Clustereventtaste2seas thescienceoftaste 18 11 2014

PARALLEL SESSION:

The science

measuring aroma, texture and colour

• The importance industry

Charlotte Boone Flanders

• Chemical-analytical aroma research for food industry

Jim Van Durme KU Leuven, technology campus Ghent

• The importance of visual appearances of food products: case

Hannelore De Maere - KU Leuven, technology campus Ghent

• Why rheologie is important!

Mohammed Foukani Groupe ISA

Charlotte Boone

MEASURING FLAVOUR

What is flavour?

• Complex set of properties

• Different senses involved

How do we measure it?

• Quantitative

• Qualitative

WHAT IS FLAVOUR?

Taste: soluble compounds detected by the tongue

WHAT IS FLAVOUR?

Taste: 5 (?) basic taste sensations

WHAT IS FLAVOUR?

Smell/Aroma: volatile compounds detected by the nose

WHAT IS FLAVOUR?

Smell/Aroma: Several thousands of volatile components, detected by +/- 400 different aroma receptors

WHAT IS FLAVOUR?

Trigeminal properties: (in)soluble compounds detected by trigeminal receptors in mouth

WHAT IS FLAVOUR?

Mouthfeel and texture: Structural and physical effects detected in the mouth

10

WHAT IS FLAVOUR?

Influenced by visual, auditory cues, and psychological effects

WHAT IS FLAVOUR?

Influenced by visual, auditory cues, and psychological effects

Tastes like white wine Tastes like red wine

HOW DO WE MEASURE IT?

Quantitative versus Qualitative

• Quantitative: puts a number on the intensity (or presence) of a certain trait

• Qualitative: states whether the product or certain aspects of it are appreciated (and to what degree)

Example: Assessing the sweetness of a product

• Quantitative: On a scale of 1-10, the sweetness of the product has a score of 8

• Qualitative: On a scale ranging from Definately not sweet enough to too sweet people scored too sweet scored

too sweet and 20% scored it about

HOW DO WE MEASURE IT?

Quantitative

• Using laboratory analyses (colour, texture, taste, aroma)

• Using people: trained panels

(6-12 panel members)

Qualitative

• Using people: consumer panels

(>60 consumers)

Chemical-analytical aroma research for food industry

DR. IR. JIM VAN DURME

Molecular odour chemistry

KU Leuven, Technology Campus Ghent

Sample preparation: Headspace

Direct headspace HS-SPME HS-SBSE

HS-SBSE-derivatisation

SDE

TDU

Detection Gas chromatography mass

spectrometry TIC SIM

MS-nose

Chemical-analytical Sensory evaluation

Tasting room

Research Unit Molecular Odor Chemistry

Kopi Luwak (Indonesia)

Thousand year egg (China)

Mouldy cheese (Belgium, France)

Flavour Research Science culture - individual

Extraction of volatiles

(partit ioning/sorption in mucus)

Human odor perception vs. chemical analysis

Extraction of volatiles

(partit ioning/sorption in mucus)

Separation

Detection of aroma compounds

(olfactory receptors)

Human odor perception vs. chemical analysis

Extraction of volatiles

(partit ioning/sorption in mucus)

Separation

Detection of aroma compounds

(olfactory receptors)

Data processing

Bulbus olfactorius brain

Human odor perception vs. chemical analysis

EXTRACTION OF VOLATILES

Static Headspace (SHS)

Dynamic Headspace (DHS) Purge and Trap (P&T) In-tube sorptive extraction (eg ITEX) Thermal extraction (TE)

Solid Phase Micro-Extraction (SPME) Hollow fiber liquid phase micro-extraction (HF-LPME)

Stir Bar Sorptive Extraction (SBSE) Headspace Sorptive Extraction (HSSE)

ANALYSIS OF VOLATILES METHODS FOR TRACE ENRICHMENT/EXTRACTION

ANALYSIS OF VOLATILES METHODS FOR TRACE ENRICHMENT/EXTRACTION

(micro) Liquid-Liquid Extraction (LLE) Single drop micro-extraction (SDME)

Cold liquid-solid extraction Ultrasonic extraction

Membrane Extraction Membrane extraction with solvent interface (MESI)

Steam Destillation Solvent Extraction (MASE) Likens-Nickerson Microwave assisted steam destillation

Simultaneous Steam Destillation (SDE)

Extraction of volatiles

K as

K fa

Solid-phase MicroExtraction

Extraction of volatiles

Headspace SPME In-liquid SPME

NOSE TONGUE

Stirbar sorption extraction (SBSE)

Extraction of volatiles

Dynamic headspace sampling

Extraction of volatiles

SEPARATION AND DETECTION

Extraction of volatiles

Separation

GC-MS vs. MS-nose

Detection (MS, FID, human senses…)

Separation (GC, HPLC)

Data processing (multivariate techniques: PCA, PLS)

Extraction of volatiles

Separation

GC-MS vs. MS-nose

Detection (MS, FID, human senses…)

Separation (GC, HPLC)

Data processing (multivariate techniques: PCA, PLS)

GC-MS

HS-SPME-GC-MS: examples Liquid smoke

0

1000000

2000000

3000000

4000000

5000000

6000000

5 10 15 20 25 30 35 40 45

Ab

un

da

nce

Time in minutes

Special H,1

Special H,2

Special H,3

Extraction of volatiles

Separation

GC-MS vs. MS-nose

Detection (MS, FID, human senses…)

Separation (GC, HPLC)

Data processing (multivariate techniques: PCA, PLS)

MS-nose

Figure 3D-Soft independent modeling of class analogy (SIMCA) plot (class projections) and principal component analysis (PCA) of the HS -SPME-MS-nose data, chocolate samples (n = 5)

Sensory evaluation GC-Olfactometry

Sensory evaluation GC-Olfactometry

CASE CASE: Healthy and tasty microalgae

Van Durme et al., 2013

Sensory evaluation Qualitative Desciptive Analysis

CASE: Healthy and tasty microalgae

HS-SPME-GC-MS

HS-SPME-GC-MS

HS-SPME-GC-MS

HS-SPME-GC-MS

Highly detailled information! - How different are the samples? - Which are the most important aroma compounds? - Correlation with sensory evaluations?

-

Odour Activity Value = Concentration / Odour Threshold Value

OAV = 390/5506 = 0,07

OAV = 21/0,16 = 131

Figure 3. Partial least squares regression (PLS2) correlation loadings plot (X-variables: OAV data; Y-variables: sensory

descriptors) of microalgae (Nanochloropsis, Botryococcus, Rhodomonas, Tetraselmis, Chlorella).

HS-SPME-GC-MS - PLS

[email protected] KU Leuven Technology Campus Ghent

Faculty of Industrial Engineering Technology | Department of Microbial and Molecular Systems (M2S) | Gebroeders De Smetstraat 1, B-9000 Gent | T +32 9 265 86 10

The importance of visual appearances of food products: case

Hannelore De Maere

Research Group for Technology and Quality of Animal Products

Faculty of Industrial Engineering Technology KU Leuven, Technology Campus Ghent

COLOUR

Colour defined in three dimensions:

Hue

Saturation

Lightness

Most important, e.g. sky

Most difficult to understand, e.g. purity, concentration

Black → white

COLOUR

Definitions:

Colour is electromagnetic radiation with a certain wavelength composition Physics

Colour is a property of chemical substances and depends on certain groups of atoms chromophores in the molecule

Chemistry

Colour is a nerve signal occuring in the eye in response to stimulation of rods and cones in the retina Biology

In general: Colour is the aspect of visual perception, allowing us to distinguish two similar objects

COLOUR

Description of colour:

colour

are based on visual perception of colour!

Ca. 500 000 hues

Ca. 25 000 industrial colours

Ca. 400 names

Zoom.nl Flexaverfshop.nl Garagepoortenantwerpen.be

Our vocabulary is limited and not precise → marketing

COLOUR

Pitfalls:

Personal.kent.edu; thebrain.mcgill.ca; www.psypress.co.uk

Influence form

Influence of background

Influence light source

Influence circumstances observer

COLOUR

These pitfalls are:

- Based on several laws of colour vision

- Described by Chevreul in 1839 on Simultaneous contrast

- Phenomena of interpretation

NOT of perception

APPEARANCE

Chromatic attributes

- Related to color-hue, saturation, purity

Geometric attributes

- Surface properties associated with the distribution of light from the object, such as gloss, haze or texture

STANDARDIZATION OBSERVER CONDITIONS

- Light sources

- Daylicht (D65 of D75)

- Incandescent 2856K

- Cool white Fluorescent 4200K

- Photometric conditions

- Illumination of 810-1880 Lux

- Geometric conditions

- Lighting overhead (0°)

- Viewing (45°) → observing colour, no gloss

- Background and surround

- Neutral Grey

- Uncluttered

Thing required to see colour:

1. Light source

2. Object

3. Observer

1. LIGHT SOURCE

Light source versus illuminant:

A light source is a physical emitter of radiation such as a

candle, a tungsten bulb or natural daylight

An illuminant is the spectral energy tabulated for each

wavelength of a black body at a given colour temperature

All light sources can be specified as an illuminant but not all

illuminants can be physically realized as a light source

Standardized by CIE (Commission Internationale de

l'Éclairage)

1. LIGHT SOURCE

Daylight Fluorescent Thungsten

2. OBJECT

An object partly reflects and partly absorbs light:

A green object absorbs mainly red light

→ reflects wavelengths from blue to yellow

• If an object absorbs all wavelengths < 600 nm

→ a red coloured object will be seen

3. OBSERVER

Trichromaticity of human perception:

Rod shaped receptors in the eye are responsible for night vision

Cone shaped receptors are responsible for daylight and colour

vision

There are three types of cone shaped receptors sensitive to red,

green and blue

→ Processing signals in the brains = interpretation of colour

(wavelength = physical data, colour = human interpretation)

3. OBSERVER

Human eye sensitivity:

Thing required to measure colour:

1. Light source

2. Specimen

3. spectrometer

COLOUR MEASUREMENT

Tristimulus colorimeter

Specrophotometer

MEASURING COLOUR WITH A TRISTIMULUS COLORIMETER

reflected light passes through

three glass filters

Detection beyond each filter

X, Y, Z values Taking into account the CIE illuminant and the

standard observer 2° of 10°

Standard observer

MEASURING COLOUR WITH A TRISTIMULUS COLORIMETER

Because X, Y, Z values are not easily understood in terms of object colour,

other colour scales have been developed to:

• Relate better of how we perceive colour

• Simplify understanding

• Improve communication of colour differences

• Be more linear throughout colour space

COLOUR SCALES

• Hunter L, a, b (1958)

→ 3-dimensional, cartesian, based on opponent colours

• CIELAB (1976): most complete colour model

→ standard to describe all colours visual for the human eye

• Independent of apparatus: same combination of L*, a* en b*, always

exactly the same colour

• Developed by CIE (Commission Internationale de l'Éclairage)

CIELAB COLOUR SPACE L*, A*, B* (1976)

CIELAB COLOUR SPACE L*, A*, B* (1976)

• L*- value: Lightness: 0 (black) tot 100 (white)

• a*- value: -60 (green) tot +60 (red)

• b*- value: -60 (blue) tot +60 (yellow)

CIELAB COLOUR SPACE L*, A*, B* (1976)

• L* (Lightness)

• Chroma (Saturation) = 𝑎 ∗ ² + 𝑏 ∗ ²

• Hue (colour) = arctan 𝑏∗

𝑎∗

European Union (EU) legislation requires most additives used in foods to be labelled clearly

in the list of ingredients, with their function, followed by either their name or E number.

An E number means that it has passed safety tests and has been approved by the

European Food Safety Authority.

additives

for

technological advantages negative connotation

ZINC PROTOPORPHYRIN IX FORMATION IN NITRITE-FREE DRY FERMENTED SAUSAGES

Positive balance Negative balance

Antioxidant properties

Antimicrobial properties

Colour formation

Specific aroma and taste

Direct toxicity (0 - 0.13 mg/kg body weight)

Indirect toxicity

(involvement in N - nitrosamines

formation)

Restriction in meat

products:

initial addition of 150 mg/kg

(Directive 2006/52/EC)

Interest:

How can the use of sodium nitrite be avoided

(without addition of other E numbers)? complex

Focus necessary

ZINC PROTOPORPHYRIN IX FORMATION IN NITRITE-FREE DRY FERMENTED SAUSAGES

Activity 1

Doctoral study

Formation of zinc protoporphyrin IX in relation to the colouring of

dry fermented meat products.

Promotor: Chris Michiels (KU Leuven)

Co-promotors: Hubert Paelinck (KU Leuven) and Sylvie Chollet (Groupe ISA)

ZINC PROTOPORPHYRIN IX FORMATION IN NITRITE-FREE DRY FERMENTED SAUSAGES

Ferrous protoporphyrin IX or heme (Fe(II)PPIX) (enclosed in

myoglobin) is responsible for the red colour in meat.

Nitrosoheme (NO-Fe(II)PPIX) – formed after addition of nitrite - is

responsible for the red colour in cured meat products.

Zinc protoporphyrin IX (Zn(II)PPIX) is able to form in nitrite-free, non

pasteurized meat products, with a red colour as result.

Only in dry cured hams!

NO

ZINC PROTOPORPHYRIN IX FORMATION IN NITRITE-FREE DRY FERMENTED SAUSAGES

Zinc protoporphyrin IX (Zn(II)PPIX) is able to form in nitrite-free, non

pasteurised meat products, with a red colour as result.

BUT

Reaction mechanisms are still uncertain

Influences of product- and process parameters

Investigation is still necessary to achieve formation of Zn(II)PPIX in dry cured

and/ or fermented meat products with a shorter production process.

Formation process needs time

ZINC PROTOPORPHYRIN IX FORMATION IN NITRITE-FREE DRY FERMENTED SAUSAGES

Experimental

dextrose 0.00%

day 0 day 21 month 2 month 6

day of production extensive drying

dextrose 0.25%

dextrose 0.50%

dextrose 0.75%

Fast screening method (Image analysis) and quantitative detection of zinc protoporphyrin IX (HPLC) - Nitrite-free dry fermented sausages with varying product parameter, pH

ZINC PROTOPORPHYRIN IX FORMATION IN DRY FERMENTED SAUSAGES

0,00% dextrose 0,25% dextrose 0,50% dextrose 0,75% dextrose

Experimental

dextrose 0.00%

day 0 day 21 month 2 month 6

day of production extensive drying

dextrose 0.25%

dextrose 0.50%

dextrose 0.75%

Fast screening method (Image analysis) and colour measurement (Miniscan EZ tristimulus colorimeter)

Nitrite-free dry fermented sausages with varying product parameter, pH

ZINC PROTOPORPHYRIN IX FORMATION IN DRY FERMENTED SAUSAGES

0,00% dextrose 0,25% dextrose 0,50% dextrose 0,75% dextrose

Colour measurement (Miniscan EZ tristimulus colorimeter) after an intensive drying period (day 129) - Dry fermented sausages with varying process parameter, addition of sodium nitrite

mean SD mean SD

53,05 1,41 55,14 1,84

16,12 1,35 8,86 1,52

11,81 0,73 15,16 2,35

19,47 1,26 17,69 1,62

38,46 6,23 58,88 6,83

Traditional product (with nitrite, low pH)

Innovative product (without nitrite, high pH)

L*

a*

b*

C

h

ZINC PROTOPORPHYRIN IX FORMATION IN NITRITE-FREE DRY FERMENTED SAUSAGES

colour?

ZINC PROTOPORPHYRIN IX FORMATION IN NITRITE-FREE DRY FERMENTED SAUSAGES

promising results

but

more investigation is still necessary to understand the effect of different product and process parameters on the formation of zinc protoporphyrin IX in dry cured

and/or fermented meat products, and their influence on colour formation.

Thank you for your attention Contact: [email protected]

WHY RHEOLOGY IS IMPORTANT !

M O H A M M E D F O U K A N I

I S A L I L L E

WHY RHEOLOGY IS IMPORTANT !

Rheology

Formulation

Processing

Structure Performance

Retro engineering

Raw material

During processing

Texture: creamy, crunchy, crispy

Rheology can be correlated with the sensory attributes to characterize the texture of the product

Rheology provides an important link between structure and performance of the product

WHAT IS RHEOLOGY ?

Stress

Rheology is the science of deformation and flow

Flow

Viscosity, spreadability, shear sensitivity

Viscosimety Oscillatory rheology

Deformation

Behaviour before flow, stability, Viscoelasticity

FLOW

n

k

Power Law model

k: consistancy (Pa.sn) n: Power-law index 0 < n < 1

)(fViscosity

M.FOUKANI Laboratoire Rhéologie

Mapping Profile

Thicker

More shear Thinning

Eau

Choc Choc Sauce

Miel Yoghurt

Syrup

Margarine

Mapping Profile can be used to optimize the performance of a product

Power-law index n

Co

nsi

sta

ncy

K

OSCILLATORY RHEOLOGY

Strain

Stress)(G Pa

Complex modulus

Stifness of material

Phase angle: Phase angle can be between 0° and 90°.

The higher the phase angle, the more viscous.

The lower the phase angle, the more elastic.

TEXTURE MAPPING

Complexe modulux G*

Phase angle

Mo

re r

igid

Less elastic

G* : stiffness under small deformations

Phase angle : viscous or elastic behavior associated

WHY RHEOLOGY IS IMPORTANT !

Scoopability

Coldness

Creaminess

Thikness, f irmess

regeneration

ICE CREAM

10 2

10 3

10 4

10 5

10 6

10 8

Pa

G'

G''

-20 -15 -10 -5 0 5 10 °C

Température T

G'

G''

G'

G''

1

2

3

Ice cream A

Ice cream B

« spoonability »

Coldness

Creaminess

ICE CREAM

1

Ice cream B

Ice cream A

10 2

10 3

10 4

10 5

10 6

10 8

Pa

G'

G''

-20 -15 -10 -5 0 5 10 °C

Temperature T

G'

G''

G'

G'' « spoonability »

ICE CREAM

Ice cream A

Ice cream B

10 2

10 3

10 4

10 5

10 6

10 8

Pa

G'

G''

-20 -15 -10 -5 0 5 10 °C Temperature T

G'

G''

G'

G''

2

Coldness

3

10 2

10 3

10 4

10 5

10 6

10 8

Pa

G'

G''

-20 -15 -10 -5 0 5 10 °C Temperature T

Ice cream A

G'

G''

Ice cream B

G'

G''

ICE CREAM

Creaminess

KETCHUP : YIELD STRESS

10 -2

10 -1

10 0

10 1

10 2

10 3

10 4

10 6

%

0.1 1 10 100 1,000 Pa

Stress

without texturing agent

with texturing agent

Yield stress without texturing agent

tau_0=13,5 Pa

Yield stress without texturing agent

tau_0=114 Pa

Strain

KETCHUP : THIXOTROPY 1

2

Oscillation Oscillation

rotation

CONCLUSION

Rheology is an important tool:

To compare products, formulations and processes To optimize the formulations

Viscosimetry tests can be used to describe and compare flow profiles of different

products

Oscillatory tests are a useful tool to compare textural properties of a material

Contact : [email protected]