Quinoa
has
high
nutritional
value
and
considered
as
health-promoting
food.
However,
the
main
primary
nutrient,
little
references
are
focus
on
characteristic
sugars
in
quinoa.
In
this
study,
three
colorful
quinoas
(WQ,
white
quinoa;
RQ,
red
BQ,
black
quinoa)
were
analyzed
based
metabolomics.
A
total
of
33
including
monosaccharaides
(21),
disaccharides
(9)
trisaccharides
(3)
identified,
25
reported
for
first
time.
D-talose
(9.49
mg/kg
BQ
～
45.98
RQ),
levoglucosan
(17.85
WQ
27.68
6-deoxy-D-glucose
(8.92
RQ
11.86
BQ)
gentiobiose
(8.70
15.82
RQ)
common
significant
(p<0.05)
differences
sugar
contents
presented
colored
quinoas.
Ribose,
mannose,
lyxose,
fructose,
xylose,
1-kestose
melibiose
respectively
showed
highest
content
RQ.
could
be
characterized
by
raffinose,
trehalose,
maltotriose,
galactose,
sorbose
D-arabitol.
Principal
component
analysis
(PCA)
was
an
effective
method
distinguishing
different
quinoa
samples
their
profiles,
cleared
well.
conclusion,
metabolomics
excellent
which
made
great
contribution
to
understand
overall
quality
Antioxidants,
Journal Year:
2023,
Volume and Issue:
12(7), P. 1453 - 1453
Published: July 19, 2023
The
demand
for
healthy
ready-to-eat
foods
like
snacks
is
increasing.
Physical
modification
of
vegetal
food
matrices
through
extrusion
generates
significant
changes
in
the
chemical
composition
final
product.
There
a
great
variety
that
can
be
used
extrusion,
most
them
being
based
on
cereals,
legumes,
fruits,
vegetables,
or
seeds.
aim
this
review
was
to
summarize
main
effects
process
bioactive
compounds
content,
namely
phenolics,
terpenes,
vitamins,
minerals,
and
fibers
mixes,
as
well
their
biological
activity.
literature
reported
contradictory
results
regarding
after
mainly
due
differences
processing
conditions,
composition,
physicochemical
properties,
nutritional
value
extruded
material
quantification
methods.
thermolabile
phenolics
vitamins
were
negatively
affected
by
while
fiber
content
proved
enhanced.
Further
research
needed
interactions
between
components
during
more
detailed
analysis
impact
terpenes
since
there
are
few
papers
dealing
with
aspect.
Agronomy,
Journal Year:
2024,
Volume and Issue:
14(4), P. 852 - 852
Published: April 19, 2024
The
research
conducted
at
the
Shanxi
Agricultural
University’s
Quinoa
Experimental
Model
Base
in
Jinzhong,
Province,
aimed
to
assess
agronomic
traits
and
their
correlation
with
yield
across
32
quinoa
varieties.
Three
distinct
categories
emerged:
low
(≤1500
kg
ha−1),
middle
(1500–2500
kg−1),
high
(>2500
ha−1).
High-yielding
varieties
demonstrated
notable
characteristics,
including
decreased
plant
height
increased
leaf
area
per
maturity
compared
low-
middle-yielding
Moreover,
decline
root
from
flowering
was
less
pronounced
high-yielding
had
a
higher
hardness
of
stem
base
by
12–13.7%
6.3–11.5%
medium-
low-yield
Furthermore,
indicated
improvements
dry
matter
accumulation,
effective
branch
number,
main
ear
length
1000-grain
weight.
Correlation
analysis
highlighted
significant
relationships
between
grain
weight,
yield,
post-flowering
senescence,
characteristics.
Structural
equation
model
revealed
negative
impact
certain
on
weight
suggesting
importance
determining
productivity.
Notably,
exhibited
conducive
shorter
height,
slower
enhanced
resilience.
These
findings
showed
that
understanding
relationship
potential
is
crucial
for
optimizing
production
promoting
sustainable
development
this
essential
crop.
Food Science & Nutrition,
Journal Year:
2024,
Volume and Issue:
12(7), P. 4810 - 4818
Published: May 6, 2024
Abstract
Quinoa
is
a
full‐nutrition
food;
however,
its
poor
flavor
and
small
size
make
it
not
the
best
food
option
for
direct
consumption.
In
this
study,
quinoa
snack
(QS,
cake)
was
developed,
aroma
profile
of
products
improved
by
adding
jujube
fruit
powder
(made
from
dried
fruits,
5%
to
30%).
Gas
chromatography
mass
spectrum
(GC–MS)
combined
with
electronic
nose
(e‐nose)
applied
characterizing
profiles
QS
samples.
Results
showed
total
26
compounds
were
identified
in
samples
GC–MS,
3‐methylbutanol
(from
1525
μg/kg
QS‐30
3487
QS‐0),
ethanol
1126
QS‐0
3581
QS‐30),
hexanal
125.6
984.1
acetaldehyde
531.9
191.1
QS‐0)
common.
The
e‐nose
response
W1S
(sensitive
methane,
17.50
93.85
QS‐30)
W1W
sulfur‐organic
e‐nose,
15.57
39.50
significantly
higher,
significant
differences
presented
among
conclusion,
sample
(
p
<
.05)
enhanced
addition
powder,
highest
content
(30%)
strongest
profile.
Moreover,
different
additions
powders
could
be
well
distinguished
principal
component
analysis
(PCA),
combination
GC–MS
effective
volatile
