Nanostructured Fat Crystal Systems

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Review in Advance first posted online on November 24, 2014. (Changes may still occur before final publication online and in print.)

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Nanostructured Fat Crystal Systems Annu. Rev. Food Sci. Technol. 2015.6. Downloaded from www.annualreviews.org Access provided by University of Guelph on 03/04/15. For personal use only.

Nuria C. Acevedo1 and Alejandro G. Marangoni2 1

Department of Food Science and Human Nutrition, Iowa State University, Ames, Iowa 50011-1061; email: [email protected]

2

Guelph-Waterloo Physics Institute, Center for Food & Soft Materials Science, Department of Food Science, University of Guelph, Guelph, Ontario N1G 2W1, Canada; email: [email protected]

Annu. Rev. Food Sci. Technol. 2015. 6:3.1–3.26

Keywords

The Annual Review of Food Science and Technology is online at food.annualreviews.org

fat nanoplatelets, oil-binding capacity, rheology of fats, fat nanostructure

This article’s doi: 10.1146/annurev-food-030713-092400

Abstract

c 2015 by Annual Reviews. Copyright All rights reserved

A new understanding of the nature and organization of fat crystalline supramolecular structure, in particular at the nanoscale, has arisen in the past three years. These new findings have helped establish that the first step in the formation of a triacylglycerol network is the creation of nanocrystalline platelets that aggregate into polycrystalline clusters in the micrometer range, ultimately forming a three-dimensional network. This review explains how fat nanostructure can be characterized and highlights recent findings on how crystallization parameters influence the formation of fat nanocrystals. For instance, shear has been shown to modify not only nanoplatelet size but also their aggregation, affecting some macroscopic properties such as porosity and, therefore, the ability of the network to effectively bind liquid oil. This new information on fat nanostructure is relevant from scientific and technological standpoints and has opened up the possibility of nanoengineering material properties as well as developing new products and processes.

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Changes may still occur before final publication online and in print

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1. STRUCTURAL LEVELS OF A FAT CRYSTAL NETWORK 1.1. Overview

Annu. Rev. Food Sci. Technol. 2015.6. Downloaded from www.annualreviews.org Access provided by University of Guelph on 03/04/15. For personal use only.

Fats and oils are abundant compounds in nature and are used extensively in food, cosmetic, pharmaceutical, and other industrial products (Gunstone & Padley 1997). Fats and oils also have the highest caloric density of all macronutrients. Fats are usually soluble in organic solvents and insoluble in water. At room temperature, they may exist in either liquid or solid forms, depending on their composition and structure, and are referred to as oil or fat, respectively. Chemically, fats and oils are triesters of glycerol and fatty acids and thus are commonly referred to as triglycerides or triacylglycerols (TAGs) (Figure 1a). The mechanical and rheological properties of fats depend highly on the ratio of solid crystallized fat to oil and on the structure of that crystalline fat. Therefore, control of fat crystallization is very important in the industrial processing of products such as chocolate, margarine, and shortening. The physical and sensory properties of these products are greatly influenced not only by the total amount of crystalline material present but also by the crystal size and shape, crystalline spatial arrangement, and magnitude of intercrystalline interactions (deMan & Beers 1987, Dixon & Parekh 1979, Hayakawa & deMan 1982, Rousseau & Marangoni 1999). The crystallization process consists of two phases: nucleation and crystal growth. Nucleation comprises the formation of stable molecular aggregates (called nuclei). Once a crystalline nucleus has formed, it grows quickly by incorporating other TAG molecules.

Short spacing

a

b L

L Long spacing

L

L

2L Chair

Tuning fork

L

3L

c

d

Lamella

Crystalline domain

Figure 1 (a) Schematic representation of a triacylglycerol (TAG) molecule in chair and tuning fork configurations. Spatial arrangements of TAG molecules (b) in pairs and subsequently (c) into a lamella are also shown. (d ) Stacking of several lamellae leads to the formation of a crystalline domain. Abbreviation: L, fatty acid chain length. Adapted from Acevedo et al. (2011) with permission from Elsevier. 3.2

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TAGs are three-legged molecules, with each leg corresponding to an acyl chain. When TAG molecules nucleate, they can pack in one of two configurations: (a) a tuning fork, in which the sn-1 and sn-3 acyl chains pack alongside each other and sn-2 is alone, or (b) a chair configuration, in which the fatty acid in the sn-2 position packs alongside the chain on either the 1 or 3 position (Figure 1a). Upon crystallization, TAG molecules stack in pairs side by side in crystal planes, and the zigzag planes of the acyl chains are parallel to each other (Figure 1b) (Bennema et al. 1988). The stacking of these TAGs can be in either a double (2L) ( Jensen & Mabis 1963, 1966) or triple (3L) (Peschar et al. 2004) fatty acid chain length structure. The height of these TAG structures and the distance between the molecules are determined using X-ray diffraction (XRD) as the long and short spacings, respectively. Subsequently, the continuous self-assembly of TAG molecules into crystals results in the formation of long lamellae (Figure 1c), with a height corresponding to the long axis (c-axis) of the unit cell. The lamellae, in turn, stack epitaxially, creating crystalline domains (Mazzanti et al. 2005) (Figure 1d ), which correspond to the thickness of a TAG nanoplatelet. These nanoplatelets immediately aggregate into larger units, eventually leading to the creation of a three-dimensional fat crystal network. The crystallization process has a strong influence on the final structure, mechanical properties, and functionality of the fat (Gamboa & Gioielli 2006, Rousseau & Sonwai 2008, Sato 2001, Wassel & Young 2007). For that reason, researchers are greatly interested in the study of fat structure-function relationships, as they are critical for the rational design and manufacture of food products. Over the past few years, the food industry has faced a new challenge related to the health consequences of an excessive consumption of fat-rich foods. Humans enjoy consuming high-fat foods because fats greatly contribute to palatability (mouthfeel) and eating pleasure. However, our society is facing an unprecedented increase in the incidence of obesity, cardiovascular disease, and type 2 diabetes. Moreover, several studies have established a direct connection between trans fatty acid intake and increased risk of cardiovascular disease (European Food Safety Authority 2004, Gidding et al. 2009). Thus, much attention has been focused on improving the health characteristics of the foods we consume; these efforts rely basically on the production of lowercaloric foods with decreased amounts of so-called bad fats. The challenge lies in the retention of the quality characteristics associated with a specific product that determines its acceptance by the consumer. As a result, it has become essential to understand the solid-state structure and supramolecular organization of fat crystals and crystal networks at different length scales and their effects on the macroscopic properties of the final product. As mentioned above, fats are polycrystalline aliphatic materials that display a surprisingly complex structural hierarchy, represented in Figure 2 (Narine & Marangoni 2004). The underlying structure of fat is a continuous fractal network of TAG polycrystals and crystal agglomerates stabilized by van der Waals forces and with liquid oil trapped within (Marangoni & Rogers 2003; Narine & Marangoni 1999; Nederveen 1963; Tang & Marangoni 2008; Van den Tempel 1961, 1979). The microstructural level, or mesoscale, of a fat crystal network may range between 1 and 100 μm and has a strong influence on the macroscopic properties of the system (Marangoni et al. 2012). At the nanoscale (0.4–500 nm), TAGs crystallize into determined polymorphic forms. Crystal clustering and the formation of larger assemblies continue until the macroscopic structure is attained. The rheological properties, mechanical strength, oil-binding capacity, and sensory properties of a fat are a function of a complex combination of the structure at different length scales. This review seeks to provide a comprehensive description of the latest and most important findings on the structure of fat crystal networks, in particular on the nanostructural level, which has recently been characterized (Acevedo & Marangoni 2010a,b). Additionally, this review aims to www.annualreviews.org • Nanostructured Fat Crystal Systems


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Rheology Mechanical strength Sensory impressions

Fat

Macroscopic world >0.2 mm

Crystal network Microstructure 0.5–200 μm

Solid fat content Mesocrystal size/shape Mass distribution

Crystal clusters

Polymorphism Nanocrystal size

Nanoplatelets Nanostructure 0.4–500 nm


Molecular structure

Triacylglycerol molecules

Figure 2 Structural hierarchy of a fat crystal network established during crystallization. Adapted from Narine & Marangoni (2004) with permission from CRC Press.

highlight some recent advances on the role of the nanostructure in the mechanical and functional properties of plastic fats.

1.2. The Problem of Quantifying the Nanostructure of Fat Crystal Networks: The Meso- or Nanoscale? In the past decade, researchers have carried out much work on the structure of fats at the mesoscale, as it was found to relate closely to the networks’ physical properties. For example, historically, polarized light microscopy (PLM) has been the most commonly used technique to visualize and quantify the microstructure of fat crystal networks (Awad et al. 2004, Campos et al. 2002, Shi et al. 2005). PLM allows for the direct observation of fat crystals in the sample because of their birefringence, i.e., crystals appear bright between two crossed polarized filters, whereas the liquid oil becomes dark. The limitation of this technique is its low resolution, which is on the order of 1 μm. Figure 3 depicts the mesoscale of a fat crystal network at two different magnifications. Crystals and polycrystal aggregates in the micrometer range, as well as the fractal distribution of crystalline mass in the network, can be observed clearly. The formation of these polycrystals is influenced strongly by external fields (such as temperature gradients and shear fields) experienced during nucleation and crystal growth. Much work has been reported on the changes induced in the crystalline network by different processing conditions and the influence on the properties of fats (deMan & Beers 1987; Heertje et al. 1987, 1988; Herrera & Hartel 2000; Marangoni & Rousseau 1996; Martini et al. 2002; Shukla & Rizvi 1996). However, the nanostructure, within a scale range of up to several nanometers, had not been identified, imaged, or quantified until recently. Instead, most of the structural studies have been restricted to mesoscale analysis. Electron microscopy would be a suitable technique for the observation of nanoscale-sized fat crystals because of its higher resolution. However, the presence of oil between the fat crystals obstructs their proper visualization. For that reason, fat nanostructure remained in the dark for many years. Special preparation techniques are clearly required to observe nanoscale-sized objects and characterize their properties. Several authors have attempted to overcome the aforementioned difficulty, providing some new insights into the microstructure of fat crystal networks. For example, Jewell & Meara (1970), 3.4

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a

b

50 μm

10 μm

Figure 3 Polarized light microscopy (PLM) and phase contrast microscopy (PCM) micrographs showing fat crystal mesostructure at two different magnifications. The images were created by superimposing PLM and PCM micrographs. Polycrystals and polycrystal agglomerates of several micrometers in size can be observed. (The data are unpublished.)

Poot et al. (1975), and Heertje et al. (1987) were able to remove oil by using solvents or detergents, allowing them to visualize the structural elements in fats by electron microscopy. Furthermore, Heertje & Leunis (1997) reported the use of a carbon fixation technique based on the fixation of fat crystals to a thin carbon support film, which allowed the imaging of individual fat crystals by transmission electron microscopy (TEM). However, it was not until Acevedo & Marangoni’s effort (2010a) that the nanostructure of a fat crystal network was identified clearly. These authors demonstrated that the polycrystals observed under PLM do not constitute the primary crystals formed upon nucleation; instead, they are an agglomerate of TAG nanoplatelets. Acevedo & Marangoni developed an effective sample treatment consisting of the extraction of nanocrystals with cold isobutanol prior to imaging by cryogenic TEM (Cryo-TEM). Figure 4a shows an example of micrographs obtained using these authors’ technique. The side view and inner organization of the primary nanoplatelets can be observed clearly (Figure 4b). This work provided a new perspective in fat structure-function research and laid the foundation for a broader understanding of the aggregation mechanisms responsible for the formation of fat crystal networks and their functional implications.

2. CHARACTERIZATION OF THE NANOSTRUCTURAL LEVEL IN FATS 2.1. Cryogenic Transmission Electron Microscopy Light microscopy is a technique with limited resolving power imposed by the wavelength of visible light. TEM, on the other hand, can achieve nanometer-scale resolution. For this reason, TEM is a very attractive technique among researchers in nanostructural studies. However, the use of TEM for the direct visualization of a fat matrix requires cryogenic conditions (Cryo-TEM) to avoid sample melting upon exposure to the electron beam. Cryo-TEM can image objects as small as 1 nm (Bellare 1988); however, in the case of fats, one further limitation exists, which is that the frozen oil entrapped by the network impedes the proper observation of nanoscale-sized crystals. This is a consequence of the low contrast between the crystallized oil and original TAG crystals. www.annualreviews.org • Nanostructured Fat Crystal Systems


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a

b Nanoplatelet thickness

100 nm


Nanoplatelet side view 200 nm

Figure 4 Cryo-TEM images showing nanoplatelets after their extraction with isobutanol at 10◦ C. (a) The micrograph corresponds to a blend of 30% weight/weight (w/w) of fully hydrogenated soybean oil in liquid soybean oil. (b) Nanoplatelet side view revealing the internal lamellar arrangement of triacylglycerol molecules. (The data are unpublished.)

Chawla et al. (1990) and Chawla & deMan (1990) reported effective separation and isolation (approximately 5%) of fat crystals from the liquid oil without a significant dissolution of solids. Thus, based on these findings, Acevedo & Marangoni (2010a) developed a cold solvent–based sample treatment to separate and extract the nanocrystals and allow their proper imaging by CryoTEM. They mixed fat samples with a cold solvent, typically isobutanol, in ratios of about 1:50 weight/weight (w/w). The key step in the sample preparation is the initial structural breakage of the matrix, which involves mechanical homogenization of the suspension with a rotor-stator. Upon this first stage of treatment, most of the sample oil is released and subsequently eliminated by filtration. A second stage of cold solvent wash is followed by ultrasonication to ensure the complete dispersion of the nanocrystals prior to imaging. Even though this new sample treatment allowed the successful observation of the extracted nanoparticles, these authors reported aggregation of fat crystals over time as a limitation of the method. They found that the prepared specimens should be imaged immediately, as newly formed agglomerates will prevent the imaging of individual nanocrystals. Nevertheless, platelet-like structures could be visualized and quantitatively characterized in size and shape from fat systems of different sources (Acevedo 2012; Acevedo & Marangoni 2010a,b, 2014; Acevedo et al. 2012a,b; Maleky et al. 2011a, 2012). This novel, solvent-based procedure, together with Cryo-TEM, proved to be an effective tool to visualize the internal organization of nanoplatelets. The fact that platelet lengths and widths were significantly larger than the thicknesses, i.e., the platelet’s short dimension, indicates that they periodically stack, forming layers parallel to the ab plane surface of the platelets (Figure 4). Therefore, the side views of platelet stacks are often observed in the images, allowing for the visualization of the inner structure of the nanoplatelets (Figure 4). A side view of a nanoplatelet revealed an internal layered structure corresponding to the epitaxial assembly of several TAG lamellae. Interestingly, in all the images analyzed, a maximum value of 7–10 lamellae per nanoplatelet was determined. According to the measured distance between consecutive lines, the average thickness of each lamella was 4.23 ± 0.76 nm in a sample of 3.6

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fully hydrogenated canola oil (FHCO). This result was found to agree closely with small-angle powder XRD data, which yielded a long spacing value of 4.5 nm for the same sample (Acevedo & Marangoni 2010a). This new analytical technique provided structural information that was not accessible before. However, as mentioned above, the main drawback associated with this technique is the strong aggregation tendency of nanocrystals, which negates the use of automatic image analysis tools for determination of crystal sizes. Instead, semiautomatic procedures must be used for this purpose. The imaging technique allows for the determination of size distributions of the platelets.

During crystallization, TAG molecules can pack into two or more crystalline forms (Chapman 1962). This phenomenon is known as polymorphism. Three polymorphic forms—α, β , and β— which differ from each other in the hydrocarbon chain packing, have been described previously in fat systems (Clarkson & Malkin 1934). The most widely accepted method for identification of crystal forms is powder XRD, as it is a well-known phase-selective method. Because TAG crystal unit cells (and therefore nanocrystals) are highly asymmetric, with one of the axes very long relative to the other two axes, two regions of characteristic lattice parameters can be recognized: long spacings in the small-angle region of the spectra (1–15◦ ) and short spacings in the wide-angle region (16–25◦ ) (Figure 5). The smallest building block of a fat crystal is the unit cell, and its successive translation in three-dimensional space leads to the formation of a crystal lattice. The length of the unit cell in the c-axis direction, corresponding to the distance between ab planes, defines the long spacing determined by XRD and corresponds to the thickness of the lamellae (Figure 6). Thus, long spacings are a function of the length of TAG molecules and the angle of tilt of the chains relative

Small angle

Wide angle

Long spacing Imax

Intensity (arbitrary units)


2.2. X-Ray Powder Diffraction: Scherrer Analysis

Short spacings

I½

1

FWHM

2

3 15

20

25

30

2θ (degrees) Figure 5 Powder X-ray diffraction spectrum obtained for a typical plastic fat in the small- and wide-angle regions. The full width at half maximum (FWHM) of the (001) reflection peak is indicated with arrows. The peaks detected in the wide-angle region (short spacings) determine the polymorphic form present in the sample. Abbreviations: Imax , maximum intensity; I1/2 , half the maximum intensity; θ , theta. Adapted from Acevedo et al. (2011) with permission from Elsevier. www.annualreviews.org • Nanostructured Fat Crystal Systems


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Front view

a

b

Cross section Hydrocarbon chain packing

Lamella thickness (long spacing) Unit cell

Subcell

a b

c

c

b a


Figure 6 Representation of a lamella indicating the physical significance of the (a) unit cell and (b) subcell within the crystal lattice. (The data are unpublished.)

to the normal plane (Chapman 1962). However, the short spacings of the subcell refer to the crosssectional packing of the hydrocarbon chains. The subcell is the smallest repeating unit within the unit cell and along the acyl chains. Each chain-packing subcell gives rise to a specific set of XRD reflections, allowing for the identification of the different polymorphic forms of fats. XRD is also an appropriate method to determine the average size of nanocrystallites in a material. The Scherrer equation links the measured width of an XRD peak (full width at half maximum, or FWHM) to the crystallite size, D, (Scherrer 1918, West 1984): D=

Kλ , FWHM cos(θ)

(1)

where θ is the diffraction angle (in radians), FWHM is the peak width in radians of the diffraction peak profile at half maximum height, λ is the X-ray wavelength (1.54 A˚ for a copper anode), and K (Scherrer constant) is a dimensionless magnitude related to the crystalline shape, usually taken as 0.9. For more detailed discussion on the prefactor, K, the reader is referred to a review reported by Langford & Wilson (1978). Scherrer’s equation can be used to estimate mean crystal sizes up to about 100 nm, as peak broadening is inversely proportional to crystallite size. Hence, for cases in which sizes are larger than 100 nm, it becomes very difficult to differentiate between peak broadening because of crystallite size and other causes such as instrumental broadening. Because nanoplatelet lengths and widths are significantly larger than the aforementioned limit, this method cannot be used for their estimation. However, the thickness of the nanoplatelets is within this range and can thus be estimated from the width of the peak corresponding to the reflection of the ab plane and by obtaining D with the Scherrer equation. The Scherrer equation has been used previously to determine crystallite size in fat matrices (Martini & Herrera 2002); however, these authors did not assign their results to a specific crystallite dimension. The correct interpretation of the results obtained from the Scherrer analysis was only possible after a systematic characterization of fat nanostructure was accomplished (Acevedo & Marangoni 2010a). Several software packages are available for the analysis of the XRD patterns. The PeakFit computer program (Seasolve, Framingham, Mass.) is, among others, widely used because of its versatility for fitting spectrometry and chromatography data. Table 1 shows the Scherrer 3.8

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Table 1 Examples of nanoplatelet thickness values (D) calculated with data from XRD curve fitting and the Scherrer equation FWHM (radians)

θ (◦ )

D (A˚)

FHCO:HOSO 30:70

2.0982 × 10−3

0.9772

661.43

FHSO:SO 40:60

6.4658 × 10−3

1.1001

216.66

FHSO:SO 30:70

6.315 × 10−3

1.1363

224.83

FHSO:SO 20:80

5.773 ×

10−3

1.0858

240.41

Commercial laminating shortening

6.4952 × 10−3

1.1372

213.67

Samplea


Abbreviations: FHCO, fully hydrogenated canola oil; FHSO, fully hydrogenated soybean oil; FWHM, full width at half maximum; HOSO, high oleic sunflower oil; SO, soybean oil; XRD, X-ray diffraction; θ, the diffraction angle. a For all samples, the Scherrer constant (K) is 0.9, and the XRD wavelength (λ) is 1.5418 A˚ for a copper anode.

parameters along with the estimated values of nanoplatelet thickness (D) for different fat crystal networks. In terms of the relevant length scales in which fat crystal networks are probed, both CryoTEM and XRD provide comparable results. Researchers have shown that D values estimated by applying the Scherrer analysis are in close agreement with those obtained from measurements of the nanocrystal side views observed by Cryo-TEM. For example, the average D value for a sample of FHCO was 31.32 ± 0.07 nm, whereas the value measured from the Cryo-TEM images was 31.2 ± 2.3 nm (Acevedo & Marangoni 2010a). The development of the new solvent-based fat sample treatment prior to imaging using electron microscopy has certainly narrowed the gap between studies of fat crystal networks performed by XRD and Cryo-TEM. Both structural techniques together allow a comprehensive exploration of the self-assembly behavior of fat molecules into nanocrystals and nanocrystals into colloidal polycrystals, structures that are difficult to characterize quantitatively. As a result of the new findings highlighted here, fat crystal networks can now be studied using a more systematic approach, as nanocrystalline elements can be accurately characterized using both XRD and Cryo-TEM. Using this information, we can diagram the three-dimensional structure of fat nanocrystals (Figure 7). The three dimensions, i.e., length, width, and thickness, can be measured using the novel sample treatment developed by Acevedo & Marangoni (2010a), followed by Cryo-TEM. Additionally, Cryo-TEM allows the determination of lamellar size. Small-angle powder XRD data provide analogous results to those of Cryo-TEM in the determination of nanoplatelet thicknesses and lamellar height. Thus, both techniques are complementary in the study of TAG crystallography and nanostructure.

3. CHANGES INDUCED AT THE NANOSTRUCTURAL LEVEL It has been widely demonstrated that composition and processing conditions impact the structure of fats (Stapley et al. 1999). Several investigations have demonstrated that changes in mesocrystal size in fat networks are due to the different nucleation rates influenced by different processing conditions (Campos et al. 2002, Dibildox-Alvarado et al. 2004, Martini et al. 2002, Singh et al. 2004). In addition, many research groups have found that, in general, processing conditions and solid fat content (SFC) have a greater influence on the shape and size of fat crystal clusters than their resulting polymorphism (Campos et al. 2002, Herrera & Hartel 2000). Matrix supersaturation has also been found to induce alterations in the microstructure of TAG networks. For instance, a reduction in cluster size and network density as a result of a decrease in matrix supersaturation has been reported previously (Ahmadi et al. 2008, Ribeiro et al. 2009, Rodr´ıguez et al. 2001). www.annualreviews.org • Nanostructured Fat Crystal Systems


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Side views

a Platelet thickness

XRD (Scherrer analysis) and Cryo-TEM

100 nm

Lamella length


XRD (long spacing) and Cryo-TEM

Front view

Cryo-TEM

Len

gth

500 nm

h

gt

n Le

h idt W

Wi dth

b

500 nm

Figure 7 Fat nanoparticles indicating the quantitative information obtained by cryogenic transmission electron microscopy (Cryo-TEM) and X-ray diffraction (XRD). (a) Nanoplatelet side view. (b) Nanoplatelet front view.

3.1. Composition Using the extraction method described above, Acevedo & Marangoni (2010a) demonstrated that supersaturation had a profound effect on crystalline nanoscale structure. This is illustrated clearly in Figure 8, which shows the results of different blends of FHCO and high oleic sunflower oil (HOSO) imaged by Cryo-TEM. In this case, all fat mixtures were crystallized under isothermal and static conditions. The reduction in the amount of sunflower oil added to the mixture directly influenced nanocrystal size; the higher the degree of supersaturation [ln(β)] in the blends (given by the decrease in liquid oil content), the smaller the nanoplatelet lengths, widths, and thicknesses (Figure 8b). These results observed at the nanoscale were not surprising, considering that a high supersaturation in the melt typically translates to a more extensive nucleation process, which in turn yields a larger number of smaller crystals (Himavan et al. 2006). Moreover, Acevedo & Marangoni (2010a) reported, for the same fat samples, a linear correlation with high correlation coefficients (r2 ) between the length or width of the nanoplatelets and 3.10

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4.4 (30% of FHCO)

4.8 (50% of FHCO)

5.9 (100% of FHCO)

a

100 nm

400

200

4.5

5.0

In(β)

5.5

6.0

Platelet thickness (nm)

300

100 4.0

200 nm

200

Platelet width (nm)

b

Platelet length (nm)


200 nm

150 100 50 0 4.0

4.5

5.0

5.5

6.0

42

38

34

30 4.0

4.5

In(β)

5.0

5.5

6.0

In(β)

Figure 8 Effect of supersaturation [ln(β)] on the nanostructural level of blends crystallized under the same conditions. (a) Cryo-TEM micrographs of samples of fully hydrogenated canola oil (FHCO) in high oleic sunflower oil (HOSO) with increasing values of ln(β). (Left to right) 4.4 (30% FHCO), 4.8 (50% FHCO), and 5.9 (100% FHCO). (b) Platelet length and width obtained from analysis of Cryo-TEM images and thickness calculated by Scherrer analysis of small-angle X-ray diffraction data; all are a function of supersaturation. Standard error is ≤1.5% in all samples. Adapted from Acevedo & Marangoni (2010a) with permission from the American Chemical Society.

their thicknesses. These authors reported nanoplatelet lengths twofold larger than the widths. Furthermore, they emphasized the significance of these findings, as it could be possible to predict platelet lengths and widths from the value of the thickness, which can be rapidly acquired by small-angle powder XRD. The new experimental results on the nanoscale of fats set the stage for the updated depiction of the structure of TAG crystal networks at different length scales (Figure 9). The complex combination of the structural properties along all length scales, from TAG molecules, primary nanoplatelets, and mesocrystals to a colloidal network of polycrystals, determines the macroscopic properties of a fat, such as its mechanical strength, oil-binding capacity, and sensory properties.

3.2. External Fields The application of external fields during crystallization is known to strongly affect the fat crystallization process (Martini et al. 2002; Mazzanti et al. 2003, 2004, 2005; Vuillequez et al. 2010). Mechanical properties, oil binding capacity, and, ultimately, product functionality can be significantly influenced by changes in processing conditions. Hence, external temperature and shear fields can be manipulated through unit operations to tailor crystalline structure and physicochemical characteristics. www.annualreviews.org • Nanostructured Fat Crystal Systems


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Spherulite

Bulk fat Nanoplatelet


100 nm

Lamella

Lamella

Nanoplatelet thickness

Nanoplatelet

Figure 9 Structural levels present in a triacylglycerol (TAG) crystal network. The crystalline unit is a platelet with sizes within the range of several nanometers; in turn, nanoplatelets are composed of stacks of TAG lamellae. At the mesoscale (several micrometers), spherulites can be observed that then self-assemble to constitute a three-dimensional network. Adapted from Marangoni et al. (2012) with permission from the Royal Society of Chemistry.

3.2.1. Crystallization at different cooling rates. Fat systems crystallized at high temperatures, i.e., at a slow cooling rate, undergo a slow nucleation process that is typically accompanied by a relative increase in mesocrystal growth and, thus, larger crystal sizes (Herrera & Hartel 2000, Wiking et al. 2009). Therefore, when fat blends of FHCO:HOSO were crystallized nonisothermally at two different cooling rates—1 and 10◦ C/min—the formation of large and small nanoplatelets, respectively, was not surprising (Acevedo & Marangoni 2010b). Figure 10a depicts Cryo-TEM images of a sample of 1:1 FHCO:HOSO, which showed the predominance of larger nanoplatelets when the mixture was crystallized at a slow cooling rate relative to a fast cooling rate. Figure 10b shows the mean values for platelet lengths and widths of different FHCO:HOSO mixtures when cooled down from the melt at both cooling rates. Again, results clearly suggest that platelet dimensions in a sample crystallized at fast cooling rates (10◦ C/min) are smaller than one crystallized at slow cooling rates (1◦ C/min) (P < 0.001) (Acevedo & Marangoni 2010b). 3.2.2. Crystallization under laminar shear fields. The influence of shearing during crystallization on fat structure is an area of current interest and has been the topic of several recent publications. Many authors have reported that under shear fields, the orientation of fat crystals and their transformation to more stable polymorphs as well as crystal nucleation are favored (Himavan et al. 2006; Kloek et al. 2005; MacMillan et al. 2002; Mazzanti et al. 2004, 2005; Sonwai & Mackley 2006). Acevedo & Marangoni (2010b, 2013) and Acevedo et al. (2012a,b) studied the effects of crystallization under shear on the nanostructure of TAG crystal networks. In their first study, working with blends of FHCO in HOSO, they showed that high laminar shear (LS) rates (300 s−1 ) during crystallization resulted in a decrease in platelet length, width, and thickness. The formation of 3.12

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10°C/min

1°C/min

200 nm

100 nm 150

Platelet width (nm)

400

b Platelet length (nm)


a

10°C/min 1°C/min

300

200

100 30

60

80

% FHCO (w/w)

100

130 110 90 70 50 40

60

80

100

% FHCO (w/w)

Figure 10 Effect of crystallization under different cooling rates on the nanostructural level of fats. (a) Cryo-TEM images obtained for fat samples 1:1 FHCO:HOSO crystallized at fast (10◦ C min−1 ) and slow (1◦ C min−1 ) cooling rates. (b) Platelet lengths and widths obtained by analysis of Cryo-TEM images of different ratios of FHCO:HOSO after crystallization at cooling rates of 10 and 1◦ C min−1 . Standard error is ≤1.5% in all samples. Abbreviations: Cryo-TEM, cryogenic transmission electron microscopy; FHCO, fully hydrogenated canola; HOSO, high oleic sunflower oil. (The data are unpublished.)

smaller nanoplatelets upon shearing, as can be observed in the Cryo-TEM images of Figure 11, was attributed to the enhancement of the kinetics of nucleation due to shear, as this increases mass transfer in the melt (MacMillan et al. 2003, Mazzanti et al. 2003, Stapley et al. 1999). After applying a shear rate of 300 s−1 , nanoplatelet length, width, and thickness decreased for all blends independent of their solid mass fraction (given by %FHCO). These results agree with findings reported by Maleky et al. (2011a,b) on cocoa butter nanostructure crystallized under LS. Acevedo et al. (2012a) used the solvent-extraction method described above to follow changes in the nanoscale of mixtures of fully hydrogenated soybean oil (FHSO) in liquid soybean oil (SO) induced by different LS rates (0, 30, and 240 s−1 ). They demonstrated that, unexpectedly, larger nanoparticles with higher aspect ratios (length to width ratios) were predominant in sheared blends, compared to those observed in nonsheared samples (Figure 12a). Furthermore, low shear rates of 30 s−1 led to the formation of the largest nanoplatelets; however, their substantial increase in size was not as www.annualreviews.org • Nanostructured Fat Crystal Systems


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Static

Shear


a

200 nm

150

Platelet width (nm)

400

Platelet length (nm)

b

200 nm

300

200

100

50

60

70

80

90

100 75 50

100

Static Shear

125

50

60

70

FHCO (%)

80

90

100

FHCO (%)

Platelet thickness (nm)

60 Static Shear

50 40 30 20 10

20

30

40

50

60

70

80

90

100

FHCO (%)

Figure 11 Example of the effect of crystallization under laminar shear on TAG nanocrystal dimensions. (a) Cryo-TEM images for samples of FHCO crystallized statically (left) and at a laminar shear rate of 300 s−1 (right). (b) Platelet lengths and widths obtained by analysis of the Cryo-TEM images and thickness obtained by Scherrer analysis of XRD data as a function of %FHCO. Standard error is ≤1.5% in all samples. Abbreviations: Cryo-TEM, cryogenic transmission electron microscopy; FHCO, fully hydrogenated canola oil; TAG, triacylglycerol; XRD, X-ray diffraction. Adapted from Acevedo & Marangoni (2010b) with permission from the American Chemical Society. 3.14

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30 s–1

Static

240 s–1

500 nm 1,500

200

150 1,000 100 500 50

0

0

30

240

0

Shear rate (s–1)

30

240

0

500 nm

50

Nanoplatelet thickness (nm)

Nanoplatelet length (nm)

b

500 nm

Nanoplatelet width (nm)


a

40 30 20 10 0

0

30

240

Shear rate (s–1)

Figure 12 Example of the effect of crystallization under laminar shear on TAG nanocrystal dimensions. (a) Cryo-TEM images obtained for 45:55 FHSO:SO blends crystallized statically (left) and at laminar shear rates of 30 (center) and 240 s−1 (right). (b) Platelet lengths and widths obtained by analysis of Cryo-TEM images and thickness obtained by Scherrer analysis of XRD data as a function of the laminar shear rate. Abbreviations: Cryo-TEM, cryogenic transmission electron microscopy; FHSO, fully hydrogenated soybean oil; SO, soybean oil; TAG, triacylglycerol; XRD, X-ray diffraction. Adapted from Acevedo et al. (2012a) with permission from the Royal Society of Chemistry.

significant at 240 s−1 . The authors suggested that these results, in conjunction with those reported in their previous study (Acevedo & Marangoni 2010b), are due to the existence of a critical value (or range) of shear rates of about 300 s−1 , above and below which the effects on the nanoscale are different. Rates below the critical shear (0 to 240 s−1 ) led to an increase in crystallite size, and shear rates higher than 300 s−1 yielded a decrease. Da Pieve et al. (2010) studied the effect of shear rates between 0 and 2,000 s−1 on the crystallization behavior of monoacylglycerol organogels. They found an increase in the domain size, i.e., nanoplatelet thickness, with increasing shear rates up to values of about 100 s−1 . However, higher shear rate values induced a decrease in nanocrystal thickness, indicating the existence of a critical shear rate, probably approximately 100 s−1 , above which a decrease in crystal thickness could be observed in the monoacylglycerol system. In their studies, Acevedo et al. (2012a,b) found that shear may have an effect on the thickness of nanoplatelets. Thickness mean values were not significantly different at the studied shear rates; www.annualreviews.org • Nanostructured Fat Crystal Systems


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however, a decreasing trend in particle thickness at 30 s−1 followed by the absence of this effect at 240 s−1 could be observed (Figure 12b). Therefore, based on the discoveries documented by Acevedo et al. (2012a,b), one can infer that, under mild shear forces, i.e., below critical shear rates, the length and width increase while thickness decreases.


3.2.3. Crystallization under turbulent shear fields. Recently, Acevedo & Marangoni (2013, 2014) focused their research on fat nanostructure toward the exploration of the effects of crystallization under shear using a scraped surface heat exchanger (SSHE). Their work aimed to evaluate the possibility of functionalizing noninteresterified mixtures of fully hydrogenated fats by altering the nanostructure of the fat using shear processing, adding emulsifiers, or both. It is widely known that crystallization under shear is advantageous in that it improves the plasticity and texture of the product and removes the heat of crystallization from the sample (Paulicka 1989). SSHEs are mechanically assisted, turbulent film heat exchangers commonly used in the food industry to crystallize highly viscous liquids (Levine 1993). Acevedo & Marangoni (2013) worked with mixtures of FHSO and liquid SO and found that crystallization in the SSHE led to the presence of not only larger but also more elongated nanoplatelets compared to static crystallization (Figure 13). Because the shear rate achieved in this work was relatively low (25 s−1 ), i.e., below the critical value of ∼300 s−1 , the findings agreed with prior results reported in Figure 12, in which an increase in nanoplatelet size upon crystallization occurred under mild LS (Acevedo et al. 2012a). Moreover, crystallization in the SSHE led to a twofold increase of nanoplatelet length relative to static crystallization. However, no significant change was observed in nanocrystal widths. Acevedo & Marangoni (2013) attributed these observations to enhanced crystal growth in the longitudinal direction. Scherrer analysis of the small-angle powder XRD revealed nanoplatelet thicknesses that were not significantly different before and after crystallization under turbulent shear fields (Figure 13b). Furthermore, the results showed thicker nanocrystals in blends with higher proportions of FHSO, suggesting that the increase in particle thickness was not affected by shear fields in the SSHE, and only nanoplatelet lengths were affected. Regarding the effect of the presence of different emulsifiers on nanocrystal sizes, Acevedo & Marangoni (2014) reported that, upon crystallization in the SSHE, the addition of surfactants could induce either an increase or a reduction in crystal sizes, depending on their influence during the nucleation and crystal growth stages. For instance, the addition of palm-based monoacylglycerol led to an increase in nanocrystal sizes. This effect was attributed to the delay in crystal growth caused by the incompatibility between palmitic and stearic acyl chains that form a eutectic upon cocrystallization. As a result, larger nanocrystals could be observed upon crystallization of the glyceryl monopalmitate emulsifier with the fat. To provide a more comprehensive analysis of the effects of external fields on the nanostructure of fats, nanoplatelet aspect ratios (length to width ratios) obtained from Acevedo & Marangoni’s research (2010b, 2013) are included in Table 2. Crystallization under shearing conditions, either laminar or turbulent, led to an enhancement of the longitudinal growth of the nanocrystals, evidenced by higher aspect ratios after crystallization under these conditions. For example, in blends of FHSO and SO, LS rates yielded aspect ratio values 17% higher than those obtained for nonsheared samples. Moreover, the same blends displayed an increase of 50% in the aspect ratio value upon crystallization in the SSHE. Crystallization under turbulent conditions evidently had a larger effect on fat nanostructure than under a laminar regime. However, laminar shearing at 300 s−1 of FHCO:HOSO mixtures led to the formation of smaller nanoplatelets in fat systems (Acevedo & Marangoni 2010b). Nevertheless, Table 2 reveals an enhancement of the nanocrystals’ longitudinal growth, indicated by an increase in the aspect ratio of the nanoparticles. 3.16

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SSHE 25 s–1

Static

b

600 Length Width

500

b

400 300

a

200 c

c

100 0

Static

25 s–1

200 nm

Nanoplatelet thickness (nm)

200 nm

Nanoplatelet size (nm)


a

60 40:60 FHSO:SO 45:55 FHSO:SO

50

b b

40 30

a a

20 10 0

Static

25 s–1

Figure 13 Effect of crystallization under turbulent shears generated by an SSHE on TAG nanocrystal dimensions. (a) Examples of Cryo-TEM micrographs obtained for 45:55 FHSO:SO blends crystallized statically and in an SSHE (25 s−1 ). (b) Nanoplatelet lengths and widths obtained by analysis of Cryo-TEM images and thickness obtained by Scherrer analysis of XRD data; in this case, information from blends with both 40% and 45% FHSO is illustrated. Letters represent statistically significant differences between the values (P < 0.05). Abbreviations: Cryo-TEM, cryogenic transmission electron microscopy; FHSO, fully hydrogenated soybean oil; SO, soybean oil; SSHE, scraped surface heat exchanger; TAG, triacylglycerol; XRD, X-ray diffraction. Adapted from Acevedo & Marangoni (2013) with permission from Springer Science and Business Media.

The enhanced growth of the nanocrystals in the direction of their long axis may be related to their preferred orientation, produced upon application of shear during crystallization. Mazzanti et al. (2003) previously indicated that the particle orientation in the direction of the shear field is in fact a consequence of the anisotropic shape of the nanocrystallites. An additional piece of information from the research published by these authors is that although the nanoplatelet geometry could not be imaged, they were able to describe the growth of crystals in the presence or absence of shear fields. In particular, they measured and reported correlation lengths (D) that we identify today as nanoplatelet thicknesses (Mazzanti et al. 2003, 2005, 2007, 2009). www.annualreviews.org • Nanostructured Fat Crystal Systems


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Brief overview of the effects of external fields on the nanostructure of plastic fatsa

Table 2

External fieldb

FHCO:HOSO

FHSO:SO

Static

2.4

2.3

SSHE 25 s−1

ND

3.6

LS 30 s−1

ND

2.7

s−1

ND

2.7

LS 300 s−1

3.4

ND

Slow cooling rate (1◦ C/min)

2.4

ND

Fast cooling rate (10◦ C/min)

4.4

ND

LS 240


Abbreviations: FHCO, fully hydrogenated canola oil; FHSO, fully hydrogenated soybean oil; HOSO, high oleic sunflower oil; LS, laminar shear; ND, not determined; SO, soybean oil; SSHE, scraped surface heat exchanger. a Nanoplatelet aspect ratios obtained for blends of FHCO in HOSO and FHSO in SO before and after crystallization under different external fields. b −1 s indicates shear rate.

Regarding the effect of cooling rate, as mentioned in Section 3.2.1, for FHCO:HOSO samples, nanoplatelets decrease in size as the cooling rate increases. Nonetheless, the aspect ratio increases (Table 2), indicating their preferential longitudinal growth. Therefore, our current thinking suggests that most fat crystallization under shear always induces longitudinal growth of the nanoplatelets.

4. RELATIONSHIP BETWEEN FAT NANOSTRUCTURE AND MACROSCOPIC PROPERTIES 4.1. Oil-Binding Capacity The ability of a fat crystal network to entrap liquid oil is an essential material property that directly impacts the functionality and stability of food products (Aguilera et al. 2004). Even though knowledge is still lacking on the mechanisms controlling oil migration through a fat matrix, much work has been performed in this area. The capacity of fat crystals to bind and retain liquid oil within their crystal network has been described to depend on molecular composition (Chawla & deMan 1990), thermal properties (deMan et al. 1995), intercrystalline interactions, wetting properties of fat crystals ( Johansson & Bergensta˚hl 1995), and crystal size (Dibildox-Alvarado et al. 2004, Marty et al. 2009). Special attention has been focused on the study of the effects of changes in crystal size and orientation, with respect to the plane of movement, on oil migration in fat systems. For example, Dibildox-Alvarado et al. (2004) reported a higher oil loss in materials composed of larger mesocrystals that were achieved by crystallization of the fat at slow cooling rates. In addition, Marty & Marangoni (2009) investigated oil migration kinetics of different cocoa butters. They demonstrated that higher permeability coefficients were associated with larger mesoparticle sizes and smaller nanocrystal thicknesses, suggesting that both the micro- and nanostructure of the material play a significant role in the oil migration process. However, there still is much to accomplish on this topic. In particular, there is still little information available on the influence and/or relationship of the nanostructural level on oil migration through the crystal network. Recently, Acevedo and collaborators (Acevedo & Marangoni 2013; Acevedo et al. 2012a,b) studied the effects of external shear fields during crystallization on the nanostructure of fats and their relationship to oil-binding capacity (OBC). In their studies, OBC, which is defined as the 3.18

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a

0.3 10 0.2 267 ± 11 5

0.1 0.0


15

OL (% day–1)

171 ± 10

185 ± 6

OL (% day–1)

OL (% day–1)

0.4

b 20

15

10 Static 30 s–1 240 s–1

5

196 ± 5 0 s–1 Static

25 s–1 SSHE

30 s–1 LS

240 s–1 LS

0

0

0

100

p. tem all w >

200

300

400

500

Nanoequivalent diameter (nm)

Figure 14 Relationship between OL values and nanocrystal equivalent diameters of 45:55 FHSO:SO samples crystallized statically and under shear. (a) OL values observed in blends before and after crystallization under different shear fields: static, SSHE, and LS crystallization. The number on each bar corresponds to the calculated nanoplatelet equivalent diameter. (b) Correlation between OL values and nanoparticle equivalent diameters of blends before and after being subjected to crystallization under LS rates of 30 and 240 s−1 and wall temperatures of −10, 0, and 20◦ C. Abbreviations: FHSO, fully hydrogenated soybean oil; LS, laminar shear; OL, oil lost; SO, soybean oil; SSHE, scraped surface heat exchanger. Adapted from Acevedo et al. (2012a) and Acevedo & Marangoni (2013) with permission from the Royal Society of Chemistry and Springer Science and Business Media.

physicochemical property of fat crystals to bind and trap liquid oil, was determined through the measurement of the amount of oil lost (OL) from the fat sample under specific conditions (Dibildox-Alvarado et al. 2004). These latest works illustrate the fact that, in general, crystallization under shearing conditions induced a large increase in OL compared to static conditions (Figure 14). In addition, LS treatment at 30 s−1 resulted in the lowest OL from the sample, suggesting that this processing inflicted a lower grade of structural damage upon the matrix. Although the SSHE and mild LS processing can generate comparable shear rates (25 s−1 versus 30 s−1 ), their impact on the matrix OBC is evidently different, crystallization in an SSHE being more deleterious. Furthermore, for laminar processing, as the shear rate increases, so does OL. These results are in close agreement with those reported by Da Pieve et al. (2010). These authors stated that shear processing causes the formation of weak networks made of small crystal clusters weakly interacting among each other and, thus, characterized by a low OBC. Regarding the relationship between OL and nanoscale structure, oil loss and platelet size appear to be related, albeit not in a linear fashion. For low or intermediate shear rates achieved either with turbulent or laminar processing, the increase in OL is accompanied by an increase in the size of nanoplatelets. However, upon crystallization under LS rates of 240 s−1 , fat blends yield significantly higher OL values, whereas nanocrystal size increase is not evident (Figure 14b). Acevedo et al. (2012a) explained that under these shearing conditions, large structural damage may be inflicted upon the network. Moreover, 240 s−1 is close to the critical shear rate of 300 s−1 , above which formation of smaller nanocrystals is favored. Matrix permeability depends strongly on crystal size. It is widely accepted that fat crystal networks structured by small crystals have an increased crystalline surface area, which improves interaction with the oil and reduces OL (Bot et al. 2009, Omonov et al. 2010). As expected, when fat mixtures were sheared at the same rate, the higher the wall temperature used (−10, 0, and 20C◦ from left to right in Figure 14b), the larger the nanoplatelets formed and hence the higher the amount of oil expelled from the samples. www.annualreviews.org • Nanostructured Fat Crystal Systems


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Interestingly, Da Pieve et al. (2010) also reported a positive relationship between nanocrystal dimensions and OL from monoacylglycerol in oil samples. Even though these researchers measured nanoplatelet thickness, represented by the domain size values, they found larger nanocrystal thicknesses in sheared blends.

4.2. Rheological Parameters

σ∗ ≈

1 6δ d −D f, a

a

(2)

b Static

7.0

3.5

6.5 3.0 4.0 2.0 0.0

0 s–1

25 s–1

30 s–1

240 s–1

Static

SSHE

LS

LS

2.5

log(G') (Pa)

4.0

log(σ*) (Pa)

log(G') (Pa)

7.5

30 s–1

240 s–1

LS

LS

8

4

6

3

4

2

2

1

0

–10

0

20 –10

0

20 –10

0

20

log(σ*) (Pa)


The mechanical properties of edible fats are strongly correlated with their functionality. From a structural perspective, mechanical properties depend on many factors such as SFC, the polymorphism of the solid state, and the crystal habit of the network (Marangoni et al. 2012). The analysis of the rheological properties of blends crystallized under shear fields and their relationship to matrix nanostructure was addressed by Acevedo and coworkers (Acevedo & Marangoni 2013; Acevedo et al. 2012a,b). These authors, working with FHSO:SO blends subjected to crystallization under different shear regimes, reported that the storage moduli (G ) and yield stress (σ ∗ ) exhibited analogous behavior with processing, and both parameters decreased upon crystallization under shearing conditions (Figure 15a). Their observations are in agreement with earlier works in which a decrease in the mechanical strength of a fat matrix was observed upon shearing (Da Pieve et al. 2010). Furthermore, Kaufmann et al. (2012), working with milk fat and its blends with rapeseed oil, demonstrated that an intermediate shear rate of 50 s−1 produced a strong crystal network, whereas high shear rates of 500 s−1 broke down the structure of the fat, resulting in low elastic moduli values. Moreover, when the FHSO:SO blends were crystallized under LS at three different wall temperatures (Figure 15b), it became evident that the decrease in G and σ ∗ was more pronounced as the wall temperatures increased. Acevedo et al. (2012a) explained these results within the framework of the model of σ ∗ proposed by Marangoni & Rogers (2003):

0

Temperature (°C)

Figure 15 Log(G ) (red bars, left axes) and log(σ ∗ ) (blue bars, right axes) of 45:55 FHSO:HOSO blends crystallized under different external shear fields. (a) Comparison of the log(G ) and log(σ∗ ) values obtained in blends before and after crystallization under different shear fields: static, SSHE, and LS crystallization. (b) Comparison of the log(G ) and log(σ ∗ ) values obtained in blends before and after being subjected to crystallization under LS rates of 30 and 240 s−1 and wall temperatures of −10, 0, and 20◦ C. Abbreviations: FHSO, fully hydrogenated soybean oil; G , storage modulus; HOSO, high oleic sunflower oil; LS, laminar shear; SSHE, scraped surface heat exchanger; σ ∗ , yield stress. Adapted from Acevedo et al. (2012a) and Acevedo & Marangoni (2013) with permission from the Royal Society of Chemistry and Springer Science and Business Media. 3.20

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4,000

15

a

r 2 = 0.940

ST

LS 30 s–1 5

ST

3,000

10

σ* (Pa)

G' (Pa × 106)

r 2 = 0.910

LS 240 s–1

2,000 1,000

LS 30 s–1 SSHE

LS 240 s–1

SSHE 0 160

180

200

220

240

0 160

260

200

220

240

260

15

b

3 10

σ* (Pa × 106)

G' (Pa × 106)


180

Nanoplatelet equivalent diameter (nm)


5 0 –5 100

Static 30 s–1 240 s–1

2 1 0

200

300

400


500

–1 100

> wall temp. 200

300

400

500


Figure 16 Relationship between G and σ ∗ and nanoparticle equivalent diameters of FHSO:SO blends crystallized under different external fields. (a) Fat mixtures before and after crystallization under different shear fields: ST, SSHE, and LS crystallization. (b) Fat blends before and after being subjected to crystallization under LS rates of 30 and 240 s−1 and wall temperatures of −10, 0, and 20◦ C (left to right). Abbreviations: FHSO, fully hydrogenated soybean oil; LS, laminar shear; SO, soybean oil; SSHE, scraped surface heat exchanger; ST, static. Adapted from Acevedo et al. (2012a) and Acevedo & Marangoni (2013) with permission from the Royal Society of Chemistry and Springer Science and Business Media.

where σ ∗ is a function of the crystal-melt interfacial tension (δ), the primary particle diameter (a), the volume fraction of solids (), and the difference between the Euclidean dimension of the embedding space (d ) and the fractal dimension (Df ) of the fat crystal network. The basis of the reduction in σ ∗ of the systems after the application of external fields during crystallization could be the increase in nanoplatelet size induced by these conditions. An interesting relationship between the rheology of the materials and nanoparticle sizes has been previously observed (Acevedo & Marangoni 2013; Acevedo et al. 2012a,b). Independent of the external fields applied, an inverse correlation between nanocrystal size and the G and σ ∗ values was reported (Figure 16a,b). Acevedo and collaborators pointed out the importance of the observed relationships, as they could potentially be used for predictive purposes. Additionally, the regressions of all the plots have r2 values greater than 0.9 for both parameters, confirming their strong relationship to nanocrystal size. This is in agreement with previous work, in which smaller crystal sizes were associated with stronger networks (Campos et al. 2002, Pérez-Mart´ınez et al. 2007). Lower values of G that corresponded to smaller nanocrystals were obtained for highly sheared samples (Figure 16a). This behavior was attributed to the large physical damage inflicted upon the network and the fact that shear rates of 240 s−1 are close to the critical shear value. Regarding www.annualreviews.org • Nanostructured Fat Crystal Systems


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the effect of wall temperature at equivalent shear rates (Figure 16b), for all shear rates, the higher the temperature, the lower the mechanical strength of the material. The effect of wall temperature during shearing seems to be more pronounced at relatively low LS rates (30 s−1 ), providing further evidence of the substantial structural damage that takes place upon shearing at higher rates. Therefore, the referenced works suggest that the solid-like macroscopic properties of fat crystal networks depend highly on their structure at the nanometer range (nanostructure).

5. CONCLUSIONS


In this review, we outlined the current knowledge on fat nanostructure as well as the latest findings on the effects of external fields at this length scale. Even though numerous advances relative to fat crystallization at the nanoscale have been made, many questions remain unanswered. For instance, understanding the process taking place when a crystalline nanoplatelet aggregates into larger mesoscale structures has become a research priority. With recent advances in technology and instrumentation, we expect to soon be able to probe nanocrystal structures during growth and storage, which will significantly advance this field of research. We also expect that the new technologies in current development will lead to a clearer understanding of the relationship between fat nanostructure and macroscopic functionality, enhancing our ability to control crystallization and, thus, ensure better-quality foods. The nanostructure of fats deserves to be further explored, as nanoscale engineering has the potential to significantly improve the design of fat-structured food products with targeted macroscopic functionality.

DISCLOSURE STATEMENT The authors are not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTS The authors thank the Natural Sciences and Engineering Research Council of Canada and the Advanced Foods and Materials Network for financial support.

LITERATURE CITED Acevedo NC. 2012. Characterization of the nanostructure of triacylglycerol crystal networks. In StructureFunction Analysis of Edible Fats, ed. AG Marangoni, pp. 5–24. Urbana, IL.: AOCS Acevedo NC, Block JM, Marangoni AG. 2012a. Critical laminar shear-temperature effects on the nano- and mesoscale structure of a model fat and its relationship to oil binding and rheological properties. Faraday Discuss. 158:171–94 Acevedo NC, Block JM, Marangoni AG. 2012b. Unsaturated emulsifier-mediated modification of the mechanical strength and oil binding capacity of a model edible fat crystallized under shear. Langmuir 8(46):16207– 17 Acevedo NC, Marangoni AG. 2010a. Characterization of the nanoscale in triacylglycerol crystal networks. Cryst. Growth Des. 10:3327–33 Acevedo NC, Marangoni AG. 2010b. Towards nanoscale engineering of triacylglycerol crystal networks. Cryst. Growth Des. 10:3334–39 Acevedo NC, Marangoni AG. 2013. Functionalization of non-interesterified mixtures of fully hydrogenated fats using shear processing. Food Bioprocess Technol. 7(2):575–87 3.22

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Acevedo NC, Marangoni AG. 2014. Engineering the functionality of blends of fully hydrogenated and nonhydrogenated soybean oil by addition of emulsifiers. Food Biophys. In press. doi: 10.1007/s11483-0149340-9 Acevedo NC, Peyronel MF, Marangoni AG. 2011. Nanoscale structure intercrystalline interactions in fat crystal networks. Curr. Opin. Colloid Interface Sci. 16:374–83 Aguilera JM, Michel M, Mayor G. 2004. Fat migration in chocolate: diffusion or capillary flow in a particulate solid?—A hypothesis paper. J. Food Sci. 69:167–74 Ahmadi L, Wright AJ, Marangoni AG. 2008. Chemical and enzymatic interesterification of tristearin/trioleinrich blends: chemical composition, solid fat content and thermal properties. Eur. J. Lipid Sci. Technol. 110:1014–24 Awad TS, Rogers MA, Marangoni AG. 2004. Scaling behavior of the elastic modulus in colloidal networks of fat crystals. J. Phys. Chem. B 108:171–79 Bellare JR. 1988. Cryo-electron and optical microscopy of surfactant microstructures. Ph.D. Thesis, Univ. Minn., Minneapolis Bennema P, Hollander FFA, Boerrigther SXM, Grimbergen RFP, Van de Streek J, Meekes H. 1988. Morphological connected net-roughening transition theory. In Crystallization and Polymorphism of Fats and Fatty Acids, ed. N Garti, K Sato, pp. 99–150. New York: Marcel Dekker Bot A, Veldhuizen YSJ, den Adel R, Roijers EC. 2009. Non-TAG structuring of edible oils and emulsions. Food Hydrocoll. 23:1184–89 Campos R, Narine S, Marangoni AG. 2002. Effect of cooling rate on the structure and mechanical properties of milk fat and lard. Food Res. Int. 35:971–81 Chawla P, deMan JM. 1990. Measurement of the size distribution of fat crystals using a laser particle counter. J. Am. Oil Chem. Soc. 67:329–32 Chawla P, deMan JM, Smith AK. 1990. Crystal morphology of shortenings and margarines. Food Struct. 9:329–36 Chapman D. 1962. The polymorphism of glycerides. Chem. Rev. 62:433–56 Clarkson CE, Malkin T. 1934. Alteration in long-chain compounds. Part II. An X-ray and thermal investigation of the triglycerides. J. Chem. Soc. 139:666–71 Da Pieve S, Calligaris S, Co E, Nicoli MC, Marangoni AG. 2010. Shear nanostructuring of monoglyceride organogels. Food Biophys. 5:211–17 deMan JM, Beers AM. 1987. Fat crystal networks: structure and rheological properties. J. Texture Stud. 18:303–18 deMan L, deMan JM, Blackman B. 1995. Effect of tempering on the texture and polymorphic behaviour of margarine fats. Fat Sci. Technol. 97:55–60 Dibildox-Alvarado E, Neves Rodrigues J, Gioielli LA, Toro-Vazquez JF, Marangoni AG. 2004. Effects of crystalline microstructure on oil migration in a semisolid fat matrix. Cryst. Growth Des. 4:731–36 Dixon GD, Parekh JV. 1979. Use of the cone penetrometer for testing the firmness of butter. J. Texture Stud. 10:421–34 Eur. Food Saf. Auth. 2004. Opinion of the Scientific Panel on Dietetic Products, Nutrition and Allergies on a request from the Commission related to the presence of trans fatty acids in foods and the effect on human health of the consumption of trans fatty acids. EFSA J. 81:1–49 Gamboa OWD, Gioielli LA. 2006. Crystallization behavior of structured lipids produced from palm kernel fat and fish oil. Qu´ım. Nova 29:646–53 Gidding SS, Lichtenstein AH, Faith MS, Karpyn A, Mennella JA, et al. 2009. Implementing American Heart Association pediatric and adult nutrition guidelines: a scientific statement from the American Heart Association Nutrition Committee of the Council on Nutrition, Physical Activity and Metabolism, Council on Cardiovascular Disease in the Young, Council on Arteriosclerosis, Thrombosis and Vascular Biology, Council on Cardiovascular Nursing, Council on Epidemiology and Prevention, and Council for High Blood Pressure Research. Circulation 119:1161–75 Gunstone FD, Padley FB, eds. 1997. Lipid Technologies and Applications. New York: Marcel Dekker Hayakawa M, deMan JM. 1982. Interpretation of cone penetrometer consistency measurement of fats. J. Texture Stud. 13:201–10 www.annualreviews.org • Nanostructured Fat Crystal Systems


3.23

ARI

13 November 2014

11:9

Heertje I, Leunis M. 1997. Measurement of shape and size of fat crystals by electron microscopy. LWT Food Sci. Technol. 30:141–46 Heertje I, Leunis M, van Zeyl WJM, Berends E. 1987. Product microscopy of fatty products. Food Microstruct. 6:1–8 Heertje I, van Eendenburg J, Cornelissen JM, Juriaanse AC. 1988. The effect of processing on some microstructural characteristics of fat spreads. Food Microstructure. 7:189–93 Herrera ML, Hartel RW. 2000. Effect of processing conditions on physical properties of a milk fat model system: microstructure. J. Am. Oil Chem. Soc. 77:1197–204 Himavan C, Starov VM, Stapley AGF. 2006. Thermodynamic and kinetic aspects of fat crystallization. Adv. Colloid Interface Sci. 122:3–33 Jensen LH, Mabis AJ. 1963. Crystal structure of β-tricaprin. Nature 197:681–82 Jensen LH, Mabis AJ. 1966. Refinement of the structure of β-tricaprin. Acta Crystallogr. 21:770–78 Jewell GG, Meara ML. 1970. A new and rapid method for the electron microscopic examination of fats. J. Am. Oil Chem. Soc. 47:535–38 Johansson D, Bergensta˚hl B. 1995. Sintering of fat crystal networks in oil during post-crystallization processes. J. Am. Oil Chem. Soc. 72:911–20 Kaufmann N, De Graef V, Dewettinck K. 2012. Shear-induced crystal structure formation in milk fat and blends with rapeseed oil. Food Biophys. 7(4):308–16 Kloek W, van Vliet T, Walstra P. 2005. Mechanical properties of fat dispersions prepared in a mechanical crystallizer. J. Texture Stud. 36:544–68 Langford JI, Wilson AJC. 1978. Scherrer after sixty years: a survey and some new results in the determination of crystallite size. J. Appl. Cryst. 11:102–13 Levine L. 1993. Scraped surface heat exchangers. Cereal Foods World 38:31–33 MacMillan SD, Roberts KJ, Rossi A, Wells MA, Polgreen MC, Smith IH. 2002. In situ small angle X-ray scattering (SAXS) studies of polymorphism with the associated crystallization of cocoa butter fat using shearing conditions. Cryst. Growth Des. 2:221–26 MacMillan SD, Roberts KJ, Wells MA, Polgreen MC, Smith IH. 2003. Identification of the initial nucleating form involved in the thermal processing of cocoa butter fat as examined using wide angle X-ray scattering (WAXS). Cryst. Growth Des. 3:117–19 Maleky F, Acevedo NC, Marangoni AG. 2012. Cooling rate and dilution affect the nanostructure and microstructure differently in model fats. Eur. J. Lipid Sci. Technol. 114:748–59 Maleky F, Smith A, Marangoni AG. 2011a. Laminar shear effects on crystalline alignments and nanostructure of a triacylglycerol crystal network. Cryst. Growth Des. 11:2335–45 Maleky F, Smith AK, Marangoni AG. 2011b. Thermal and mechanical properties of cocoa butter crystallized under external laminar shear field. Cryst. Growth Des. 11:2429–37 Marangoni AG, Acevedo NC, Maleky F, Co E, Peyronel F, et al. 2012. Structure and functionality of edible fats. Soft Matter 8:1275–300 Marangoni AG, Rogers M. 2003. Structural basis for the yield stress in plastic disperse systems. Appl. Phys. Lett. 82:3239–41 Marangoni AG, Rousseau D. 1996. Is plastic fat rheology governed by the fractal nature of the fat crystal network? J. Am. Oil Chem. Soc. 73:991–93 Martini S, Herrera ML. 2002. X-ray diffraction and crystal size. J. Am. Oil Chem. Soc. 79:315–16 Martini S, Herrera ML, Hartel RW. 2002. Effect of cooling rate on crystallization behavior of milk fat fraction/sunflower oil blends. J. Am. Oil Chem. Soc. 79:1055–62 Marty S, Baker KW, Marangoni AG. 2009. Optimization of a scanner imaging technique to accurately study oil migration kinetics. Food Res. Int. 42:368–73 Marty S, Marangoni AG. 2009. Effects of cocoa butter origin, tempering procedure, and structure on oil migration kinetics. Cryst. Growth Des. 9(10):4415–23 Mazzanti G, Guthrie SE, Marangoni AG, Idziak SHJ. 2007. A conceptual model for shear-induced phase behavior in crystallizing cocoa butter. Cryst. Growth Des. 7(7):1230–41 Mazzanti G, Guthrie SE, Sirota EB, Marangoni AG, Idziak SHJ. 2003. Orientation and phase transitions of fat crystals under shear. Cryst. Growth Des. 3:721–25


FO06CH03-Acevedo

3.24

Acevedo

·

Marangoni



FO06CH03-Acevedo

ARI

13 November 2014

11:9

Mazzanti G, Guthrie SE, Sirota EB, Marangoni AG, Idziak SHJ. 2004. Novel shear-induced phases in cocoa butter. Cryst. Growth Des. 4:409–11 Mazzanti G, Marangoni AG, Idziak SHJ. 2005. Modeling phase transitions during the crystallization of a multicomponent fat under shear. Phys. Rev. E 71:1–12 Mazzanti G, Marangoni AG, Idziak SHJ. 2009. Synchrotron study on crystallization kinetics of milk fat under shear flow. Food Res. Int. 42:682–94 Narine S, Marangoni AG. 1999. Mechanical and structural model of fractal networks of fat crystals at low deformations. Phys. Rev. E 60(6 Pt. B):6991–7000 Narine S, Marangoni AG. 2004. Microstructure. In Fat Crystal Networks, ed. AG Marangoni, pp. 179–255. Boca Raton, FL: CRC Nederveen CJ. 1963. Dynamic mechanical behavior of suspensions of fat particles in oil. J. Colloid Sci. 18:276– 91 Omonov TS, Bouzidi L, Narine S. 2010. Quantification of oil binding capacity of structuring fats: a novel method and its application. Chem. Phys. Lipids 163:728–40 Paulicka FR. 1989. Shortening products. World Conf. Proc. Edible Fats Oils Process. Basic Princ. Modern Pract., Maastricht, Neth., pp. 203–302 Pérez-Mart´ınez D, Alvarez-Salas C, Charo-Alonzo M, Dibildox-Alvarado E, Toro-Vazquez JF. 2007. The ´ cooling rate effect on the microstructure and rheological properties of blends of cocoa butter with vegetable oils. Food Res. Int. 40:47–62 Peschar R, Pop MM, De Ridder DJA, Van Mechelen JB, Driessen RAJ, Schenk H. 2004. Crystal structures of 1,3-distearoyl-2-oleoylglycerol and cocoa butter in the β(V) phase reveal the driving force behind the occurrence of fat bloom on chocolate. J. Phys. Chem. B 108:15450–53 Poot C, Dijkshoorn W, Haighton AJ, Verburg CC. 1975. Laboratory separation of crystals from plastic fats using detergent solution. J. Am. Oil Chem. Soc. 70:69–72 Ribeiro APB, Grimaldi R, Gioielli LA, Oliveira dos Santos A, Cardoso LP, Gonçalves LAG. 2009. Thermal behavior, microstructure, polymorphism, and crystallization properties of zero trans fats from soybean oil and fully hydrogenated soybean oil. Food Biophys. 4:106–18 Rodr´ıguez A, Castro E, Salinas MC, Lopez R, Miranda M. 2001. Interesterification of tallow and sunflower ´ oil. J. Am. Oil Chem. Soc. 78:431–36 Rousseau D, Marangoni AG. 1999. The effects of interesterification on physical and sensory attributes of butterfat and butterfat–canola oil spreads. Food Res. Int. 31:381–88 Rousseau D, Sonwai S. 2008. Influence of the dispersed particulate in chocolate on cocoa butter microstructure and fat crystal growth during storage. Food Biophys. 3:273–78 Sato K. 2001. Crystallization behaviour of fats and lipids—a review. Chem. Eng. Sci. 56:2255–65 Scherrer P. 1918. Bestimmung der Große und der Inneren Struktur von Kolloidteilchen mittels ¨ Rontgenstrahen. Nachrichten Ges. Wiss. Gött. Math.-Phys. Kl. 2:98–100 ¨ Shi Y, Liang B, Hartel RW. 2005. Crystal morphology, microstructure, and textural properties of model lipid systems. J. Am. Oil Chem. Soc. 82:399–408 Shukla A, Rizvi SSH. 1996. Relationship among chemical composition, microstructure and rheological properties of butter. Milchwissenschaft 51(3):144–48 Singh AP, Bertoli C, Rousseau PR, Marangoni AG. 2004. Matching Avrami indices achieves similar hardnesses in palm oil-based fats. J. Agric. Food Chem. 52:1551–57 Sonwai S, Mackley MR. 2006. The effect of shear on the crystallization of cocoa butter. J. Am. Oil Chem. Soc. 83:583–96 Stapley AGF, Tewkesbury H, Fryer PJ. 1999. The effects of shear and temperature history on the crystallization of chocolate. J. Am. Oil Chem. Soc. 76(6):677–85 Tang D, Marangoni AG. 2008. Fractal dimensions of simulated and real fat crystal networks in 3D space. J. Am. Oil Chem. Soc. 85:495–99 Van den Tempel M. 1961. Mechanical properties of plastic disperse systems at very small deformations. J. Colloid Sci. 16:284–96 Van den Tempel M. 1979. Rheology of concentrated suspensions. J. Colloid Interface Sci. 71:18–20 Vuillequez A, Koza L, Youssef B, Bridier M, Saiter JM. 2010. Thermal and structural behavior of palm oil. Influence of cooling rate on fat crystallization. Macromol. Symp. 290:137–45 www.annualreviews.org • Nanostructured Fat Crystal Systems


3.25

FO06CH03-Acevedo

ARI

13 November 2014

11:9


Wassel P, Young NWG. 2007. Food applications of trans fatty acid substitutes. Int. J. Food Sci. Technol. 42:503–17 West AR, ed. 1984. Solid State Chemistry and Its Applications. Chichester, West Sussex, UK: John Wiley & Sons Wiking L, De Graef V, Rasmussen M, Dewettinck K. 2009. Relations between crystallisation mechanisms and microstructure of milk fat. Int. Dairy J. 19:424–30

3.26

Acevedo

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Marangoni
