic,
based
on
a
transformer
architecture,
this
enhances
topic
refinement
diversity,
distinguishing
it
from
traditional
reviews.
The
findings
highlight
significant
shift
towards
IoT
innovations,
such
as
security
privacy,
reflecting
integration
smart
technologies
with
agricultural
practices.
Notably,
introduces
comprehensive
popularity
index
that
integrates
trend
intensity
proportion,
providing
nuanced
insights
dynamics
across
countries
journals.
analysis
shows
regions
robust
development,
USA
Germany,
are
advancing
in
like
Machine
Learning
while
diversity
topics,
assessed
through
information
entropy,
indicates
varied
global
scope.
These
assist
scholars
institutions
selecting
directions
provide
newcomers
an
understanding
field's
dynamics.
Advances in environmental engineering and green technologies book series,
Journal Year:
2025,
Volume and Issue:
unknown, P. 321 - 362
Published: Jan. 3, 2025
As
the
demand
for
sustainable
and
efficient
farming
practices
grows,
autonomous
drones
have
emerged
as
vital
tools
enhancing
agricultural
productivity
resource
management.
The
chapter
begins
by
outlining
fundamental
principles
of
drone
operation
in
settings,
highlighting
advancements
sensor
technology,
machine
learning,
real-time
data
processing.
It
then
explores
various
cutting-edge
techniques,
including
multispectral
imaging,
3D
mapping,
AI-driven
analytics,
that
enable
precise
monitoring
crop
health,
soil
conditions,
pest
infestations.
Practical
applications
these
techniques
shows
how
been
successfully
deployed
tasks
such
scouting,
variable
rate
application,
yield
estimation.
By
providing
a
comprehensive
overview
latest
technological
their
real-world
applications,
this
serves
valuable
researchers,
agronomists,
practitioners
aiming
to
leverage
optimize
practices.
IGI Global eBooks,
Journal Year:
2025,
Volume and Issue:
unknown, P. 197 - 232
Published: Feb. 18, 2025
Amidst
the
escalating
global
challenges
of
climate
change,
limited
resources,
and
population
growth,
adoption
sustainable
land
resource
management
has
become
imperative
to
ensure
food
security
environmental
conservation.
Precision
agriculture
enhances
process
efficiency,
reduces
impact,
improves
agricultural
productivity
through
integration
artificial
intelligence
technologies,
including
machine
learning,
deep
computer
vision.
Key
findings
indicate
a
reduction
10–20%
in
input
costs
an
increase
15–25%
crop
yields
efficient
utilisation.
Furthermore,
precision
irrigation
systems
can
achieve
water
savings
up
50%,
while
targeted
pesticide
treatments
reduce
chemical
usage
by
30–40%.
This
chapter
examines
economic
benefits,
highlighting
20%
CO2
emissions.
Recent
advancements
underscore
potential
AI
foster
agriculture,
promoting
conservation
viability.
Journal of Fungi,
Journal Year:
2025,
Volume and Issue:
11(3), P. 207 - 207
Published: March 6, 2025
Sorghum
(Sorghum
bicolor
L.)
is
a
globally
important
energy
and
food
crop
that
becoming
increasingly
integral
to
security
the
environment.
However,
its
production
significantly
hampered
by
various
fungal
phytopathogens
affect
yield
quality.
This
review
aimed
provide
comprehensive
overview
of
major
affecting
sorghum,
their
impact,
current
management
strategies,
potential
future
directions.
The
diseases
covered
include
anthracnose,
grain
mold
complex,
charcoal
rot,
downy
mildew,
rust,
with
an
emphasis
on
pathogenesis,
symptomatology,
overall
economic,
social,
environmental
impacts.
From
initial
use
fungicides
shift
biocontrol,
rotation,
intercropping,
modern
tactics
breeding
resistant
cultivars
against
mentioned
are
discussed.
In
addition,
this
explores
disease
management,
particular
focus
role
technology,
including
digital
agriculture,
predictive
modeling,
remote
sensing,
IoT
devices,
in
early
warning,
detection,
management.
It
also
key
policy
recommendations
support
farmers
advance
research
thus
emphasizing
need
for
increased
investment
research,
strengthening
extension
services,
facilitating
access
necessary
inputs,
implementing
effective
regulatory
policies.
concluded
although
pose
significant
challenges,
combined
effort
innovative
policies
can
mitigate
these
issues,
enhance
resilience
sorghum
facilitate
global
issues.
Frontiers in Sustainable Food Systems,
Journal Year:
2025,
Volume and Issue:
9
Published: March 6, 2025
Introduction
Most
farmers
in
Nigeria
lack
knowledge
of
their
farmland’s
nutrient
content,
often
relying
on
intuition
for
crop
cultivation.
Even
when
aware,
they
struggle
to
interpret
soil
information,
leading
improper
fertilizer
application,
which
can
degrade
and
ground
water
quality.
Traditional
analysis
requires
field
sample
collection
laboratory
analysis;
a
tedious
time-consuming
process.
Digital
Soil
Mapping
(DSM)
leverages
Machine
Learning
(ML)
create
detailed
maps,
helping
mitigate
depletion.
Despite
its
growing
use,
existing
DSM-based
ML
methods
face
challenges
prediction
accuracy
data
representation.
Aim
This
study
presents
GeaGrow,
an
innovative
mobile
app
that
enhances
agricultural
productivity
by
predicting
properties
providing
tailored
recommendations
yam,
maize,
cassava,
upland
rice,
lowland
rice
southwest
using
Artificial
Neural
Networks
(ANN).
Materials
The
presented
method
involved
the
samples
from
six
states
were
analysed
compile
primary
dataset
mapped
coordinates.
A
secondary
was
compiled
iSDAsoil’s
API
augmentation
validation.
two
sets
pre-processed
normalized
Python,
ANN
employed
predict
such
as
NPK,
Organic
Carbon,
Textural
Composition
pH
levels
through
regressive
while
building
composite
model
Texture
Classification
based
predicted
composition.
model’s
performance
yielded
Mean
Absolute
Error
(MAE)
1.9750
NPK
Carbon
prediction,
3.5461
0.1029
prediction.
For
classification
texture,
results
showed
high
value
99.9585%.
Results
highlight
effectiveness
combining
texture
with
retention,
optimize
application.
GeaGrow
provides
accessible,
location-based
insights
personalized
recommendations,
marking
significant
advancement
technology.
also
smallholder
scalable,
ease
adoption
use
developed
Conclusion
research
demonstrates
potential
transform
management
improve
yields,
contributing
sustainable
farming
practices
Nigeria.
