lc-ms/ms analysis of marker compounds for sensory quality ...€¦ · 2.0 0.1 13.2 20.7 14.8...

© 2016 Technische Universität München

LC-MS/MS analysis of marker

compounds for sensory quality

and authenticity of fruit juices

Andreas Dunkel

SCIEX Innovation Day, Analytica, 160511

© 2016 Technische Universität München

simplified sample prep.

inexpensive

high robustness

high reproducibility

library creation

automation possible

combinatorial odor/taste

codes required

instrumental

Mass spectrometry

(SENSOMICS)

direct sample analysis

expensive & time consuming

subjective vs. objective

sensory fatigue

volatility of experience

personnel fluctuation

skilled personnel required

in vivo

Human sensory analysis

(trained panelists)

massive sample prep.

multiple assays needed

low robustness

prone to interferences

library creation

crowded IP landscape

skilled personnel required

in vitro

Cell-based or bioelectronic

taste receptor assays

Tools for aroma/taste assessment

© 2016 Technische Universität München

Direct juice (DJ) vs. juice from concentrate (CJ)

• European market: predominantly apple

and orange juices from concentrate

• Insufficient reconstitution affects the quality of

CJ, consumer protection organizations

increasingly report a decline in sensory quality

• Technological challenge to achieve organoleptic/

analytical equivalence of DJ and CJ as required

by legal regulations (Fruchtsaftverordnung)

• Current situation: only verification of the

„analytical similarity“ insufficient verification

of the sensory quality of the reconstituted juice

• Aims: improvement of the sensory quality of

apple and orange juices from concentrate,

quantification of the crucial sensory active

compounds, development of objective parameters

for evaluation of sensory quality and simplified

analytical methods

© 2016 Technische Universität München

Which molecules hit our receptor repertoire during food consumption?

© 2016 Technische Universität München

HILIC-MS/MS(ESI+)-SIDA Tosoh TSK-gel Amide 80,

150 x 2.0 mm, 3 µm

ZIC-pHILIC-MS/MS(ESI-)-SIDA Sequant polymeric ZIC-pHILIC

150 x 4.6 mm i.d., 5 µm

LC-MS/MS-SIDA quantitation of “generalist“ tastants

RP18-HPLC MS/MS(ESI-)-SIDA Phenomenex Synergi Hydro-RP

4µm, 80Å, 150 x 2.0 mm

© 2016 Technische Universität München

Isolation of sweet taste modulating molecules from apples

• Recombinant of basic tastants from apple juice shows an non-characteristic sweet-sour profile

Prep. RP18-HPLC – Taste Dilution Analysis

EtOAc extract induces

change in sweet/sour

profile (α < 0.05)

Fraction VIII of EtOAc

extract induces change in

sweet/sour profile (α < 0.05)

Prep. PheHex-HPLC of subfraction VIII

© 2016 Technische Universität München

Structures and taste thresholds of ursane triterpenoids

H3C(25)

HC(1)

H3C(29)

HC(18)

HC(20)

ROESY, 500 MHz, d3-MeOH

euscaphic acid

(25 µmol/L)

corosolic acid

(13.2 µmol/L)

ursolic acid

(14.8 µmol/L)

annurconic acid

(20.7 µmol/L)

annurcoic acid

(0.1 µmol/L)

• Structure elucidation of sweet taste modulating ursane

triterpenoids by means of 1D/2D-NMR and MS experiments

© 2016 Technische Universität München

LC-MS/MSMRM quantitation of ursane triterpenoids

0 4 8 12 16 20 24 28 time [min]

Inte

nsity, cp

s

recovery expt. in recombinant

compound recovery [%]

euscaphic acid 97.6 ± 0.3

annurcoic acid 100.58 ± 0.04

corosolic acid 108.7 ± 2.5

annurconic acid 105.7 ± 0.8

ursolic acid 108.9 ± 1.2

5500 QTrap

Ekspert microLC 200

• Application of micro-UHPLC enables direct quantitation without sample workup

Stationary phase: Sciex ChromXP C18-AQ (3µm, 150 mm x 0.3 mm, 120Å)

Mobile phase: H2O/ACN (1%FA each)

Sample volume: 1 µL

© 2016 Technische Universität München

Annurcoic acid

Corosolic acid

Annurconic acid

Ursolic acid

Euscaphic acid

1.9

0.6

0.6

0.5

2.0

0.1

13.2

20.7

14.8

>25.0

21.0

< 0.1

< 0.1

< 0.1

<0.1

LC-MS/MSMRM quantitation of ursane triterpenoids

0 4 8 12 16 20 24 28 time [min]

Inte

nsity, cp

s

recovery expt. in recombinant

compound recovery [%]

euscaphic acid 97.6 ± 0.3

annurcoic acid 100.58 ± 0.04

corosolic acid 108.7 ± 2.5

annurconic acid 105.7 ± 0.8

ursolic acid 108.9 ± 1.2

5500 QTrap

Ekspert microLC 200

sweet

modulating

Tastant Conc [µmol/L] Threshold [µmol/L] DoT

• Application of micro-UHPLC enables direct quantitation without sample workup

© 2016 Technische Universität München

aspartic acid K+ phlorizin quercitrin annurcoic acid

Direct juice (DJ) vs. juice from concentrate (CJ)

Direct juice

Juice from concentrate

© 2016 Technische Universität München

Taste active compounds in orange juice

minerals polyphenols carbohydrates organic acids amino acids

limonoids and

limonoid glucosides

polymethoxylated

flavones

O

O

O

O

O

O

O

O

Limonin

Glabasnia (2008)

9 µmol/L (bitter)

19 µmol/L (astr.)

3,5,6,7,3´,4´-HMF

150 µmol/L (bitter)

31 µmol/L (astr.)

5,6,7,4´-TMF Nomilin-17-β-D-glcp

4 µmol/L (bitter) > 700 µmol/L (bitter)

© 2016 Technische Universität München

Quantitation method for the bitter principles of orange juices

• 2 Limonoids, 6 limonoid glycosides, and 9 polymethoxylated flavones could be detected in orange

juice samples as well as process steps

• Commercially available internal standards (e.g. 3,5,7,3‘,4‘-pentamethoxyflavone for PMF‘s)

• Direct injection of samples after filtration)

t [min]

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25

Micro-HPLC-MS/MS: Sciex QTRAP 5500 + Ekspert 200

Stationary phase: Phenomenex Synergi Fusion-RP (4µm, 50 mm x 0.3 mm, 80Å)

Mobile phase: H2O/ACN (0.1%FA each)

Sample volume: 1 µL

Multivariate analysis of commercial orange juices (german market)

© 2016 Technische Universität München

−4

0

4

8

−10 −5 0 5Comp.1

Com

p.2

• Score plot Partial least squares – discriminant analyisis

(non-linear iterative partial least squares algorithm, leave-one-out cross validation,

unit variance scaled

Direct juice (cold storage)

Direct juice

Juice from concentrate

© 2012 Technische Universität München

Modeling of orange juice bitter taste

sugarsterpenesPMFsterpenesPMFs *Bitter taste

intensity =

Model experiments

Variation of sugar content Variation of sugar content

Va

riation o

f P

MF

conte

nt

Varia

tion o

f lim

onoid

conte

nt

© 2012 Technische Universität München

Modeling of orange juice bitter taste – „Calibration“

56

78

9

10

11

0

1

2

3

4

5

6

7

1,4

1,2

1,00,8

0,60,4

0,2

Correlation between bitterness and concentration of sugars (PMFs konst. 1.1 mg/100 g)

bitte

r in

tensity

Concentra

tion o

f Lim

onoids [m

g/100 g

]

Concentration of sugars [g/100 g]

0

0,8750

1,750

2,625

3,500

4,375

5,250

6,125

7,000

© 2012 Technische Universität München

Modeling of orange juice bitter taste

0 1 2 3 4 5

0

1

2

3

4

5

estimated bitter taste intensity

bitte

r ta

ste

inte

nsity

Calibration

R2 = 0.98

Commercial Juice Samples

0

1

2

3

4

5

0 1 2 3 4 5

bitte

r ta

ste

inte

nsity

estimated bitter taste intensity

© 2016 Technische Universität München

Pushing limits in controlling “food quality“ based on profound

scientific knowledge

No food quality without mass spectrometry!

© 2014 Technische Universität München

Many thanks!

© 2016 Technische Universität München