The Influence of Different Processing Stages on Particle Size, Microstructure, and Appearance of Dark Chocolate

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The Influence of Different Processing Stageson Particle Size, Microstructure, and Appearanceof Dark ChocolateVirginia Glicerina, Federica Balestra, Marco Dalla Rosa, Bjorn Bergenhstal, Eva Tornberg, and Santina Romani

Abstract: The effect of different process stages on microstructural and visual properties of dark chocolate was studied.Samples were obtained at each phase of the manufacture process: mixing, prerefining, refining, conching, and tempering.A laser light diffraction technique and environmental scanning electron microscopy (ESEM) were used to study theparticle size distribution (PSD) and to analyze modifications in the network structure. Moreover, colorimetric analyses(L∗, h°, and C∗) were performed on all samples. Each stage influenced in stronger way the microstructural characteristicof products and above all the PSD. Sauter diameter (D [3.2]) decreased from 5.44 μm of mixed chocolate sample to3.83 μm, of the refined one. ESEM analysis also revealed wide variations in the network structure of samples during theprocess, with an increase of the aggregation and contact point between particles from mixing to refining stage. Samplesobtained from the conching and tempering were characterized by small PS, and a less dense aggregate structure. Fromcolor results, samples with the finest particles, having larger specific surface area and the smallest diameter, appearedlighter and more saturated than those with coarse particles.

Keywords: appearance, chocolate, ESEM, manufacture stages, microstructure, particle size distribution

Practical Application: Final quality of food dispersions is affected by network and particles characteristics. The deepknowledge of the influence of single processing stage on chocolate microstructural properties is useful in order to improveor modify final product characteristics. ESEM and laser diffraction are suitable techniques to study changes in chocolatemicrostructure.

IntroductionDark chocolate can be defined as a concentrated suspension

made up of solid particles (sugar and ground cocoa particles) dis-persed in a Newtonian fluid, generally cocoa butter (Afoakwa andothers 2008). Quality and stability of final products are affectedby a number of factors, such as particle size (PS), particle sizedistribution (PSD), and interaction between them and are strictlyrelated to the raw materials but also to the manufacture process(Servais and others 2002; Granger and others 2005; Sato and oth-ers 2009; Baldino and others 2010). The physicochemical andmicrostructural properties of chocolate depend on many factorsbesides the ingredients and their proportions. The different processsteps (mixing, prerefining, refining, conching, and tempering) ofchocolate manufacture and the different adopted process param-eters can affect chocolate properties that, in turn, determine thebehavior and the characteristics of the final product. An effec-tive control of the technological parameters is required in orderto achieve a constant and desirable quality of the final product(Muller-Fischer and others 2005; Baixauli and others 2007). The

MS 20131759 Submitted 11/26/2013, Accepted 4/19/2014. Authors Glice-rina, Balestra, and Rosa are with Interdepartmental Centre for Agri-Food Indus-trial Research, Alma Mater Studiorum, Univ. of Bologna, Piazza Goidanich, 60,Cesena, Italy. Author Romani is with Interdepartmental Centre for Agri-Food In-dustrial Research and with Dept. of Agri -Food Science & Technologies, AlmaMater Studiorum, Univ. of Bologna, Piazza Goidanich, 60, Cesena, Italy. Au-thors Bergensthal and Tornberg are with Dept. of Food Technology, Engineering andNutrition, Lund Univ., Lund, Sweden. Direct inquiries to author Glicerina (E-mail:[email protected]).

processing of foods and in particular of dark chocolate bringsseveral changes in their microstructure. During chocolate man-ufacturing, mixtures of sugar, cocoa, and fat are heated, cooled,pressurized, and refined (Beckett 2000). These steps not only affectPS reduction, but also break agglomerates and distribute lipid andlecithin-coated particles through the continuous phase, modifyingthe microstructure of final chocolate (Afoakwa and others 2009).The interactions between the suspended particles and the contin-uous phase provide information about the existing network andconsequently can be associated with the properties and character-istics of the dispersions (Sato and others 2009). Since macroscopicproperties of foods, such as the appearance attributes and color, arestrongly determined by the microstructure of the food material,evaluation of the microstructure of food and its components isnecessary for understanding its macroscopic properties (Aguileraand Stanley 1999). PS values of chocolate are influenced by its for-mulation, and in particular as known by literature (Awua 2002),optimum PS for dark chocolate should be lower than 35 μm ofdiameter.

Environmental scanning electron microscopy (ESEM) is one ofthe most suitable techniques used to investigate microstructure offoods and to highlight the changes in the different structures ob-tained during the manufacturing process (Kalab and others 1996).ESEM, in fact, is a technique producing high-resolution imagesof chocolate specimen due to the way the image is obtained;ESEM images have a characteristic 3-dimensional appearance andlet to investigate the macroscopic properties of a sample (Dahlen-borg and others 2010). Laser diffraction analytical method is alsoa very spread technique used for PS analysis, based on the laser

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Microstructure of dark chocolate . . .

light scattered by particles. This method has the advantage of highspeed, good reliability, and high reproducibility (Ma and others2001).

Afoakwa and others (2008, 2009) used this technique and ob-tained good results in order to study some PSD aspects of darkchocolate.

The appearance of chocolate, a macroscopic property, sum-marized as gloss, lightness, shininess, and translucency, be-comes a key attribute in customer choice and acceptability offinal product (Beckett 2003; Whitefield 2005; Briones and oth-ers 2006). These color parameters are psychophysical phenomenaassociated with the way in which light is reflected, absorbed, andscattered by a surface. In general, the color characteristics can benatural in origin, or the result of manufacturing process (Saluenaand Gamasa 2012). In the case of dark chocolate, because of thecomplex matrix, appearance is strictly dependent on the processstages and mostly related with the PSD.

To our knowledge, no papers are available about the influence ofsingle-process steps on dark chocolate microstructural and appear-ance properties. Most literature (Servais and others 2004; Afoakwaand others 2008, 2009; Baldino and others 2010; Efraim and oth-ers 2011) has focused on the study of these characteristics after thefinal tempering process step.

In our opinion, a deep knowledge of the influence of sin-gle processing stage (mixing, prerefining, refining, conching, andtempering) on structural chocolate properties could be very usefuland is a starting point if it is necessary to improve or modify finalproduct characteristics.

For this purpose, in the present work, the microstructural prop-erties of dark chocolate were evaluated after each stage of themanufacturing process.

Materials and Methods

MaterialsDark chocolate samples were produced in an Italian confec-

tionery factory using an industrial plant (Buhler, Malmo, Sweden)provided of mixer, prerefiner, refiner, conching, and temperingmachine, equipped to produce 6000 kg of chocolate at everyproduction cycle. Dark chocolate production was made up by dif-ferent steps as shown in detailed way in Figure 1. The formulationemployed for the recipe was cocoa liquor (53%), sugar (39.52%),cocoa butter (7% added during the conching stage), soy lecithin(0.3%), sodium carbonate (0.15%), and vanilla extract (0.03%).Experimental samples were taken after each production phase:mixing (A), prerefining (B), refining (C), conching (D), and tem-pering (E). Samples were stored in plastic bucket (1 kg capacity)at room temperature until the analytical determinations. Beforeperforming each analysis, the samples were melted in a microwave(Stortz and Marangoni 2013), at 150 W for 25 min. The meltingparameters were chosen after preliminary experiments in order tominimize changes in the chocolate properties.

MethodsDetermination of PSD. Measurement of PSD was made

using a Mastersizer, Micro Laser Diffraction Particle Size 2000(Malvern Instrument Ltd., Malvern, U.K.) equipped with a

Figure 1–Scheme of chocolatemanufacturing process (adapted fromBabin 2005).

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Table 1–Particle size distribution of the dark chocolate.

Samples D(v,0.9)∗ (μm) D(v,0.1)∗ (μm) D(v,0.5)∗ (μm) D[3,2]∗ (μm) D[4,3]∗ (μm) Specific surface area (m2/g)

A 621.19a ± 4.17 2.18a ± 0.87 11.64a ± 1.57 5.44a ± 0.92 155.36a ± 3.33 1.10e ± 0.05B 129.96b ± 2.87 1.93b ± 0.54 10.69b ± 1.83 4.98b ± 0.98 41.85b ± 2.43 1.20b ± 0.18C 31.28c ± 1.54 1.68c± 0.32 7.58c ± 1.18 4.13c ± 0.12 14.65c ± 1.27 1.45c ± 0.04D 25.63c ± 1.32 1.63d ± 0.35 7.12d ± 1.06 3.95d ± 0.08 10.85c± 1.53 1.52b ± 0.06E 27.10c ± 1.44 1.56e ± 0.08 6.91e ± 0.59 3.83e ± 0.78 11.09c ± 1.27 1.57a ± 0.09

∗D(v, 0.9), D(v, 0.1), D(v, 0.5), D[3,2], and D[4,3], respectively, represent 90%, 10%, 50%. Sauter mean diameter and weight mean diameter of all particles finer than this size.a-dValues in the same column followed by different letters differ significantly at P < 0.05 level.

Hydro 2000 SM (B) for paraffin oil (RI 1.450). About 0.3 g ofdark chocolate was dispersed in oil until an obscuration of 16.85%,following the user guide of the instrument. Speed of stirring wasmaintained at 1900 rpm for all the measurements.

Size distribution was determined as relative volume of particlesin “size bands” and presented as size distribution curve and statistics

(Malvern Mastersizer Micro Software v. 5.60). PSD parametersobtained were: specific surface area, the largest PS (D90), meanparticle volume (D50), the smallest PS (D10), Sauter mean diameter(D [3, 2]), and volume mean particle diameter (D [4, 3]).

The last 2 parameters (Sauter mean diameter and volume meanparticle diameter) are the most commonly used to characterize

Figure 2–Particle size distribution of dark chocolate after: (A) mixing, (B) prerefining, (C) refining, (D) conching, and (E) tempering steps.

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PS and represent, respectively: the diameter of a sphere with theequivalent surface to volume ratio of all the particles in the sizedistribution (1)

d32 =∑

i

ni d 3i /

∑

i

ni d 2i (1)

and the diameter of a sphere having the average volume of all theparticles in the size distribution (2) (Black and others 1996).

d43 =∑

i

ni d 4i /

∑

i

ni d 3i (2)

Microstructure analysis. Microstructure of samples was ob-served by using an environmental scanning electron microscopeESEM (Evo 50 EP, Zeiss, Germany) equipped with a microprobe

(EDS Mod. 350, Oxford Instrument, U.K.). The used detector wasa backscatter electron detector (QBSE) that provided good com-positional contrast imaging at 20 kV and in low vacuum modewith 100 Pascal at 500× magnification, taking 10 micrographs foreach sample. These parameters were chosen after preliminary trialsand according to Dahlenborg and others (2010), considering thatthey cause minimal damage of the chocolate surface and in or-der to optimize the imaging quality. With this kind of instrumentESEM, samples are not coated and images are more dependenton sample rather than coating characteristics; thus, the true struc-ture can be analyzed (Rousseau 2007). The acquired images weresubsequently elaborated using the software Image Pro-plus 6.0(Bethesda, Md., U.S.A.).

Color measurements. Color of samples was measured using acolor spectrophotometer mod. Colorflex (Hunterlab, Reston, Va.,U.S.A.) equipped with a sample holder (diameter 64 mm). Color

Figure 3–Microghraphs of dark chocolate after different processing steps: (A) mixing, (B) prerefining, (C) refining, (D) conching, and (E) tempering.


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Table 2–Microstuctural analysis of the dark chocolate.

Samples Particle size (Feret diameter) Nr. of particles/area Area occupied by particles (%)

A 466.85a ± 1.99 263c ± 1.52 54B 105.26b ± 1.90 367b ± 2.00 65C 29.34c ± 1.93 460a ± 3.05 85D 22.72c ± 2.70 521a ± 2.00 40E 19.32c ± 2.72 532a ± 2.65 42

a-cValues in the same column followed by different letters differ significantly at P < 0.05 level.

was measured using the CIE L∗a∗b∗ color space and illuminantD65. The instrument was calibrated with a white tile (L∗ = 98.03,a∗ = −0.23, b∗ = 2.05) and the calibration was also validated withgreen standard tile (L∗ = 53.14, a∗ = −26.23, b∗ = 12.01) beforethe measurements.

Numerical values of a∗ and b∗ were converted into hue angle(h°) and Chroma (C∗) that represent the hue and the saturationindex (McGuire 1992):

C∗ = [(a ∗)2 + (b ∗)2

]1/2, ho = [

arctan (b ∗/a ∗) /2 �]∗

360

Each analysis was executed in triplicate.Statistical analyses. Analyses of variance (ANOVA) and the

test of mean comparison according to Fisher least significant differ-ence (LSD) were applied on all obtained data. Level of significancewas P � 0.05.

Figure 4–Lightness (L∗) color parameter of dark chocolate samples.a–dValues followed by different letters differ significantly at P < 0.05 level.

Figure 5–Hue angle (h°) color parameter of dark chocolate samples.a–cValues followed by different letters differ significantly at P < 0.05 level.

The statistical software used was STATISTICA, version 8.0(StatSoft, Tulsa, Oklahoma).

Results and Discussion

PSDIn Table 1 are reported the results of the PSD. Wide differences

in PSD were highlighted comparing results of different samples.The volume-based diameter (D [4, 3]) is mainly determined bythe large particles present in the suspension, while the area-baseddiameter (D [3, 2]) takes into account also small particles. Smallparticles are important in determining the physicochemical andtextural properties of the material because they fill spaces betweenlarger particles and contribute to the network structure of the sus-pension (Bayod 2008). A statistically significant decrease in D10,D50, and D [3, 2] values was obtained from sample A to sampleE with a simultaneous increase of the specific surface area. Theseresults are in agreement with those of Beckett (2000) and Sokmenand Gunes (2006) who stated an inverse correlation between spe-cific surface area and the remaining PSD parameters in chocolate.They also indicate that process steps from mixing to temperinginvolve a drastic reduction in PS (from 5.44 to 3.83 μm of Sauterdiameter) with a probable increase of the particles number and aconcurrent increase of points of contact. No statistical differenceswere found from samples C to E for what concern D [4, 3] andD90 parameters. In Figure 2(A) to (E), the volume curves of PSDsof different samples are shown. It can be observed as a narrowbimodal distribution of samples A (Figure 2A), a wide bimodaldistribution of sample B (Figure 2B), and a narrow unimodal dis-tribution of samples C, D, and E (Figure 2C to E). These resultsmean the influence of different stages, reducing the PS; involvea change in the particle distribution that moves from a bimodaltrend to a unimodal one. Moreover, from a graphical point ofview, different heights in the curves were highlighted. From sam-ples A to B, a drastic reduction in the height of the 2nd peak (in arange from 100 to 1000 μm) was observed, this confirms that thedecrease in PS values previously evaluated. Another increase in thecurves peak height was noted from samples C to E (from 3.8% to6%) in the range between 1 and 100 μm. This trend that involvesan increase of the volume occupied by small particles confirmsthe reduction of PS observed from the refined to the temperedsample.

According to Beckett (2000), D90 and specific surface area arethe 2 key parameters to assess PSD during chocolate manufacture.Large-particle diameters determine chocolate coarseness influenc-ing textural characteristics of final product, while specific surfacearea is related to the presence of fat that influences flow properties.For this reason, the control and the optimization of manufactureprocess becomes a nodal point in order to improve the final prop-erties of dark chocolate.




Microstructural properties of dark chocolateIn Figure 3(A) to (E), the micrographs relating to the samples

A, B, C, D, and E obtained by ESEM are shown. Microscopy wasused to characterize the variations, during the different processingsteps, in sugar crystalline network, particle shape, particle–particleinteraction, and particle–fat phase behavior of chocolate samples.The micrographs showed a strong heterogeneity in particles size,shape, and microstructure. In particular, it is possible to noticethat particles obtained from samples A and B (Figure 3A to B)are more flat, large, and made up from less angular shape, thanthose of sample C (Figure 3C). As shown by micrographs, sampleC was characterized by a complex structure having flaky particleswith a lot of angular and sharp edges, smaller than those of A andB. The particles of samples D and E (Figure 3D to E) had thesmallest size and the most regular shape. This is due to the effectof the last processing stages that reduce sharp edges, improving theroundness of particles.

Microstructural examination, carried out with the image anal-ysis (Table 2), showed a decrease of samples PS from the mixingstage (A) to the tempering phase (E), in agreement with PSDanalysis results.

The absolute values of PS evaluated with the image analysiswere lower than the ones obtained with the laser light diffrac-tion technique. According to the studies of Pieri and others(2006), the distribution of disc-shaped particles (not sphericalas in the case of a chocolate matrix), obtained with a laserlight diffraction technique, shifts the particles size toward largerfractions, with respect to the ESEM results. The reduction ofthe particle diameter caused an increase of the particle num-ber, parallel to an increase of contact points between particle–particle (Glicerina and others 2013), due to chemical and me-chanical interactions (Servais and others 2004; Afoakwa andothers 2009).

The percentage of the relative areas occupied by parti-cles increased from the mixing stage (A) to the refining one(C), and then decreased in the D and E samples. In suchsamples, which are derived by the conching and temperingstage, the presence of smallest particles is parallel to the pres-ence of a lower packed structure, in which particles are moreseparated.

The increase of particle interactions and specific surface areafrom samples A to C caused a reduction of the particles mobilitydue to their high aggregation. The result is a fully dense and packedsuspension in which small particles fill spaces between large ones(Bayod 2008).

Samples D and E (Figure 3D to E), having particles with smallsize diameter, were constituted by a less dense sugar crystallinenetwork, highlighted by a large number of void spaces. This couldbe related both to the further addition of cocoa butter duringthe conching stage that, in agreement with Beckett (2000) andAfoakwa (2009), wets the suspension filling the voids within thecrystal network and opens the structure, and also to the addition oflecithin. In fact, lecithin migrates to sugar/fat interfaces and coatssugar crystals, reducing particle–particle interactions and scatteringcrystals in the fat phase (Beckett 2000; Dhonsi and Stapley 2006).The micrographs of sample E seem to be apparently different fromthat of sample D. This is due to the effect of tempering step thatimproves the sample surface aspect, making it more shining andsmooth.

Color measurementsThe lightness (L∗), hue angle (h°), and chroma (C∗) val-

ues of chocolate samples are shown in Figure 4, 5, and 6,respectively.

Samples D and E, characterized by smaller particles of the othersamples, presented the significantly highest values of lightness, hueangle, and chroma. B and C chocolate samples, with the mostaggregated structures, showed intermediate values for all con-sidered color parameters, while sample A, with the less denseand homogenous network, due to particles with the highest size,showed the significantly lowest values of color parameters. Thehighest values of L∗, h°, and C∗ were recorded with the decreaseof the PS in the final samples (C, D, and E). In particular, theaddition of cocoa butter during conching step (D), determiningan inherent crystalline network, scatters light further increasingall color parameter values. Obtained results can be explained,according to the studies of Sagufy and Graf (1991), Hutchings(1994), and Afoakwa (2008), by the inverse relationship that existsbetween scattering light factors and particles size. Dark choco-late samples with the finest particles have a large specific surface

Figure 6–Chroma (C∗) color parameter of darkchocolate samples.a–dValues followed by different letters differsignificantly at P < 0.05 level.


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area and small diameter that tend to scatter more light, appear-ing lighter and more saturated compared to samples with coarseparticles.

ConclusionsBoth ESEM and the laser diffraction methods were very useful

and accurate in order to discriminate the differences existing ata microstructural level between dark chocolate samples duringprocessing steps.

ESEM provided detailed information about the different net-work between sugar particles in chocolate samples, highlight-ing the presence of more or less aggregate structures, due tothe particles–particles interaction during chocolate process. Laserdiffraction technique, on the other hand, was very appropriate formeasuring PSD evolution and, providing results in form of num-ber rather than images, to let a more rapid comparison betweensamples.

Overall, obtained results evidenced the increase of small par-ticles number and specific surface area in the chocolate sam-ples from the mixing to the refining stage that involved a re-duction of the particles mobility (Glicerina and others 2013),due to their high aggregation. The result was a microstructureevolution until a fully dense and packed suspension of refinedsample, in which the smallest particles fill spaces between thelargest ones. Moreover, during process, a reduction in the net-work density was noted after the addition of fat and lecithin,even if in presence of small particles. From obtained data, itis possible to state as an extended and rigorous microstructuralevaluation of this kind of samples is feasible using advancedtechnologies, such as microlaser diffraction and ESEM analyticaltechniques.

The overall obtained results are useful in order to give furtherand new information on chocolate microstructure and PSD andcan contribute to better improve processes and products and/orto design new chocolate products. In this sense, it is necessaryto elucidate how manufacturing process affect the food structurecharacteristics, and its final properties.

AcknowledgmentsThe authors would like to thank Unigra S.r.l (Conselice, Ra,

Italy) for providing dark chocolate samples.

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The Influence of Different Processing Stages on Particle Size, Microstructure, and Appearance of Dark Chocolate