Journal of Agricultural and Food Chemistry,
Год журнала:
2024,
Номер
72(43), С. 24109 - 24129
Опубликована: Окт. 16, 2024
The
brown
marmorated
stink
bug
(Halyomorpha
halys)
poses
a
significant
threat
to
hazelnut
crops
by
affecting
kernel
development
and
causing
quality
defects,
reducing
the
market
value.
While
previous
studies
have
identified
bitter-tasting
compounds
in
affected
kernels,
impact
of
feeding
on
metabolome,
particularly
concerning
aroma
precursors,
remains
underexplored.
This
study
aims
map
nonvolatile
metabolome
volatilome
samples
obtained
caging
H.
halys
different
cultivars
two
locations
identify
markers
for
diagnosing
damage.
Using
multiomic
approach
involving
headspace
solid-phase
microextraction
(HS-SPME),
comprehensive
two-dimensional
gas
chromatography-time-of-flight
mass
spectrometry
(GC
×
GC-TOF
MS),
liquid
chromatography-high-resolution
(LC-HRMS),
both
raw
roasted
hazelnuts
are
analyzed,
with
artificial
intelligence
(AI)
machine
learning
tools
employed
explore
data
correlations.
finds
that
exhibit
high
chemical
complexity
classes
such
as
aldehydes,
ketones,
alcohols,
terpenes
hazelnuts.
Multivariate
analysis
indicates
orchard
location
significantly
impacts
followed
damage
type,
cultivar
differences
being
less
pronounced.
Partial
least-squares
discriminant
(PLS-DA)
models
achieve
predictive
accuracy
(99%)
type
(≈80%),
showing
highest
accuracy.
Correlation
matrices
reveal
relationships
between
metabolites
samples,
suggesting
potential
could
guide
assessment
mitigation
strategies.
Data
fusion
techniques
further
enhance
classification
performance,
predicting
underscoring
integrating
multiple
sets
assessment.
Nutrients,
Год журнала:
2024,
Номер
16(17), С. 2922 - 2922
Опубликована: Сен. 1, 2024
Food
systems
face
the
challenge
of
maintaining
adequate
nutrition
for
all
populations.
Inter-individual
responses
to
same
diet
have
made
precision
or
personalized
(PN)
an
emerging
and
relevant
topic.
The
aim
this
study
is
analyze
evolution
PN
field,
identifying
principal
actors
topics,
providing
a
comprehensive
overview.
Therefore,
bibliometric
analysis
scientific
research
available
through
Web
Science
(WOS)
database
was
performed,
revealing
2148
papers
up
June
2024.
VOSviewer
WOS
platform
were
employed
processing
analysis,
included
evaluation
diverse
data
such
as
country,
author
most
frequent
keywords,
among
others.
revealed
period
exponential
growth
from
2015
2023,
with
USA,
Spain,
England
top
contributors.
field
“Nutrition
Dietetics”
particularly
significant,
comprising
nearly
33%
total
publications.
highly
cited
institutions
are
universities
Tufts,
College
Dublin,
Navarra.
relationship
between
nutrition,
genetics,
omics
sciences,
along
dietary
intervention
studies,
has
been
defining
factor
in
PN.
In
conclusion,
represents
promising
significant
potential
further
advancement
growth.
Journal of Agricultural and Food Chemistry,
Год журнала:
2024,
Номер
72(42), С. 23616 - 23630
Опубликована: Окт. 11, 2024
This
study
examines
the
complex
volatilome
of
maize
silage,
both
with
and
without
commercial
heterolactic
strain
inoculation,
conserved
for
100
days,
using
quantitative
volatilomics.
Chemical
classes
linked
to
microbial
metabolism
were
analyzed
across
a
concentration
range
from
10
μg
g
IntechOpen eBooks,
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 2, 2024
Multidimensional
separation
systems
offer
several
advantages
over
traditional
one-dimensional
systems,
particularly
their
ability
to
separate
molecules
from
complex
mixtures.
Two-dimensional
liquid
chromatography
(2D-LC)
significantly
enhances
the
analyze
mixtures
by
providing
greater
power,
sensitivity,
and
flexibility,
making
it
an
invaluable
tool
for
metabolomics
research.
The
2D-LC
is
exciting
mode
when
pursuing
untargeted
analysis,
as
allows
high-resolution
subsequent
identification
quantification
of
more
analytes.
This
chapter
summarizes
current
applications
in
setups
different
modes
that
are
being
employed,
presenting
most
suitable
combinations
chromatographic
methods
targeted
applications.
Journal of Agricultural and Food Chemistry,
Год журнала:
2024,
Номер
72(43), С. 24109 - 24129
Опубликована: Окт. 16, 2024
The
brown
marmorated
stink
bug
(Halyomorpha
halys)
poses
a
significant
threat
to
hazelnut
crops
by
affecting
kernel
development
and
causing
quality
defects,
reducing
the
market
value.
While
previous
studies
have
identified
bitter-tasting
compounds
in
affected
kernels,
impact
of
feeding
on
metabolome,
particularly
concerning
aroma
precursors,
remains
underexplored.
This
study
aims
map
nonvolatile
metabolome
volatilome
samples
obtained
caging
H.
halys
different
cultivars
two
locations
identify
markers
for
diagnosing
damage.
Using
multiomic
approach
involving
headspace
solid-phase
microextraction
(HS-SPME),
comprehensive
two-dimensional
gas
chromatography-time-of-flight
mass
spectrometry
(GC
×
GC-TOF
MS),
liquid
chromatography-high-resolution
(LC-HRMS),
both
raw
roasted
hazelnuts
are
analyzed,
with
artificial
intelligence
(AI)
machine
learning
tools
employed
explore
data
correlations.
finds
that
exhibit
high
chemical
complexity
classes
such
as
aldehydes,
ketones,
alcohols,
terpenes
hazelnuts.
Multivariate
analysis
indicates
orchard
location
significantly
impacts
followed
damage
type,
cultivar
differences
being
less
pronounced.
Partial
least-squares
discriminant
(PLS-DA)
models
achieve
predictive
accuracy
(99%)
type
(≈80%),
showing
highest
accuracy.
Correlation
matrices
reveal
relationships
between
metabolites
samples,
suggesting
potential
could
guide
assessment
mitigation
strategies.
Data
fusion
techniques
further
enhance
classification
performance,
predicting
underscoring
integrating
multiple
sets
assessment.
