Non-invasive and early detection of tomato spotted wilt virus infection in tomato plants using a hand-held Raman spectrometer and machine learning modelling
Plant Stress,
Journal Year:
2025,
Volume and Issue:
unknown, P. 100732 - 100732
Published: Jan. 1, 2025
Language: Английский
Characterization of rice starch changes in saline and alkaline area under different fertilization conditions based on Raman spectral recognition technology
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: March 18, 2025
Starch
content
in
rice
is
one
of
the
important
parameters
characterizing
nutritional
quality
rice,
and
starch
produced
saline
soils
under
different
fertilization
conditions
varies.
In
this
study,
Raman
spectroscopy
combined
with
three
machine
learning
models,
support
vector
(SVM),
feedforward
neural
network,
k-nearest
neighbor
classification,
was
used
to
classify
evaluate
effect
fertilizer
treatments
on
rice.
The
collected
spectral
data
were
normalized
before
learning,
then
preprocessed
multiple
scattering
correction
(MSC),
standard
normal
variable,
Savitzky–Golay
filtering
algorithms
improve
reliability
data.
evaluation
indexes
such
as
confusion
matrix
receiver
operating
characteristic
curve
comprehensively
analyzed
model's
performance.
research
shows
that
MSC
preprocessing
method
significantly
improves
classification
accuracy
prediction
ability
all
close
100%,
while
overall
performance
SVM
models
after
various
best
among
methods.
predictive
coefficient
determination,
root
mean
square
error,
average
relative
error
detection
model
built
by
0.93,
0.04%,
0.20%,
respectively,
which
indicated
its
had
high
low
error.
results
study
carry
out
identification
techniques
correlation
characteristics,
providing
theoretical
experimental
for
rapid
quality.
Language: Английский
Raman spectroscopy – a visit to the literature on plant, food, and agricultural studies
Journal of the Science of Food and Agriculture,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Aug. 12, 2024
Raman
spectroscopy,
a
fast,
non-invasive,
and
label-free
optical
technique,
has
significantly
advanced
plant
food
studies
precision
agriculture
by
providing
detailed
molecular
insights
into
biological
tissues.
Utilizing
the
scattering
effect
generates
unique
spectral
fingerprints
that
comprehensively
analyze
tissue
composition,
concentration,
structure.
These
are
obtained
without
chemical
additives
or
extensive
sample
preparation,
making
spectroscopy
particularly
suitable
for
in-field
applications.
Technological
enhancements
such
as
surface-enhanced
scattering,
Fourier-transform-Raman
chemometrics
have
increased
sensitivity
precision.
other
advancements
enable
real-time
monitoring
of
compound
translocation
within
plants
improve
detection
contaminants,
essential
safety
crop
optimization.
Integrating
agronomic
practices
is
transformative
marks
shift
toward
more
sustainable
farming
activities.
It
assesses
quality
-
well
originated
from
production
early
stress
supports
targeted
breeding
programs.
Advanced
data
processing
techniques
machine
learning
integration
efficiently
handle
complex
data,
dynamic
view
conditions
health
under
varying
environmental
stresses.
As
global
faces
dual
challenges
increasing
productivity
sustainability,
stands
out
an
indispensable
tool,
enhancing
practices'
precision,
safety,
compatibility.
This
review
intended
to
select
briefly
comment
on
outstanding
literature
give
researchers,
students,
consultants
reference
works
in
mainly
focused
plant,
food,
sciences.
©
2024
Society
Chemical
Industry.
Language: Английский