APPLICATION NOTE

WITec GmbH, Lise-Meitner-Str. 6, 89081 Ulm, Germany
Tel. +49 (0) 731 140 700, Fax +49 (0) 731 140 70 200
info@WITec.de, www.WITec.de

Food Analysis with
Confocal Raman Microscopy

Confocal Raman microscopy is a
powerful tool for visualizing the chemical composition of heterogeneous
samples on the sub-micrometer scale.
This application note demonstrates
the utility of Raman imaging forcharacterizing various food samples
such as honey, chocolate and fatspreads, leading to a comprehensive
understanding of the products andthe production processes.

application noteLise-Meitner-Str. 6 • D-89081 Ulm, Germany
Tel. +49 (0) 731 140 700 • Fax. +49 (0) 731 140 70200
www.witec.de • info@witec.de

The Raman principle

The Raman effect is based on the inelastic
scattering of light by the molecules ofgaseous, liquid or solid materials. Theinteraction of a molecule with photons
causes vibrations of its chemical bonds,
leading to specific energy shifts in thescattered light. Thus, any given chemicalcompound produces a particular Raman
spectrum when excited and can be easily
identified by this individual “fingerprint.”
Raman spectroscopy is a well-established,label-free and non-destructive method foranalyzing the molecular composition of asample.

No need for compromises

Raman imaging

In Raman imaging, a confocal microscopeis combined with a spectrometer anda Raman spectrum is recorded at every
image pixel. The resulting Raman image
visualizes the distribution of the sample’scompounds. Due to the high confocality ofWITec Raman systems, volume scans and3D images can also be generated.

The Raman effect is extremely weak, soevery Raman photon is important forimaging. Therefore WITec Raman imaging
systems combine an exceptionallysensitive confocal microscope with anultra-high throughput spectrometer(UHTS). Precise adjustment of all opticaland mechanical elements guarantees thehighest resolution, outstanding speed andextraordinary sensitivity - simultaneously!
This optimization allows the detectionof Raman signals of even weak Raman
scatterers and extremely low material
concentrations or volumes with thelowest excitation energy levels. This isan unrivaled advantage of WITec systems.

Resolution

Lateral resolution is physicallylimited to ~200 nm, dependingon the wavelength of theincident light.

Speed

The more sensitive a system is, the shorter
the acquisition time for a single spectrum.
WITec’s Ultrafast Raman Imaging reduces
acquisition times for single Raman spectra
down to well below 1 ms.

Sensitivity

A high confocality increases the signal-to-noise ratio by reducing
the background. With the UHTS Series, WITec developed lens-based,wavelength-optimized spectrometers with a spectral resolution
down to 0.1 cm-1 relative wavenumbers.

application noteLise-Meitner-Str. 6 • D-89081 Ulm, Germany
Tel. +49 (0) 731 140 700 • Fax. +49 (0) 731 140 70200
www.witec.de • info@witec.de

Food analysis with confocal Raman microscopy
Properties of food such as flavor andtexture critically depend on the distribution and microstructure of its various
ingredients, including additives such as
emulsifiers, stabilizers and thickeners.
The food industry therefore requires
powerful analytical tools for optimizing
products and ensuring their compliancewith quality standards. Raman microscopy
is ideally suited for this task, as it cancharacterize the chemical composition ofheterogeneous samples on the sub-micrometer scale [1-6] and analyze particles, forexample in beverages [7].

Figure 1: Raman image of squashed banana
pulp overlaid on a white-light image. The main
components are starch (green), carotenoids (red)and water (blue). Raman image parameters:
400 x 300 μm2, 1200 x 900 pixels, integrationtime: 2 ms per spectrum.

Raman imaging investigation of natural food products
Highly sensitive confocal microscopes
enable fast and high-resolution Raman
imaging simultaneously. A Raman imageof banana pulp consisting of more than
one million Raman spectra was acquiredin less than 45 minutes (Fig. 1). It visualizes
the distribution of starch grains andcarotenoids in a water matrix.
Confocal Raman imaging can alsovisualize the distribution of compounds in
3D and characterize crystal properties. A
3D Raman image of a honey droplet wasgenerated from 50 individual 2D Raman
images acquired at successive planes
along the z-axis (Fig. 2). It shows a pollen
grain embedded in the liquid honey phase.
Three different crystalline honey phases
are also differentiated.
Figure 2: 3D Raman image of a honey droplet. The liquid honey phase (yellow) surrounds apollen grain (green) and several crystalline honey phases (red, blue, cyan). Image parameters:
50 x 50 x 50 μm3; 150 x 150 x 50 pixels; 2 ms per spectrum.

application noteLise-Meitner-Str. 6 • D-89081 Ulm, Germany
Tel. +49 (0) 731 140 700 • Fax. +49 (0) 731 140 70200
www.witec.de • info@witec.de

Characterizing emulsions and fat-spreads
Fat-spreads such as butter or margarine
are water-in-oil emulsions. The microstructure of fat-spreads determines properties
such as suppleness, texture, stability andspreadability. These properties depend on
the fat crystal network at the water/oilinterface and on the emulsifier and they
are strongly influenced by the production
process. Therefore, manufacturers ofemulsions and fat-spreads analyze theirproducts in detail to understand therelationships between their composition,production process, structure and function.
For this purpose, confocal Raman imaging
is a very valuable technique [1].

AFig. 3 presents a confocal Raman imageof an emulsion containing fat, water andthe emulsifier E476 polyglycerol polyricin­
oleate (PGPR). This emulsifier decreases
the friction between solid particles, forexample, in chocolate. A Raman imageof the emulsion shows the distributionof its ingredients (Fig. 3). The emulsifier
PGPR clearly accumulates at the interface
between the water droplets and the fattymatrix.

A study from the Dutch company Unileverdescribes hyperspectral data analysis ofRaman images of fat spreads including
data-pre-processing and multivariate
curve resolution (MCR) [1]. ConfocalRaman imaging could not only locate
the molecular compounds in fat spreads,
but also relate their microstructure andproduction processes. The results showthat water forms droplets in a continuumof sunflower oil, stabilized at the interface
by an emulsifier (monoglycerides) andlipids in the crystalline phase (Fig. 4). The
crystalline lipids (solid fat) are also foundin the continuous phase of the emulsion,
forming a network between the different

B

Figure 3: Confocal Raman study of a foodemulsion.

A: Raman image of the emulsion, color-codedaccording to the spectra in B: emulsifier PGPR(yellow), water (blue) and fatty matrix (red,green).

B: Raman spectra of the emulsion’s components.

water droplets. The rightmost image
shows the competition/co-crystallization
between the solid fat and the emulsifier
at the droplet interface. The authors of
the study conclude that, “This method canbe applied to a wide range of different
food emulsions such as butter, margarine,
mayonnaise and salad dressings.” [1]Figure 4: Raman images of a fat-spread. From left to right, the concentrations of sunflower oil, water, solid fat and emulsifier are shown in individual
images, with the highest concentrations in red and the lowest in dark blue. In the rightmost image, the Raman signals from solid fat and emulsifier areoverlaid. Image parameters: 20 x 20 μm2, 86 x 86 pixels.

Images courtesy of Gerard van Dalen and colleagues, Unilever, Vlaardingen, The Netherlandsapplication noteLise-Meitner-Str. 6 • D-89081 Ulm, Germany
Tel. +49 (0) 731 140 700 • Fax. +49 (0) 731 140 70200
www.witec.de • info@witec.deIn a related example, Raman imaging isused to compare two butter products inorder to investigate the chemical differences underlying their different spreadability.
Individual 3D Raman images of normalbutter and a more spreadable productwere generated by combining 2D images
acquired at successive focal planes along
the z-axis (Fig. 5A, B). Both products clearly
are water-in-oil emulsions as expected. The
water content is higher in the spreadable
butter and the water forms larger droplets
than in the more solid fat-spread. Chemical differences in the fatty phases become
evident by comparing their Raman spectra(Fig. 5C). Each product is shown to containdifferent types of fat and oil. The consistency of fats is influenced by the amountof unsaturated fatty acids, among otherparameters. The unsaturation level of fats
can be compared by the ratio of the C=C
stretching mode around 1655 cm-1 and theCH2 scissoring mode around 1444 cm-1 [8],which is higher for the spreadable butter
than for the normal one (Fig. 5C). This
indicates a higher amount of unsaturated
fatty acids, which contributes to theimproved spreadability.

AB

Figure 5: Comparison of two butter products.

CA, B: 3D Raman imaging of conventional (A)and spreadable butter (B). Blue: water phase; red, green: fat phases. Image parameters:
12 x 12 x 4 µm3 generated from 6 images with
200 x 200 pixels each (A), 12 x 12 x 3.3 µm3generated from 5 images with 200 x 200 pixels
each (B).
C: Raman spectra of the fatty phases (red:normal butter, green: spreadable butter) andzoom-in.

Fat-spreads with a high amount ofunsaturated amino acids and a reduced fat
content are also considered healthier thanconventional butter.

Confocal Raman imaging evaluation of chocolate
AB

Figure 6: Raman imaging of white chocolate.

A Raman image of white chocolate clearly reveals a distinct phase separation, withsucrose and additive particles embedded in a fatty matrix (Fig. 6). The sizes of the sucrose
particles vary between 0.65 µm and 10 μm.

A: Raman image of white chocolate, color-coded
according to the spectra in B: sucrose (blue), fat(green) and excipients (red).
B: Raman spectra of the chocolate’s ingredients.

application noteLise-Meitner-Str. 6 • D-89081 Ulm, Germany
Tel. +49 (0) 731 140 700 • Fax. +49 (0) 731 140 70200
www.witec.de • info@witec.de

Topographic Raman imaging with TrueSurfaceTM
WITec’s TrueSurface™ technology enables
topographic Raman imaging, a correlativetechnique that records a Raman image
and the surface topography simultaneously and compensates for height differences
during the measurement. Thus, Raman
spectra are acquired from precisely along
the surface, or at a set, user-defined distance above or below it. Roughly textured,
inclined or irregularly-shaped samples arereliably kept in focus during Raman measurements, even for large-area scans andduring long measurements. The resulting
topographic Raman image correlates thedistribution of a sample’s chemical compounds with its structural features.
TrueSurface’s capabilities are demonstrated on a sugar bar in the following application. Seven components were identified bytheir Raman spectra and their distribution
is visualized on a very large, rough surface
and even along the imprinted text (Fig. 7).

AB
Figure 7: Topographic Raman imaging of asugar bar.

A: The topographic Raman image displays thedistribution of seven chemical components (B)on the rough surface of a sugar bar, even along
the imprinted text.
B: Raman spectra of the seven components.

AThe second example investigates thefrosting on a gingerbread cookie. The distribution of the frosting’s components on
the cookie’s uneven surface is visualized ina topographic Raman image (Fig. 8A). As
expected, the frosting consists of different
sugars and polysaccharides (Fig. 8B).

B

Figure 8: Topographic Raman imaging of frosted gingerbread.

A: Raman image overlaid on the surface topography. The frosting consisted of different sugars (redand green) and polysaccharides (blue and yellow).
B: Raman spectra of the frosting’s components.

application noteLise-Meitner-Str. 6 • D-89081 Ulm, Germany
Tel. +49 (0) 731 140 700 • Fax. +49 (0) 731 140 70200
www.witec.de • info@witec.de

Raman analysis of particulate baking ingredients
Many ingredients for baking and cooking
are particulate, for example flour, sugar,salt, baking powder, semolina, starch andmany spices, and their size and distribution influence the macroscopic properties offood products. In drinks such as beer, theanalysis of haze particles is an importanttask [7]. Comprehensive particle analyses
are thus relevant for research, development and quality control in the food anddrink industries. Apart from characterizing
particulate products, the detection ofmicroplastic particles is important as
microplastics are becoming increasingly
prevalent and their potentially harmful
effects on humans and animals continue
to be investigated [9].

Here we demonstrate particle analysis
with Raman spectroscopy using analpha300 Raman microscope equippedwith WITec’s particle analysis software,
ParticleScout. For this purpose, a mixtureof typical particulate baking ingredientswas spread on a cover slide and whitelight images were acquired at different
sample positions. The dark-field imageof one area is shown in Fig. 9A. Raman
spectra were recorded automatically forthe particles in all images and identified
using the TrueMatch integrated databasemanagement software. Fig. 9B shows thesame sample area as Fig. 9A, but with theanalyzed particles color-coded according totheir chemical identities. As the differentABparticle types have different average sizes,
their abundance is represented by theirarea fraction in Fig. 9C. Starch and smaller
oligo- and polysaccharides, which are themain components of flour, account for two
thirds of the mixture. Sugar and vanillasugar represent about 15% and baking
powder 5%. The remaining 5% include, forexample, some proteins. More detailed
analyses of the particles’ shapes andsizes would of course be possible after
measuring a more statistically significant
number of particles. Further examples
for particle characterization withParticleScout and Raman microscopy canbe found in the WITec Application Note
about particle analysis [10].

References[1] G. van Dalen et al. (2017) Raman hyperspectral
imaging and analysis of fat spreads, J. Raman
Spectrosc. 48: 1075 – 1084. DOI: 10.1002/jrs.5171[2] E.M. Both et al. (2018) Morphology development
during single droplet drying of mixed component
formulations and milk, Food Res. Int. 109: 448 – 454.
DOI: 10.1016/j.foodres.2018.04.043[3] E. Nickless and S.E. Holroyd (2020) Raman imaging
of protein in a model cheese system, J. Spectr. Imaging
9: a9. DOI: 10.1255/jsi.2020.a9[4] G.P.S. Smith et al. (2017) Raman imaging processedcheese and its components, J. Raman Spectrosc. 48:
374 – 383. DOI: 10.1002/jrs.5054

Figure 9: Particle analysis with Raman spectroscopy in a mixture of baking ingredients.
A: Dark-field image of the particles in a mixtureof typical baking ingredients.

B: The particles located in A were color-coded according to their Raman spectra: starch (yellow),polysaccharides (orange), sucrose (green), vanillasugar (blue), baking powder (cyan), others (grey).
Particles at the picture edges were not analyzed.
C: The components’ area fractions. In total, 139particles were identified.

C[5] J. Huen et al. (2014) Confocal Raman microscopy offrozen bread dough, J. Cereal Sci. 60: 555 – 560.
DOI: 10.1016/j.jcs.2014.07.012[6] I.A. Larmour et al. (2010) Raman microspectroscopy mapping of chocolate, API Conf. Proc. 1267:758 – 759. DOI: 10.1063/1.3482793[7] E.-M. Kahle et al. (2020) Identification anddifferentiation of haze substances using Raman
microspectroscopy. J. Inst. Brew. 126: 362 – 370.
DOI: 10.1002/jib.627[8] K. Czamara et al. (2015) Raman spectroscopy oflipids: a review, J. Raman Spectrosc. 46: 4 – 20.
DOI: 10.1002/jrs.4607[9] N.P. Ivleva et al. (2017) Microplastic in AquaticEcosystems, Angew. Chem. Int. Ed. 56: 1720 – 1739.
DOI: 10.1002/anie.201606957[10] WITec Application Note “ParticleScout forAutomated Confocal Raman Imaging Analysis ofMicroparticles” www.witec.de/assets/Literature/Files/WITec-AppNote-ParticleScout.pdf

WITec Microscope Seriesalpha300 S: Scanning
Near-field Optical Microscopealpha300 A:
Atomic Force Microscopealpha300 R:
Confocal Raman Microscopealpha300 apyron: AutomatedConfocal Raman Microscope

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Phone +49 (0) 731 140700
Fax +49 (0) 731 14070200
info@witec.de
www.witec.de

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alpha300 Ri: Inverted
Confocal Raman Microscope

RISE: Raman Imaging –Scanning Electron Microscopealpha300 access: Confocal
Micro-Raman System

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